A review on integrated process planning and scheduling
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paper_title: Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems

paper_content:

This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making. A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include. 1. Machine tool sclection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM). for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling.
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paper_title: Integrated process planning and scheduling in holonic manufacturing systems

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The objective of the research described is to develop an integrated process planning and scheduling system of machine products, aiming at realizing flexible production control in holonic manufacturing systems. The basic architecture of the holonic manufacturing system is discussed from the viewpoint of the integration of the process planning and the scheduling systems. Procedures are proposed to select suitable machining sequences of machining features and suitable sequences of machining equipment, taking into consideration future schedules of machining equipment. A combined method of genetic algorithm and dynamic programming is applied to selection of the machining sequence and the sequence of the machining equipment.
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paper_title: Process Planning and Scheduling for Distributed Manufacturing

paper_content:

An Effective Approach for Distributed Process Planning Enabled by Event-Driven Function Blocks Web-based Polishing Process Planning Using Data Mining Techniques Integration of Rule-based Process Selection with Virtual Machining for Distributed Manufacturing Planning CyberCut: A Coordinated Pipeline of Design, Process Planning and Manufacture Process Planning, Scheduling and Control for One-of-a-Kind Production Setup Planning and Tolerance Analysis Scheduling in Holonic Manufacturing Systems Agent-based Dynamic Scheduling for Distributed Manufacturing A Multi-agent System Implementation of an Evolutionary Approach to Production Scheduling Distributed Scheduling in Multiple-factory Production with Machine Maintenance Resource Scheduling for a Virtual CIM System A Unified Model-based Integration of Process Planning and Scheduling A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing Managing Dynamic Demand Events in Semiconductor Manufacturing Chains by Optimal Control Modelling A Parameter Perturbation Approach to Replanning Operations STEP into Distributed Manufacturing with STEP-NC
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paper_title: Integration of process planning and scheduling— a review

paper_content:

In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.
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paper_title: Agent technology for collaborative process planning: a review

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Agent technology has been considered as a promising approach for developing process planning systems and optimizing process plans in a distributed environment. A number of researchers have attempted to use agent technology in process planning for the purpose of integrating systems, tools and algorithms which are geographically distributed. In this paper, the historical background of agent technology is systematically reviewed. A comprehensive review of agent technology and its applications in manufacturing is presented including the applications of agent in scheduling, control, and enterprise integration and supply chain management. The focus of the paper is on how agent technology can be further developed in the support of collaborative process planning as well as its future research issues and directions in process planning. The current research directions in computer aided process planning (CAPP) and issues in traditional CAPP approaches are also discussed. Three agent-based approaches for process planning are presented. Finally, the key issues in developing agent-based collaborative process planning systems are summarized.
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paper_title: Integration of process planning and scheduling— a review

paper_content:

In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.
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paper_title: Computerized Manufacturing Process Planning Systems

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Preface. List of abbreviations. 1. Introduction to manufacturing (preliminary knowledge). 2. Manufacturing process planning. 3. Impact of computer integrated manufacturing. 4. Group technology in process planning. 5. Automated tolerance analysis for process planning. 6. Computer aided process planning. 7. Implementation of CAPP systems. 8. Feature based design and IGES/PDES/STEP. 9. A survey of CAPP systems. 10. Crucial issues and future trends of CAPP development. 11. Building a CAPP system - a case study. Appendix A: List of raw materials in the database. Appendix B: The block diagrams of the operation sequences. Appendix C: Indication of codes for tool selection. Appendix D: Screen display for running examples. Appendix E: Exercises. Index.
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paper_title: An algorithm for solving the job-shop problem

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In this paper, we propose a branch and bound method for solving the job-shop problem. It is based on one-machine scheduling problems and is made more efficient by several propositions which limit the search tree by using immediate selections. ::: ::: It solved for the first time the famous 10 × 10 job-shop problem proposed by Muth and Thompson in 1963.
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paper_title: Job Shop Scheduling by Local Search

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We present a computational performance analysis of local search algorithms for job shop scheduling. The algorithms under investigation are iterative improvement, simulated annealing, threshold accepting and genetic local search. Our study shows that simulated annealing performs best in the sense that it finds better solutions than the other algorithms within the same amount of running time. Compared to more tailored algorithms, simulated annealing still finds the best results but only under the assumption that running time is of no concern.
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paper_title: A Branch and Bound Algorithm for the Job-Shop Scheduling Problem

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Abstract A fast branch and bound algorithm for the job-shop scheduling problem has been developed. Among other hard problems it solves the 10 × 10 benchmark problem which has been open for more than 20 years. We will give a complete description of this algorithm and will present computational results.
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paper_title: Deterministic Job-Shop Scheduling: Past, Present and Future

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Abstract Due to the stubborn nature of the deterministic job-shop scheduling problem many solutions proposed are of hybrid construction cutting across the traditional disciplines. The problem has been investigated from a variety of perspectives resulting in several analytical techniques combining generic as well as problem specific strategies. We seek to assess a subclass of this problem in which the objective is minimising makespan, by providing an overview of the history, the techniques used and the researchers involved. The sense and direction of their work is evaluated by assessing the reported results of their techniques on the available benchmark problems. From these results the current situation and pointers for future work are provided. © 1999 Elsevier Science B.V. All rights reserved.
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paper_title: Job Shop Scheduling by Simulated Annealing

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We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems. The generalization involves the acceptance of cost-increasing transitions with a nonzero probability to avoid getting stuck in local minima. We prove that our algorithm asymptotically converges in probability to a globally minimal solution, despite the fact that the Markov chains generated by the algorithm are generally not irreducible. Computational experiments show that our algorithm can find shorter makespans than two recent approximation approaches that are more tailored to the job shop scheduling problem. This is, however, at the cost of large running times.
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paper_title: Parallel Taboo Search Techniques for the Job Shop Scheduling Problem

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We apply the global optimization technique called taboo search to the job shop scheduling problem and show that our method is typically more efficient than the shifting bottleneck procedure, and also more efficient than a recently proposed simulated annealing implementation. We also identify a type of problem for which taboo search provides an optimal solution in a polynomial mean time in practice, while an implementation of the shifting bottleneck procedure seems to take an exponential amount of computation time. Included are computational results that establish new best solutions for a number of benchmark problems from the literature. Finally, we give a fast parallel algorithm that provides good solutions to very large problems in a very short computation time. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
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paper_title: A genetic algorithm for the job shop problem

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In this paper we introduce a genetic algorithm whose peculiarities are the introduction of an encoding based on preference rules and an updating step which speeds up the evolutionary process. This method improves on the results gained previously with Genetic Algorithms and has shown itself to be competitive with other heuristics. The same algorithm has been applied to flow shop problems, revealing itself to be considerably more effective than Branch and Bound techniques.
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paper_title: The Shifting Bottleneck Procedure for Job Shop Scheduling

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We describe an approximation method for solving the minimum makespan problem of job shop scheduling. It sequences the machines one by one, successively, taking each time the machine identified as a bottleneck among the machines not yet sequenced. Every time after a new machine is sequenced, all previously established sequences are locally reoptimized. Both the bottleneck identification and the local reoptimization procedures are based on repeatedly solving certain one-machine scheduling problems. Besides this straight version of the Shifting Bottleneck Procedure, we have also implemented a version that applies the procedure to the nodes of a partial search tree. Computational testing shows that our approach yields consistently better results than other procedures discussed in the literature. A high point of our computational testing occurred when the enumerative version of the Shifting Bottleneck Procedure found in a little over five minutes an optimal schedule to a notorious ten machines/ten jobs problem on which many algorithms have been run for hours without finding an optimal solution.
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paper_title: Integration of process planning and scheduling— a review

paper_content:

In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.
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paper_title: A very fast TS/SA algorithm for the job shop scheduling problem

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The job shop scheduling problem (JSP) is one of the most notoriously intractable NP-complete optimization problems. Over the last 10-15 years, tabu search (TS) has emerged as an effective algorithmic approach for the JSP. However, the quality of solutions found by tabu search approach depends on the initial solution. To overcome this problem and provide a robust and efficient methodology for the JSP, the heuristics search approach combining simulated annealing (SA) and TS strategy is developed. The main principle of this approach is that SA is used to find the elite solutions inside big valley (BV) so that TS can re-intensify search from the promising solutions. This hybrid algorithm is tested on the standard benchmark sets and compared with the other approaches. The computational results show that the proposed algorithm could obtain the high-quality solutions within reasonable computing times. For example, 17 new upper bounds among the unsolved problems are found in a short time.
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paper_title: The Job Shop Scheduling Problem: Conventional and new Solution Techniques

paper_content:

A job shop consists of a set of different machines that perform operations on jobs. Each job has a specified processing order through the machines, i.e. a job is composed of an ordered list of operations each of which is determined by the machine required and the processing time on it. There are no precedence constraints among operations of different jobs. Operations can not be interrupted (non-preemption) and each machine can handle only one job at a time. Consequently, each job can be performed on only one machine at a time. The operation sequences on the machines are unknown and have to be determined in order to minimize the makespan, i. e. the time required to complete all jobs.
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paper_title: Dynamic process planning — The static phase

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Abstract Dynamic process planning is concerned with the integration of process planning with scheduling. This paper presents the computer-aided process planning (CAPP) system, PARIS, that is meant to be integrated with a scheduling system. The approach to dynamic process planning implemented divides the planning tasks into the two phases: static and dynamic planning. This paper discusses the overall approach and focusing on the details of the implementation of the static phase. An example is used to illustrate the concepts presented.
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paper_title: Integration of scheduling with computer aided process planning

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Abstract Computer aided process planning (CAPP) and scheduling are two major activities in a modern manufacturing system. The existing CAPP systems have not taken account of shop floor conditions while developing process plans. This paper discusses the importance of integration of scheduling and CAPP and proposes a method for the same. There can be several methods to machine a part and several machines capable of performing the process required to complete the part. Based on this concept, this paper suggests a method of scheduling and its integration with CAPP, so that on-line process plan can be generated taking into account the availability of machines and alternative routes. A scheduling factor for an operation and machine combination has been defined taking into consideration the actual working conditions and capabilities of the machines. Finally operation–machine assignment is made on the basis of these actual scheduling factors. This helps in generating more realistic process plans and helps in improving the efficiency of the manufacturing system as a whole.
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paper_title: Process Planning and Scheduling for Distributed Manufacturing

paper_content:

An Effective Approach for Distributed Process Planning Enabled by Event-Driven Function Blocks Web-based Polishing Process Planning Using Data Mining Techniques Integration of Rule-based Process Selection with Virtual Machining for Distributed Manufacturing Planning CyberCut: A Coordinated Pipeline of Design, Process Planning and Manufacture Process Planning, Scheduling and Control for One-of-a-Kind Production Setup Planning and Tolerance Analysis Scheduling in Holonic Manufacturing Systems Agent-based Dynamic Scheduling for Distributed Manufacturing A Multi-agent System Implementation of an Evolutionary Approach to Production Scheduling Distributed Scheduling in Multiple-factory Production with Machine Maintenance Resource Scheduling for a Virtual CIM System A Unified Model-based Integration of Process Planning and Scheduling A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing Managing Dynamic Demand Events in Semiconductor Manufacturing Chains by Optimal Control Modelling A Parameter Perturbation Approach to Replanning Operations STEP into Distributed Manufacturing with STEP-NC
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paper_title: Web-based decision making for collaborative manufacturing

paper_content:

This paper presents methodologies of web-based decision making for collaborative manufacturing, including web-based knowledge sharing, distributed process planning, dynamic scheduling, real-time monitoring and remote control, targeting distributed yet collaborative manufacturing environments. The web-based decision making is enabled by a framework that allows users to plan and control manufacturing operations based on information either gathered via the Web or collected from manufacturing devices. The objective of this research is to develop an integrated system for web-based collaborative planning and control, supported by real-time monitoring for dynamic scheduling. Details on the principle of the framework, system architecture, and a proof-of-concept prototype are reported in this paper. An example of remote machining is chosen as a case study to demonstrate the effectiveness of this framework toward web-based collaborative manufacturing.
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paper_title: Integration of process planning and scheduling functions

paper_content:

Automated process planning (APP) has received a considerable amount of attention in recent years. This has mainly been due to APP allowing for the bridging of the gap between design and manufacturing, and for its automation of the related tedious human task. While there have been several efforts in developing interfaces between computer-aided design (CAD) and APP, little attention has been given to the integration of APP and scheduling, which is likely to be of even higher importance. This paper addresses the basic issues involved in the integration of the two functions, demonstrates a methodology and the potential benefits of the integrated approach by an example, and presents directions for future research.
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paper_title: IPPM – A Prototype to Integrate Process Planning and Job Shop Scheduling Functions

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Summary Functional integration has taken the foreground in the current manufacturing system development. Process planning and job shop scheduling are two main manufacturing functions involved in shop floor activities. An integrated process planning model (IPPM) is introduced in this paper. The two functions (process planning and job shop scheduling) are truly integrated by means of distributed approach which is different from current nonlinear and alternative process planning approaches. In this paper, the two functions are integrated at task stage, while the nonlinear and alternative approaches are taken place at result stage which cannot be considered as real integration but rather interface. The introduced IPPM works in three levels, based on manufacturing resource availability and real time feedback from shop floor, they are pre-planning, pairing planning, and final planning. The IPPM consists of three modules, introduced in detailed in the paper, they are: process planning module, production scheduling module, and decision making module. An example is provided to illustrate the model. This paper is to be considered as a contribution to the research efforts in process planning and integrated manufacturing.
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paper_title: Methods for integration of process planning and production planning

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Abstract Integration is often considered to be a tangible word. In fact integration is diffuse: it does not express in any detail how to conduct integration initiatives. On the other hand, integration docs represent a very efficient way of improving the operational characteristics of a manufacturing facility. The concepts provided for integration are derived from the discovery of time-dependent tasks within the process planning domain. When operating in dynamic environments it is important to separate static and dynamic controlled decision making and to provide architectures capable of providing the required dynamic knowledge at the time when the decisions are made. A natural expansion of this hypothesis is the development of an approach for process planning conducted concurrently with the other engineering activities within product life. This article introduces a practical approach to the integration of process planning and production control business functions. The approach outlines systematic methods t...
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paper_title: Decision making on the factory floor: An integrated approach to process planning and scheduling

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Abstract Computers make accesible large amounts of information to the different levels of manufacturing organizations. However, this information can be of limited use if adequate decision making methodology is not applied. Very often, decisions made on the factory floor have a substantial impact on the performance of the entire manufacturing system. Process planning and scheduling are two activities that influence significantly these decisions. The common aspect of these activities is the assignment of various factory resources to the production tasks. The method presented in this paper seeks to use this commonality to integrate process planning and scheduling.
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paper_title: An overview of distributed process planning and its integration with scheduling

paper_content:

Process planning and scheduling are considered as two separate and distinct phases in manufacturing. Traditional approaches to these problems do not consider the constraints of both domains simultaneously and can only result in sub-optimal solutions. This separation becomes a barrier to further improving manufacturing performance. Most process planning and scheduling systems are off-line and centralized. The process plans generated off-line may become invalid at the time of plan execution. On the other hand, scheduling based on rigid process plans may have already lost the optimal options. Today, there is an increasing need for the integration of process planning and scheduling to generate more realistic and practical solutions. This paper provides a literature review on the integration of process planning and scheduling, particularly on agent-based approaches. It is followed by an overview of our approach toward distributed process planning and scheduling. The paper is finally concluded with future research opportunities.
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paper_title: Integration of process planning and scheduling— a review

paper_content:

In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.
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paper_title: Integration of process planning and scheduling in a job shop environment

paper_content:

Today’s manufacturing systems are striving for an integrated manufacturing environment. To achieve truly computer-integrated manufacturing systems (CIMS), the integration of process planning and production scheduling is essential. This paper proposes a framework for integration of process planning with production scheduling in a job shop environment for axisymmetric components. Based on the design specifications of incoming parts, feasible process plans are generated taking into account the real time shop floor status and availability of machine tools. The scheduling strategy prioritizes the machine tools based on cost considerations.
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paper_title: Job shop scheduling with alternative process plans

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Abstract Successful implementation of automated manufacturing systems highly depends on effective utilization of resources. Efficient scheduling algorithms for alternative process plans may increase the throughput rate and guarantee a reasonable return on investment. This paper investigates an optimization methodology for scheduling jobs in a just-in-time environment. We consider the non-preemptive case where each job consists of a distinct number of operations to be processed in a specified order. Each operation has to be processed on one of a set of resources (e.g. machines) with possibly different efficiency and hence processing time. The objective is to minimize the sum of the weighted quadratic tardiness of the jobs. We obtain a fast near-optimal algorithm with guaranteed bounds for the distance to the optimum by using Lagrangian relaxation and show that just one relaxation suffices.
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paper_title: Evaluating the impact of alternative plans on manufacturing performance

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In recent years, process planners have become interested in the development of dynamic process planning systems that can interface to scheduling systems providing alternative process plans to increase flexibility in scheduling. However, deciding how many alternatives are needed has not been addressed in any previous studies. This paper presents the results of a simulation-based study aimed at characterizing the benefit provided from having alternative plans available for use in scheduling. This benefit is quantified in terms of the overall performance of a job-shop manufacturing environment. The results of this study indicate that the advantage gained by increasing the number of alternative process plans diminishes rapidly. In fact, under some conditions for the particular system studied, increasing the number of alternatives actually resulted in degraded system performance. Based on these results developers of process planning systems and methodologies need to evaluate carefully the benefit of expending time and resources on the generation of alternative plans or optimal plans.
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paper_title: A prototype of a feature-based multiple-alternative process planning system with scheduling verification

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The primary objective of this research was to develop a prototype feature-based multiple-alternative process planning system in which the process plan would be generated directly from design and available factory facility information. An overall removable volume is generated by graphically comparing the 3D part and 3D workpiece blank. The manufacturing features are decomposed into a series of general manufacturing features by using a mixed graph-based and rule-based algorithm. The multiple-alternative process plan generation is based on recognized manufacturing features and various production rules. After generating multiple process plans, each process plan is allocated the possible manufacturing scheduling time and the candidate process plans are retrieved based on the required due day. An example problem is presented to illustrate the functionality of the prototype system. This research presents an alternative method that provides useful information to the factory planner and controller to facilitate production.
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paper_title: Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems

paper_content:

This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making. A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include. 1. Machine tool sclection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM). for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling.
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paper_title: A mathematical model for job shop scheduling with multiple process plan consideration per job

paper_content:

In this paper, a mixed integer programming model is formulated for scheduling a set of jobs through a shop when each job is supplied or provided with multiple process plans or process routings. Simultaneous selection of a process plan for each job and the sequencing of the jobs through the machines in the shop based on the set of selected process plans is addressed. The procedure developed seeks to integrate the selection of machines for each job and the sequencing of jobs on each machine based on the objective of minimizing production makespan. the application of the procedure is demonstrated with an example problem. The following conclusions were drawn as a result of the research: (1) the procedure developed produces optimal or near optimal solution; (2) the benefit from the developed approach is that it allows a shop to adaptively select process plans for jobs to optimize on production makespan. By combining solution quality with scheduling flexibility and efficiency, the productivity of a shop can be ...
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paper_title: A negotiation based scheduling for items with flexible process plans

paper_content:

A job-shop scheduling method is described utilizing a negotiation-based algorithm in autonomous distributed systems. Elements of a production system such as jobs and machines are regard as agents that act like an independent profit maker. A negotiation procedure is suggested including price-based bid construction and price revising mechanism. We propose a simulation-based iteration procedure in order to revise the decision making parameters. It is shown that the iterative procedure eventually improves the global performance of the entire system. The proposed method is expected to have flexibility against various system alternations, addition or deletion of jobs or sudden failure of machines. We develop a prototype software that utilizes the object oriented concept.
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paper_title: Integration of process planning and scheduling -- A modified genetic algorithm-based approach

paper_content:

Traditionally, process planning and scheduling for parts were carried out in a sequential way, where scheduling was done after process plans had been generated. Considering the fact that the two functions are usually complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved greatly. In this paper, a new integration model and a modified genetic algorithm-based approach have been developed to facilitate the integration and optimization of the two functions. In the model, process planning and scheduling functions are carried out simultaneously. In order to improve the optimized performance of the modified genetic algorithm-based approach, more efficient genetic representations and operator schemes have been developed. Experimental studies have been conducted and the comparisons have been made between this approach and others to indicate the superiority and adaptability of this method. The experimental results show that the proposed approach is a promising and very effective method for the integration of process planning and scheduling.
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paper_title: Integration of process planning and job shop scheduling for dynamic and adaptive manufacturing control

paper_content:

The concept and prototypical implementation of a flexibly integrated production planning and scheduling system called FIPS (flexible integration of production system) is described. It consists of three major parts: a feature-recognizing system (FREDOS) that evaluates the 3-D-BREP (boundary representation) geometrical description of a part in terms of generic features that correspond to the execution of a basic manufacturing operation; a static process planning system (SSM) that identifies all combinations of manufacturing resources that are suited to produce the part; and a dynamic resource-allocation system (DRS) that decides online which of the possible resources has to be used in order to execute a manufacturing order. The assignment strategies may be individually specified by the application using the specification language SORC. A description is given of the basic ideas behind these systems along with a short overview of their implementation. >
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paper_title: A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling

paper_content:

This paper addresses the integrated problem of process planning and scheduling in job shop flexible manufacturing systems. Due to production flexibility, it is possible to generate many feasible process plans for each job. The two functions of process planning and scheduling are tightly interwoven with each other. The optimality of scheduling depends on the result of process planning. The integration of process planning and scheduling is therefore important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. For the performance improvement of the algorithm, it is important to enhance population diversity and search efficiency. We adopt the strategies of localized interactions, steady-state reproduction, and random symbiotic partner selection. Efficient genetic representations and operator schemes are also considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and an existing cooperative coevolutionary algorithm. The experimental results show that the proposed algorithm outperforms the compared algorithms.
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paper_title: Scheduling in a production environment with multiple process plans per job

paper_content:

Traditional job shop scheduling problems generally assume that there is a single feasible routing with which a part can be processed in a shop. In today's flexible production systems, this assumption is rarely true. For most manufactured parts, it is possible to generate multiple ways to sequence the operations required to realize the finished product. Each feasible ordering of the operations generates a process plan. Multiple process plans per job increase production flexibility, while at the same time they increase planning and scheduling difficulty. In this paper, the problem of scheduling multiple jobs with each having multiple process plans in a job shop environment is addressed. The problem is modelled and solved using a mathematical approach. Because of the high computational effort required to solve the model using an exact solution procedure, two algorithms were developed and compared against solutions obtained by an optimum finding technique. The results of the test problems indicate that one of...
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paper_title: Job-shop scheduling with processing alternatives

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Abstract In this paper we study an extension of the job-shop scheduling problem where the job routings are directed acyclic graphs that can model partial orders of operations and that contain sets of alternative subgraphs consisting of several operations each. We develop two heuristic algorithms for our problem: a tabu search and a genetic algorithm. The two heuristics are based on two common subroutines: one to insert a set of operations into a partial schedule and another to improve a schedule with fixed routing alternatives. The first subroutine relies on an efficient operation insertion technique and the second one is a generalisation of standard methods for classical job-shop scheduling. We compare our heuristics on various test problems, including the special case MPM job-shop scheduling. Moreover, we report on the success of the two subroutines on open-shop instances.
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paper_title: A simulated annealing-based optimization approach for integrated process planning and scheduling

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A job shop needs to deal with a lot of make-to-order business, in which the orders are usually diverse in types but each one is small in volume. To increase the flexibility and responsiveness of the job shop in the more competitive market, process planning and scheduling modules have been actively developed and deployed. The functions of the two modules are usually complementary. It is ideal to integrate them more tightly to achieve the global optimization of product development and manufacturing. In this paper, a unified representation model and a simulated annealing-based approach have been developed to facilitate the integration and optimization process. In the approach, three strategies, including processing flexibility, operation sequencing flexibility and scheduling flexibility, have been used for exploring the search space to support the optimization process effectively. Performance criteria, such as makespan, the balanced level of machine utilization, job tardiness and manufacturing cost, have been systematically defined to make the algorithm adaptive to meet various practical requirements. Case studies under various working conditions and the comparisons of this approach with two modern evolutionary approaches are given. The merits and characteristics of the approach are thereby highlighted.
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paper_title: An integrated scheme for process planning and scheduling in FMS

paper_content:

Process planning and scheduling are the two important manufacturing functions involved in any shop floor activities. As functional integration is essential to realize the benefits of computer integrated manufacturing, a scheme for integration of process planning and scheduling has been introduced in this paper. The proposed scheme can be implemented in a company with existing process planning and scheduling departments when multiple process plans remain available on the shop floor. It consists of two main modules, introduced in detail in this paper. They are process plan selection module and scheduling module.
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paper_title: Integration of process planning and scheduling functions

paper_content:

Automated process planning (APP) has received a considerable amount of attention in recent years. This has mainly been due to APP allowing for the bridging of the gap between design and manufacturing, and for its automation of the related tedious human task. While there have been several efforts in developing interfaces between computer-aided design (CAD) and APP, little attention has been given to the integration of APP and scheduling, which is likely to be of even higher importance. This paper addresses the basic issues involved in the integration of the two functions, demonstrates a methodology and the potential benefits of the integrated approach by an example, and presents directions for future research.
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paper_title: Integrating Process Planning and Scheduling with an Intelligent Facilitator

paper_content:

This paper introduces a dynamic facilitating mechan is m for the integration of process planning and scheduling in a batch-manufacturi ng environment. This integration is essential for the optimum use of production resources and generation of realistic process plans that can be readily executed with little or no modification. In this paper, integration is modeled in two le vels, viz., process planning and scheduling, which are linked by an intelligent facilitator. The process planning module employs an optimization approach in whi ch the entire plan solution space is first generated and a search algorithm is t hen used to find the optimal plan. Based on the result of scheduling module an u nsatisfactory performance parameter is fed back to the facilitator, which then i dentifies a particular job and issues a change to its process plan solution spac e to obtain a satisfactory schedule.
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paper_title: Integration of process planning and scheduling by exploring the flexibility of process planning

paper_content:

A unique method for the integration of process planning and scheduling in a batch-manufacturing environment is reported. This integration is essential for the optimum use of production resources and for the generation of realistic process plans that can be readily executed with little modification. The integration problem is modelled at two levels: process planning and scheduling, which are linked by an intelligent facilitator. The process-planning module employs an optimization approach in which the whole plan solution space in terms of available machines, tools, tool accessibility and precedence constraints is first generated and a search algorithm is then used to find the optimal plan. For a given set of jobs, the scheduling module takes the optimal plans for each job and generates a schedule based on a given criterion, as well as the performance parameters (machine utilization and number of tardy jobs). An unsatisfied performance parameter is fed back to the facilitator, which then identifies a partic...
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paper_title: Dynamic process planning — The static phase

paper_content:

Abstract Dynamic process planning is concerned with the integration of process planning with scheduling. This paper presents the computer-aided process planning (CAPP) system, PARIS, that is meant to be integrated with a scheduling system. The approach to dynamic process planning implemented divides the planning tasks into the two phases: static and dynamic planning. This paper discusses the overall approach and focusing on the details of the implementation of the static phase. An example is used to illustrate the concepts presented.
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paper_title: Process control and dynamic process planning

paper_content:

Real time machine tool control and the planning activities which precede manufacture are usually interfaced through a low level language which allows little more than position, feed, and speed information to be passed between the two systems. The higher level systems used to describe geometry and tool paths also lack an adequate capability to describe manufacturing processes. The authors discuss the provision of a much richer interface between the planning and control activities which both facilitates the identification and scheduling of suitable monitoring tasks and allows the updating of process plan data from real time measurements. The result of such integration is an improvement in the efficiency of real time optimisation, and perhaps most importantly the possibility of quasi real time process planning. A system that is able to perform both initial process planning and plan refinement based upon low level feedback must also encompass the path generation activity, such a system is referred to by the authors as a dynamic process planning system. The paper describes the fundamentals of the process models, identification algorithms, control strategies, and low level process plan generation used within such an integrated system.
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paper_title: Integration of scheduling with computer aided process planning

paper_content:

Abstract Computer aided process planning (CAPP) and scheduling are two major activities in a modern manufacturing system. The existing CAPP systems have not taken account of shop floor conditions while developing process plans. This paper discusses the importance of integration of scheduling and CAPP and proposes a method for the same. There can be several methods to machine a part and several machines capable of performing the process required to complete the part. Based on this concept, this paper suggests a method of scheduling and its integration with CAPP, so that on-line process plan can be generated taking into account the availability of machines and alternative routes. A scheduling factor for an operation and machine combination has been defined taking into consideration the actual working conditions and capabilities of the machines. Finally operation–machine assignment is made on the basis of these actual scheduling factors. This helps in generating more realistic process plans and helps in improving the efficiency of the manufacturing system as a whole.
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paper_title: An architecture for the vertical integration of tooling considerations from design to process planning

paper_content:

Abstract To meet the competitive demands of modern manufacturing, it is necessary to reduce design times and enrich decision making by integrating process planning into the design activity using Concurrent Engineering principles. Although this is traditionally done through the interaction between designers and process planners, it is perhaps more desirable for a CAD system to have the functionality necessary to automatically advise the designer of the shop floor implications of design decisions. Cutting tool selection is an essential thread linking feature-based design of machined parts to process planning. Thus, the implementation of tooling considerations into design is an important requirement for an integrated CAD/CAPP system. This paper defines an architecture to enable the vertical integration of tooling considerations from early design to process planning and scheduling. The architecture is based on a five-level tool selection procedure which is mapped to a time-phased aggregate, management and detailed process planning framework. This paper draws on literature and the results of an industrial survey to identify the tooling methods suitable for integration within a CAD system and categorises them into the five levels of tool selection. The functions are then placed on a time-dependent framework that covers the progression of a product from design to process planning. The new functionality is being implemented as an object-oriented application called VITool, which is being developed so that it can be fully integrated within an existing CAD system.
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paper_title: A hierarchical bicriterion approach to integrated process plan selection and job shop scheduling

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Abstract The job shop scheduling literature deals with problems characterized by a fixed linear process plan for each job: it is assumed that the process planning problem has been solved before scheduling, and no flexibility in the process plan is considered. Our aim here is to propose a solution approach for a joint process plan selection and job shop scheduling problem, taking both operations cost and makespan into account within a multi-objective framework. Due to the complexity of the problem, a two-phase hierarchical method is proposed. In the first phase, a relaxed version of the problem is solved, yielding an approximation of the set of efficient process plans with respect to cost and load balancing objectives. Each process plan is then considered and the corresponding scheduling problem is solved by tabu search; the process plan selection is improved by a two-level hierarchical tabu search algorithm.
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paper_title: DPP : An Agent-Based Approach for Distributed Process Planning

paper_content:

A changing shop floor environment characterized by larger variety of products in smaller batch sizes requires creating an intelligent and dynamic process planning system that is responsive and adaptive to the rapid adjustment of production capacity and functionality. In response to the requirement, this research proposes a new methodology of distributed process planning (DPP). The primary focus of this paper is on the architecture of the new process planning approach, using multi-agent negotiation and cooperation. The secondary focus is on the other supporting technologies such as machining feature-based planning and function block-based control. Different from traditional methods, the proposed approach uses two-level decision-making—supervisory planning and operation planning. The former focuses on product data analysis, machine selection, and machining sequence planning, while the latter considers the detailed working steps of the machining operations inside of each process plan and is accomplished by intelligent NC controllers. By the nature of decentralization, the DPP shows promise of improving system performance within the continually changing shop floor environment.
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paper_title: A Blackboard Architecture for Integrating Process Planning and Production Scheduling

paper_content:

As companies attempt to increase customization levels in their product offerings, move toward smaller lot production, and experi ment with more flexible customer/supplier arrangements such as those made possible by electronic data interchange (EDI), they increas ingly require the ability to (1) respond quickly, accurately, and competitively to customer requests for bids on new or modified products and (2) efficiently work out supplier/subcontractor arrangements for these products This in turn requires the ability to (1) rapidly convert standard-based product specifications into process plans and (2) quickly integrate process plans for new orders into the existing production schedule to best accommodate the current state of the manufacturing enterprise
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paper_title: Development of a function block designer for collaborative process planning

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The research objective is to develop methodologies and framework for collaborative process planning and scheduling, supported by a real-time monitoring system in distributed environments. A function block enabled collaborative process planning approach is proposed to handle various dynamic changes during process plan generation and execution. This paper focuses on collaborative process planning, particularly on the development of a function block designer As function blocks can sense environmental changes, it is expected that a so generated process plan can adapt itself to the changes with dynamically optimized solutions for plan execution and process monitoring.
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paper_title: A collaborative process planning and scheduling system

paper_content:

Traditionally, process planning and scheduling have been rather separate activities within a company. Nowadays, the need for more flexible production and shorter production lead times urges for a close collaboration between these activities as a first step towards simultaneous engineering. This article describes the results of the ESPRIT project COMPLAN, which aims at the implementation of an integrated automatic process planning and scheduling system based on the concept of non-linear process plans. In addition to the use of NLPP for flexible load balancing and reactive rescheduling, a new collaborative approach is presented that is based on production constraints as a means to realize a feedback from scheduling to process planning. A process-planning kernel is described that integrates this concept of production constraints.
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paper_title: Concurrent process planning and scheduling in distributed virtual manufacturing

paper_content:

With the fast development of the world economy, distributed virtual manufacturing is becoming increasingly important since it can respond rapidly to market changes and make resource sharing more efficient among manufacturing partners. In this environment, partners may be located at different geographical locations, and co-operation among partners is a vital task and thus concurrent planning and scheduling has become a challenging research topic. This paper presents a computerized model that can integrate these manufacturing functions and resolve some of the critical problems in distributed virtual manufacturing, such as virtual co-operation, optimal partner selection, etc. This integration model is realized through a multi-agent approach that provides a practical approach for software integration in a distributed environment. A cost function is proposed and adopted for optimal partner selection in a virtual enterprise, which not only considers a partner's manufacturing capability and process requirements, but also the processing time, partner's location and product due date. Through establishing a virtual manufacturing model in a simulated environment, the proposal was validated with a case study. It shows that the proposed methodology can satisfy the distribution and agility requirements. This approach is able to contribute to the reduction of product cost, improving product quality and shortening lead time, compared to the sequential approach in the normal engineering and production practice.
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paper_title: Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

paper_content:

Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified
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paper_title: Dynamic shopfloor scheduling in multi-agent manufacturing systems

paper_content:

Abstract This paper is on the development of an agent-based approach for the dynamic integration of the process planning and scheduling functions. In consideration of the alternative processes and alternative machines for the production of each part, the actual selection of the schedule and allocation of manufacturing resources is achieved through negotiation among the part and machine agents which represent the parts and manufacturing resources, respectively. The agents are to negotiate on a fictitious cost with the adoption of a currency function. Two MAS architectures are evaluated in this paper. One is a simple MAS architecture comprises part agents and machine agents only; the other one involves the addition of a supervisor agent to establish a hybrid-based MAS architecture. A hybrid contract net protocol is developed in the paper to support both types of MAS architectures. This new negotiation protocol enables multi-task many-to-many negotiations, it also incorporates global control into the decentralized negotiation. Simulation runs are conducted to compare the performance of the proposed MAS-based IPPS approaches and that of an evolutionary algorithm. It also shows that the hybrid-based MAS, with the introduction of supervisory control, is able to provide integrated process plan and job shop scheduling solutions with a better global performance.
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paper_title: Agent technology for collaborative process planning: a review

paper_content:

Agent technology has been considered as a promising approach for developing process planning systems and optimizing process plans in a distributed environment. A number of researchers have attempted to use agent technology in process planning for the purpose of integrating systems, tools and algorithms which are geographically distributed. In this paper, the historical background of agent technology is systematically reviewed. A comprehensive review of agent technology and its applications in manufacturing is presented including the applications of agent in scheduling, control, and enterprise integration and supply chain management. The focus of the paper is on how agent technology can be further developed in the support of collaborative process planning as well as its future research issues and directions in process planning. The current research directions in computer aided process planning (CAPP) and issues in traditional CAPP approaches are also discussed. Three agent-based approaches for process planning are presented. Finally, the key issues in developing agent-based collaborative process planning systems are summarized.
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paper_title: Modelling of integrated, distributed and cooperative process planning system using an agent-based approach

paper_content:

This paper describes a conceptual framework for applying a multi-agent system to process planning for integrating design, process planning and shop floor scheduling so that a distributed, cooperative and integrated process planning system is constructed. The problem in process planning has been mapped onto a multi-agent architecture based on multistage cooperation. The multi-agent system has some common characteristics, such as distribution, autonomy, interaction and openness, which are helpful for the traditional architecture to be transferred to the distributed, cooperative architecture for process planning system. An agent-based framework for an integrated, distributed and cooperative process planning system (IDCPPS) integrates all the activities of process planning into a distributed intelligent open environment. Agents in the agent-based framework for the IDCPPS can be organized dynamically and cooperate with each other to perform an appointed task flexibly. In addition, using CORBA technology, a prototype system of the IDCPPS is implemented.
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paper_title: DPP : An Agent-Based Approach for Distributed Process Planning

paper_content:

A changing shop floor environment characterized by larger variety of products in smaller batch sizes requires creating an intelligent and dynamic process planning system that is responsive and adaptive to the rapid adjustment of production capacity and functionality. In response to the requirement, this research proposes a new methodology of distributed process planning (DPP). The primary focus of this paper is on the architecture of the new process planning approach, using multi-agent negotiation and cooperation. The secondary focus is on the other supporting technologies such as machining feature-based planning and function block-based control. Different from traditional methods, the proposed approach uses two-level decision-making—supervisory planning and operation planning. The former focuses on product data analysis, machine selection, and machining sequence planning, while the latter considers the detailed working steps of the machining operations inside of each process plan and is accomplished by intelligent NC controllers. By the nature of decentralization, the DPP shows promise of improving system performance within the continually changing shop floor environment.
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paper_title: An introduction to agent technology

paper_content:

Intelligent agent technology is a rapidly developing area of research. However, in reality, there is a truly heterogeneous body of work being carried out under the 'agent' banner. In this paper, software agent technology is introduced by briefly overviewing the various agent types currently under investigation by researchers.
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paper_title: An overview of distributed process planning and its integration with scheduling

paper_content:

Process planning and scheduling are considered as two separate and distinct phases in manufacturing. Traditional approaches to these problems do not consider the constraints of both domains simultaneously and can only result in sub-optimal solutions. This separation becomes a barrier to further improving manufacturing performance. Most process planning and scheduling systems are off-line and centralized. The process plans generated off-line may become invalid at the time of plan execution. On the other hand, scheduling based on rigid process plans may have already lost the optimal options. Today, there is an increasing need for the integration of process planning and scheduling to generate more realistic and practical solutions. This paper provides a literature review on the integration of process planning and scheduling, particularly on agent-based approaches. It is followed by an overview of our approach toward distributed process planning and scheduling. The paper is finally concluded with future research opportunities.
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paper_title: Integrated process planning and scheduling/rescheduling—an agent-based approach

paper_content:

This paper presents a hybrid-based multi-agent system (MAS) for integrating process planning with scheduling/rescheduling in job shops or similar kinds of flexible manufacturing environments. The approach is called Online Hybrid Agent-based Negotiation (oHAN). It employs the affected operations rescheduling approach to reschedule the operations affected directly or indirectly by the disruptions. The proposed MAS architecture comprises local agents, which are the part and machine agents, and a supervisor agent. The local agents detect the production disturbances and reschedule the affected operations via decentralized negotiations. A comprehensive set of process plan flexibilities including flexible routings and alternative machines is considered during rescheduling. The supervisor agent coordinates and monitors the rescheduling process in order to ensure the observance of a global rescheduling objective. An online hybrid contract-net negotiation protocol (oHCNP) has been established to control the interac...
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paper_title: Concurrent process planning and scheduling in distributed virtual manufacturing

paper_content:

With the fast development of the world economy, distributed virtual manufacturing is becoming increasingly important since it can respond rapidly to market changes and make resource sharing more efficient among manufacturing partners. In this environment, partners may be located at different geographical locations, and co-operation among partners is a vital task and thus concurrent planning and scheduling has become a challenging research topic. This paper presents a computerized model that can integrate these manufacturing functions and resolve some of the critical problems in distributed virtual manufacturing, such as virtual co-operation, optimal partner selection, etc. This integration model is realized through a multi-agent approach that provides a practical approach for software integration in a distributed environment. A cost function is proposed and adopted for optimal partner selection in a virtual enterprise, which not only considers a partner's manufacturing capability and process requirements, but also the processing time, partner's location and product due date. Through establishing a virtual manufacturing model in a simulated environment, the proposal was validated with a case study. It shows that the proposed methodology can satisfy the distribution and agility requirements. This approach is able to contribute to the reduction of product cost, improving product quality and shortening lead time, compared to the sequential approach in the normal engineering and production practice.
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paper_title: Bidding-based multi-agent system for integrated process planning and scheduling: a data-mining and hybrid tabu-SA algorithm-oriented approach

paper_content:

This paper conceptualizes a bidding-based multi-agent system for solving integrated process-planning and scheduling problem. The proposed architecture consists of various autonomous agents capable of communicating (bidding) with each other and making decisions based on their knowledge. Moreover, in contrast to the traditional model of integrated process-planning and scheduling problem, a new paradigm has been conceptualized by considering tool cost as a dynamic quantity rather than a constant. Tool cost is assumed to comprise tool-using cost and its repairing cost. The repairing cost is considered to depend on the tool-breaking probability, which is predicted by the data-mining agent equipped with the virtues of C-fuzzy decision tree. When a job arrives at the shop floor, the component agent announces a bid for one feature at a time to all the machine agents. Among the machine agents capable of producing the first feature, one comes forward to become a “leader”, and groups other machine agents for the processing of remaining features of the job. Once all features are assigned to the appropriate machines, the leader then sends this allocation information to the optimization agent. The optimization agent finds optimal/near-optimal process plans and schedules via the hybrid tabu-SA algorithm.
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paper_title: Bidding-based process planning and scheduling in a multi-agent system

paper_content:

Abstract Effective and efficient implementation of intelligent and/or agile manufacturing systems requires an enterprise level integration. The first step in this direction is to integrate design, process planning and and scheduling. This paper describes a bidding-based approach to the integration of computer-aided design, process planning and real time scheduling. The product is represented in a STEP model with detailed design and administrative information including design specifications, batch size, and due dates. Upon arrival at the manufacturing facility, the product is registered in the shop floor manager which is essentially a coordinating agent. The shop floor manager broadcasts the product's requirements to the machines. The shop contains autonomous machines that have knowledge about their functionality, capabilities, tooling and schedules. Each machine has its own process planner and responds to the product's request in a way that is consistent with its capabilities and capacities. When more than one machine offers certain process(es) for the same requirements, they enter into negotiation. Based on processing time, due date and cost, one of the machines wins the contract. The successful machine updates its schedule and advises the product to request raw material for processing. The concept was implemented using a multi-agent system in an object-oriented programming language. The task decomposition and planning are achieved through contract nets. Examples are included to illustrate the approach.
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paper_title: Multiagent-based process planning and scheduling in context of supply chains

paper_content:

Intelligent software agents are a promising approach to improve information logistics in manufacturing enterprises. This paper deals with the application of agents in the area of process planning and production control. Thus, enterprises will be able to fulfil the requirement of flexible, reliable and fault-tolerant manufacturing. Fulfilment of these requirements is a prerequisite for successful participation in modern business alliances like supply chains and virtual enterprises. Thus, agent-based improvements of information logistics enable enterprises to face the challenges of competition successfully. Current research activities focus on the development of agent-based systems for integrated process planning and production control. They led to the IntaPS approach, which is presented in this paper. Furthermore, the integration of different agent-based systems in context of collaborative manufacturing in supply chains will be discussed.
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paper_title: A Petri net model for integrated process and job shop production planning

paper_content:

In this paper a new Petri net class (Chameleon systems) for modeling and analyzing joined process planning and job shop production planning is proposed based on the multi-level Petri net model introduced by Valk (1995). Chameleon system is a High-level Petri net extended with time that consists of a High-level Petri net modeling the workshop which is called system net and ordinary Petri net modeling the jobs and setups which act as tokens of the system net and therefore are called token nets. Process plans of the jobs are partial orders of operation groups and alternatives. The uncertainty of operation duration is captured by a new time model. The advantages of this new modeling approach are the following: (i) a modular construction of the joined process and job shop planning is allowed, (ii) classical known Petri net analysis methods can be applied and (iii) the analysis can be done at different levels of abstraction.
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paper_title: Integrated process planning and scheduling with minimizing total tardiness in multi-plants supply chain

paper_content:

In this paper, we propose an integrated process planning and scheduling (IPPS) model for the multi-plant supply chain (MSC), which behaves like a single company through strong coordination and cooperation toward mutual goals. The IPPS problem is one of the most important issues for supporting the global objectives, because the function takes part in the assignment of factory resources to production tasks. The problem is formulated as a mathematical model considering alternative machines and sequences, sequence-dependent setup, and distinct due dates. The objective of the model is to decide the schedules for minimizing total tardiness through analysis of the alternative machine selection and the operation sequences in MSC. In order to obtain good approximate solutions, genetic algorithm-based heuristic approach is developed. Numerical experiments are carried out to demonstrate the efficiency of the proposed approach.
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paper_title: A simulated annealing approach to integrated production scheduling

paper_content:

This paper describes an approach to manufacturing planning that seeks to integrate both process planning and scheduling. We show that separating these two related tasks, as is the common practice, can impose constraints that substantially reduce the quality of the final schedule. These constraints arise from premature decisions regarding operation sequence and allocation of manufacturing resources. Having formulated an integrated process planning and scheduling problem, we describe a solution technique based on simulated annealing. We compare this approach with others reported in the literature, considering both their generality and performance. In particular, we perform a detailed empirical comparison between simulated annealing and the popular technique of dispatching rules. Our results, achieved with two distinct sets of example problems, show that simulated annealing can produce solutions of significantly higher quality than those achieved through a published dispatching rule approach.
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paper_title: An adaptive genetic algorithm with dominated genes for distributed scheduling problems

paper_content:

This paper proposes an adaptive genetic algorithm for distributed scheduling problems in multi-factory and multi-product environment. Distributed production strategy enables factories to be more focused on their core product types, to achieve better quality, to reduce production cost, and to reduce management risk. However, when comparing with single-factory production, scheduling problems involved in multi-factory one are more complicated, since different jobs distributed to different factories will have different production scheduling, consequently affect the performance of the supply chain. Distributed scheduling problems deal with the assignment of jobs to suitable factories and determine their production scheduling accordingly. In this paper, a new crossover mechanism named dominated gene crossover will be introduced to enhance the performance of genetic search, and eliminate the problem of determining optimal crossover rate. A number of experiments have been carried out. For the comparison purpose, five multi-factory models have been solved by different well known optimization approaches. The results indicate that significant improvement could be obtained by the proposed algorithm.
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paper_title: An Emergent Synthesis Approach to Simultaneous Process Planning and Scheduling

paper_content:

Optimality of a process plan and a production schedule frequently conflict. It is difficult to determine a proper plan that meets both objectives simultaneously. This paper proposes a new simultaneous process planning and scheduling method to solve dilemmas posed by such situations using evolutionary artificial neural networks based on emergent synthesis. The effectiveness of the proposed method is confirmed by solving a benchmark problem, thereby demonstrating high productivity resulting from role-sharing among machines. Results also show that the proposed method is applicable to more realistic problems including larger volumes of products and production demand fluctuations.
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paper_title: A web-based integrated process planning and scheduling system

paper_content:

This paper reports a unique approach to integrate the process planning and scheduling functions. The proposed approach here is used to reduce the tardy jobs by exploring the process plan solution space of the selected jobs. The integrated system comprises a process planning module, a scheduling module and an integrator module. The integration is achieved in an iterative manner. The uniqueness of this approach is characterized by the flexibility of the process planning strategy, which makes full use of the plan solution space intuitively to achieve a satisfactory schedule. Two heuristic rules for modifying solution space are proposed and the simulation on the Web-based collaborative system shows that the proposed approach can achieve satisfactory schedule performance levels in a fair number of iterations.
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paper_title: Integration of process planning and scheduling -- A modified genetic algorithm-based approach

paper_content:

Traditionally, process planning and scheduling for parts were carried out in a sequential way, where scheduling was done after process plans had been generated. Considering the fact that the two functions are usually complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved greatly. In this paper, a new integration model and a modified genetic algorithm-based approach have been developed to facilitate the integration and optimization of the two functions. In the model, process planning and scheduling functions are carried out simultaneously. In order to improve the optimized performance of the modified genetic algorithm-based approach, more efficient genetic representations and operator schemes have been developed. Experimental studies have been conducted and the comparisons have been made between this approach and others to indicate the superiority and adaptability of this method. The experimental results show that the proposed approach is a promising and very effective method for the integration of process planning and scheduling.
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paper_title: A genetic algorithm for integration of process planning and scheduling in a job shop

paper_content:

This study focused on the integration problem of process planning and scheduling in a job shop environment. In an effort to integrate process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we have designed a GA (Genetic Algorithm)-based scheduling method. The performance of this newly suggested GA-based method has been evaluated by comparing integrated scheduling with separated scheduling in a real company that has alternative process plans. Also, a couple of benchmark cases have been tested for performance evaluation.
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paper_title: An Improved Particle Swarm Optimization(PSO) Algorithm and Fuzzy Inference Systems Based Approach to Process Planning and Production Scheduling Integration in Holonic Manufacturing System (HMS)

paper_content:

New paradigms for manufacturing system control are required that provide manufacturers with the adaptability and responsiveness required to compete in today's market. In this paper, an integrated process planning and scheduling system, which is applicable to the holonic manufacturing system is presented. Basic architecture of the target holonic manufacturing system is discussed from the viewpoint of the process planning and the scheduling systems. Process planning are proposed to select suitable machining sequences of machining features and suitable sequences of machining equipment, taking into consideration of future schedules of machining equipment. A fuzzy inference system (FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop in HMS is presented. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, an improved particle swarm optimization (PSO) have been used to balance the load for all the machines. Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling
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paper_title: Manufacturing responsiveness through integrated process planning and scheduling

paper_content:

This paper describes a novel approach to improve manufacturing responsiveness, defined as the ability of a manufacturing system to make a rapid and balanced response to the predictable and unpredictable changes characterizing today's manufacturing environments. The approach aims at creating a dynamic environment that is capable of reacting to factory conditions and which has a significant impact on the reduction of cost, lead time and inventory. The concurrent engineering concept of information sharing to support all the product development phases is employed here. Techniques such as design for manufacture have been applied to the design-process planning interface. Efforts have been made towards eliminating the divisions between process and scheduling activities using the concept of resource elements, which are the exclusive and shared capability boundaries between processing elements in the manufacturing facility. A prototype integration system has been implemented consisting of a knowledge base with fac...
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paper_title: An introduction of dominant genes in genetic algorithm for FMS

paper_content:

This paper proposes a new idea, namely genetic algorithms with dominant genes (GADG) in order to deal with FMS scheduling problems with alternative production routing. In the traditional genetic algorithm (GA) approach, crossover and mutation rates should be pre-defined. However, different rates applied in different problems will directly influence the performance of genetic search. Determination of optimal rates in every run is time-consuming and not practical in reality due to the infinite number of possible combinations. In addition, this crossover rate governs the number of genes to be selected to undergo crossover, and this selection process is totally arbitrary. The selected genes may not represent the potential critical structure of the chromosome. To tackle this problem, GADG is proposed. This approach does not require a defined crossover rate, and the proposed similarity operator eliminates the determination of the mutation rate. This idea helps reduce the computational time remarkably and improv...
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paper_title: Scheduling with alternatives: a link between process planning and scheduling

paper_content:

The objective of this research is to develop and evaluate effective, computationally efficient procedures for scheduling jobs in a large-scale manufacturing system involving, for example, over 1000 jobs and over 100 machines. The main performance measure is maximum lateness; and a useful lower bound on maximum lateness is derived from a relaxed scheduling problem in which preemption of jobs is based on the latest finish time of each job at each machine. To construct a production schedule that minimizes maximum lateness, an iterative simulation-based scheduling algorithm operates as follows: (a) job queuing times observed at each machine in the previous simulation iteration are used to compute a refined estimate of the effective due date (slack) for each job at each machine; and (b) in the current simulation iteration, jobs are dispatched at each machine in order of increasing slack. Iterations of the scheduling algorithm terminate when the lower bound on maximum lateness is achieved or the iteration limit is reached. This scheduling algorithm is implemented in Virtual Factory, a Windows-based software package. The performance of Virtual Factory is demonstrated in a suite of randomly generated test problems as well as in a large furniture manufacturing facility. To further reduce maximum lateness, a second scheduling algorithm also incorporates a tabu search procedure that identifies process plans with alternative operations and routings for jobs. This enhancement yields improved schedules that minimize manufacturing costs while satisfying job due dates. An extensive experimental performance evaluation indicates that in a broad range of industrial settings, the second scheduling algorithm can rapidly identify optimal or nearly optimal schedules.
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paper_title: Optimizing the Performance of an Integrated Process Planning and Scheduling Problem: An AIS-FLC based Approach

paper_content:

The present market scenario demands an integration of process planning and scheduling to stay competitive with others. In the present work, an integrated process planning and scheduling model encapsulating the salient features of outsourcing strategy has been proposed. The paper emphasizes on the role of outsourcing strategy in optimizing the performance of enterprises in rapidly changing environment. In the present work authors have proposed an Artificial Immune System based AIS-FLC algorithm embedded with the fuzzy logic controller to solve the complex problem prevailing under such scenario, while simultaneously optimizing the performance. The authors have shown the efficacy of the proposed algorithm by comparing the results with other random search methods.
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paper_title: A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling

paper_content:

This paper addresses the integrated problem of process planning and scheduling in job shop flexible manufacturing systems. Due to production flexibility, it is possible to generate many feasible process plans for each job. The two functions of process planning and scheduling are tightly interwoven with each other. The optimality of scheduling depends on the result of process planning. The integration of process planning and scheduling is therefore important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. For the performance improvement of the algorithm, it is important to enhance population diversity and search efficiency. We adopt the strategies of localized interactions, steady-state reproduction, and random symbiotic partner selection. Efficient genetic representations and operator schemes are also considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and an existing cooperative coevolutionary algorithm. The experimental results show that the proposed algorithm outperforms the compared algorithms.
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paper_title: Integration of process planning and production scheduling with particle swarm optimization (PSO) algorithm and fuzzy inference systems

paper_content:

Integration of process planning with scheduling by considering the manufacturing system's capacity, cost and capacity in its workshop is a critical issue. The concurrency between them can also eliminate the redundant process and optimize the entire production cycle, but most integrated process planning and scheduling methods only consider the time aspects of the alternative machines when constructing schedules. In this paper, a fuzzy inference system (FIS) in choosing ::: alternative machines for integrated process planning and scheduling of a job shop manufacturing system is presented. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The mean time to failure (MTF) values is input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be ::: chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the particle swarm optimization (PSO) have been used to balance the load for all the machines. Simulation study shows that the system can be used as an alternative way of choosing machines in integrated process planning and scheduling.
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paper_title: Flexible job-shop scheduling with routing flexibility and separable setup times using ant colony optimisation method

paper_content:

This paper proposes an ant colony optimisation-based software system for solving FMS scheduling in a job-shop environment with routing flexibility, sequence-dependent setup and transportation time. In particular, the optimisation problem for a real environment, including parallel machines and operation lag times, has been approached by means of an effective pheromone trail coding and tailored ant colony operators for improving solution quality. The method used to tune the system parameters is also described. The algorithm has been tested by using standard benchmarks and problems, properly designed for a typical FMS layout. The effectiveness of the proposed system has been verified in comparison with alternative approaches.
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paper_title: A Genetic Algorithm for Integration of Process Planning and Scheduling Problem

paper_content:

Traditionally, process planning and scheduling for parts are carried out in a sequential way, where scheduling is done after process plans have been generated. Considering the two functions are usually complementary, there is a great potential to integrate them more tightly so that greater performance and higher productivity of a manufacturing system can be achieved. In this paper, a genetic algorithm-based approach has been developed to facilitate the integration and optimization of these two functions. To improve the optimized performance of the genetic algorithm-based approach, efficient genetic representations and operator schemes have been developed. Experiment studies have been conducted. The experimental results show that the proposed approach is a promising and very effective method for the integration of process planning and scheduling.
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paper_title: Evolutionary algorithm for advanced process planning and scheduling in a multi-plant

paper_content:

Integration of process planning and scheduling is one of the most important functions to support flexible planning in a multi-plant. The planning and scheduling are actually interrelated and should be solved simultaneously. In this paper, we propose an advanced process planning and scheduling model for the multi-plant. The objective of the model is to decide the schedules for minimizing makespan and operation sequences with machine selections considering precedence constraints, flexible sequences, and alternative machines. The problem is formulated as a mathematical model, and an evolutionary algorithm is developed to solve the model. Numerous experiments are carried out to demonstrate the efficiency of the proposed approach.
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paper_title: Genetic algorithms for job shop scheduling problems with alternative routings

paper_content:

The purpose of this research is to solve a general job shop problem with alternative machine routings. We consider four performance measures: mean flow time, makespan, maximum lateness, and total absolute deviation from the due dates. We first develop mixed-integer linear programming (MILP) formulations for the problems. The MILP formulations can be used either to compute optimal solutions for small-sized problems or to test the performance of existing heuristic algorithms. In addition, we have developed a genetic algorithm that can be used to generate relatively good solutions quickly. Further, computational experiments have been performed to compare the solution of the MILP formulations with that of existing algorithms.
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paper_title: Integration of process planning and job shop scheduling using genetic algorithm

paper_content:

This study focused on the integration problem of process planning and scheduling in a job shop environment. In an effort to integrate process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we have designed a GA (Genetic Algorithm)-based scheduling method. The performance of this newly suggested GA-based method has been evaluated by comparing integrated scheduling with separated scheduling in a real company that has alternative process plans. Also, a couple of benchmark cases have been tested for performance evaluation, thus proving that the integrated scheduling shown by this research can be effectively applied to the real case.
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paper_title: The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling model

paper_content:

Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhance...
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paper_title: A simulated annealing-based optimization approach for integrated process planning and scheduling

paper_content:

A job shop needs to deal with a lot of make-to-order business, in which the orders are usually diverse in types but each one is small in volume. To increase the flexibility and responsiveness of the job shop in the more competitive market, process planning and scheduling modules have been actively developed and deployed. The functions of the two modules are usually complementary. It is ideal to integrate them more tightly to achieve the global optimization of product development and manufacturing. In this paper, a unified representation model and a simulated annealing-based approach have been developed to facilitate the integration and optimization process. In the approach, three strategies, including processing flexibility, operation sequencing flexibility and scheduling flexibility, have been used for exploring the search space to support the optimization process effectively. Performance criteria, such as makespan, the balanced level of machine utilization, job tardiness and manufacturing cost, have been systematically defined to make the algorithm adaptive to meet various practical requirements. Case studies under various working conditions and the comparisons of this approach with two modern evolutionary approaches are given. The merits and characteristics of the approach are thereby highlighted.
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paper_title: Agent technology for collaborative process planning: a review

paper_content:

Agent technology has been considered as a promising approach for developing process planning systems and optimizing process plans in a distributed environment. A number of researchers have attempted to use agent technology in process planning for the purpose of integrating systems, tools and algorithms which are geographically distributed. In this paper, the historical background of agent technology is systematically reviewed. A comprehensive review of agent technology and its applications in manufacturing is presented including the applications of agent in scheduling, control, and enterprise integration and supply chain management. The focus of the paper is on how agent technology can be further developed in the support of collaborative process planning as well as its future research issues and directions in process planning. The current research directions in computer aided process planning (CAPP) and issues in traditional CAPP approaches are also discussed. Three agent-based approaches for process planning are presented. Finally, the key issues in developing agent-based collaborative process planning systems are summarized.
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Title: A Review on Integrated Process Planning and Scheduling

Section 1: Introduction
Description 1: An overview of process planning and scheduling, highlighting the relationship between them and the significance of their integration.

Section 2: Background of study
Description 2: Detailed information on process planning and production scheduling, and the problems in traditional manufacturing systems without IPPS.

Section 3: Brief review of process planning
Description 3: Summary of process planning, including types of Computer-Aided Process Planning (CAPP) systems and their implementation approaches.

Section 4: Brief review of scheduling
Description 4: Overview of scheduling, covering its types, challenges, and various optimization algorithms and approximation methods.

Section 5: Statement of problems
Description 5: Discussion of issues arising from traditional, sequential process planning and scheduling, and the need for IPPS.

Section 6: Review on Integrated Process Planning and Scheduling
Description 6: Definition of IPPS and a review of research in this area.

Section 7: IPPS in support of distributed and collaborative manufacturing
Description 7: Examination of how IPPS supports distributed and collaborative manufacturing environments.

Section 8: Integration models of IPPS
Description 8: Different models proposed for IPPS integration, including Non-linear Process Planning (NLPP), Closed-Loop Process Planning (CLPP), and Distributed Process Planning (DPP).

Section 9: Non-linear Process Planning
Description 9: Description of NLPP, its methodology, and various research works supporting the model.

Section 10: Closed-Loop Process Planning
Description 10: Explanation of CLPP and its dynamic feedback mechanism, along with related research.

Section 11: Distributed Process Planning
Description 11: Outline of DPP, its phases, and research supporting this approach.

Section 12: Comparison of integration models
Description 12: Comparative analysis of NLPP, CLPP, and DPP, highlighting their advantages and disadvantages.

Section 13: Implementation approaches of IPPS
Description 13: Overview of various AI-based approaches developed to implement IPPS, including agent-based, petri-net-based, and algorithm-based methods.

Section 14: Agent-based approaches of IPPS
Description 14: Review of agent-based approaches for IPPS, highlighting relevant research and future trends.

Section 15: Petri-net-based approaches of IPPS
Description 15: Discussion of using Petri-net models for IPPS integration.

Section 16: Algorithm-based approaches of IPPS
Description 16: Description of algorithm-based approaches, focusing on evolutionary algorithms and other meta-heuristic methods.

Section 17: Critique of current implementation approaches
Description 17: Critical assessment of agent-based, petri-net-based, and algorithm-based approaches for IPPS.

Section 18: Future research trends and conclusions
Description 18: Identification of future research trends in IPPS and concluding remarks on the significance of continued research and development in this area.