It is thus possible to use the concepts and techniques of fuzzy set theory and manage imprecision in an quantitative way, since most conventional procedures do not treat imprecision and implicitly assume a fixed structure, when, in fact, decisionmaking needs flexible and robust models to deal with real life situations.For example, imprecision and uncertainty in industry are included in information about flux times, labour, materials performance, lead times, and so on. This data, which is easy to define and include in a model having absolute measurements, is always imprecise, partly due to the uncompleted information and the uncertainty that could exist with internal and external factors.
En la industria, por ejemplo, la imprecisión y la incertidumbre están presentes en la información referida a los tiempos de flujo, la mano de obra, el rendimiento de los materiales, los tiempos de suministro, y así sucesivamente; estos datos, fáciles de definir e involucrar en un modelo como medidas absolutas, son siempre imprecisos debido en parte a información incompleta y a la incertidumbre que pueden generar factores internos y externos.