Welcome to session 12 of our course on Quality Control and Improvement using Minitab. I am Professor Indrajit Mukherjee from Shailesh J Mehta School of Management, Diety Bombay. So, we are discussing in last session about attribute control chart. So, two charts we have discussed like C chart and U chart which is used for monitoring the defects and C is used when constant sample size are used to monitor defects and U is used when sample size varies at different time points like that. So, we will move on with other attribute control chart. So, beyond this what is there is that we have a P types of P type of control chart over here. P is basically P chart and NP chart we will discuss both the charts over here. So, a P is proportion defective which is monitored, earlier case was defect this is defective over here and defective means 0 1 condition either it is useful or it cannot be used like that. So, in this case either useful or scrap we can think of. So, in this case one of the example that is showing over here is a number of defective cans when every time I am inspecting 50 samples subgroup size we can think of. So, number of samples at a given time point what we have at time point E 1. So, these are the 12 cans which was found defective and 50 cans were inspected basically. So, over here formulation is also this assumption was taken as binomial distribution assumption and based on that formulation is given over here. What you can see is that UCL will be P average P average will be calculated based on individual proportions over here. So, proportions can be calculated for a specific values over here. So, if I take this value P 1 it will be 12 by 50 basically. So, then I can calculate what is the value proportion over here P 2 similarly P n like that. So, P i is given over here which will be a number of defective items divided by sample size that we have taken as respect to 1. So, P i and then we can get we will get 30 P i's and then average of this 30 P i's will give me P bar or average defectives of the process like that. So, that will be the central line over here and then we can calculate UCL P bar 3 multiplied by and this will be constant in case we are taking constant sample size and it will be different if I am taking a different sample size at every time point like that. So, we can vary the sample size also if you have varied sample size also we can plot that one. So, this is for scenarios where we are we are interested in plotting the defectives like that. So, somebody may be number of rejections in number of rejections of may be engine assembly in that case how many engines are rejected like that. I produce this many engines in a shift and how many produced are defective like that. So, that scenarios also can be monitored which is abnormal which is normal which is abnormal like that. So, this is one example and we have some other example also on this. So, this is also another example where 20 samples of size 100. So, every time I take 100 samples and this is taken from the book Amitav Amitav both the case we will solve and try to see how P charts can we can use P charts for interpretation of the data. So, what we will do is that we will take some examples over here. So, I will open P charts and then I will illustrate how this can be done in Minitab. So, this is the two examples that we are talking about non-confirming CANS first one and then the sample fraction defective what you see is that 12 by 50 was done and this is 0.24. Like this we divided by 50 I get proportion defectives and that can be monitored like that. So, what we can do is that we can calculate this one. So, we can use calculators over here to calculate this one. So, if we want to calculate this one. So, this store results in if I say C3 over here what I can do is that I will write down that C2 divided by 50 let us say. So, that is the expression I want to use over here and if you click that one automatically this values will be replaced and you will get all this observation that you see over here. So, these are the observations that is saved over here. So, this is same numbers what I can see over here. So, this is 12, 12, 15 like that. So, sample size or subgroup size was 50. So, that division was done. So, Minitab you do not need to divide this one. So, what you do is that stat you go to I know this is for defectives and I go to control charts attribute control chart I go to P chart directly. What I do is that which is the variable number of non-confirming cans over here. What is the subgroup size? I mentioned 50 over here and P chart option again the same thing I test I want to test anything beyond 3 sigma limits like that which is abnormal scenarios I click ok. What will happen is that you will get the P chart corresponding P chart. So, in this case what happens is that two points are going outside what you can see and these are the abnormal scenarios. So, proportion defectives goes outside. So, proportion defective what you see is that upper limit line is 0.41, average is 0.23 and lower control is 0.05. So, two points gone outside. So, we have to find out figure out what has gone wrong at this time point when proportion non-confirming are very high in these two points like that ok. Now, the problem with this is that in this case. So, this is proportion defectives and if this proportion defectives changes and when the sample size changes in that case also we can we can figure out what can. So, this is a P chart over here if the sample size changes in that case only what will happen is that I will have a variable UCL and variable LCL like that ok. So, that is one aspect. So, what happens is that in production flow what generally happens is that proportion defectives people understand defectives one defect one defective two defectives like that when you say in fraction they do not understand because engine fraction defective does not make any sense. So, what they does is that they multiply is the N with P. So, they call it as N P charts like that that makes an impression that number of defectives then we can we can immediately understand over here ok. So, in this case what you see is fraction in the central limit UCL and LCL like that. So, operator may not understand what is fraction that you are saying average defective is 0.04, but I understand that it should be more than 1 like that. So, it should be more than 0 or on the higher side or on the positive side we want to we do not understand means how this average is 0.04 like that proportion I do not understand make it much simpler like that. So, in that case what they does is that they will multiply it with N nothing else they are doing over here. So, in this case what they will do is that they will have a different limit lines. So, in this case N P charts are recommended over here. So, this N is multiplied over here with P and this is N multiplied by P formula somewhat changed. So, this will be the central line and this will be the lower control limit line. So, in this case what you will observe is that the numbers are in whole number with some fractions like that. So, now 2011 this is understood. So, this is 2. So, this is understood by the operator lower control is 2 defectives like that. So, we expect out of 50 this 2 is the lower control limit line. So, we should be above this one and the upper is around 20 or something like that. So, that is what is the upper limit. So, number of defectives out of 50 inspection should not go beyond 20 like that, that is the feeling of the operator like that. So, that becomes easier to monitor for the operator like that. So, we have a chart which is not as N P chart which is just a variance of P chart. So, what we can do is that we can we can we can same charts like that. So, we can we can also see N P charts and where we can. So, number of cans like this over here same examples we are taking. So, stat I go to stat control chart attribute chart I click on N P charts like that. So, I do not want to see proportion and their upper limit lower limit like that. I want to see number of non confirming one and I will say subgroup size is 50 because and other conditions remain same and then what I do is that I click ok. And then I get the control limit lines this is the N P chart which is which is done by Minitab and here you see the numbers are 20. So, this is easily understood by the operator that 20 defectives if it is going beyond that then I should be very very much cautious like that out of 50 more than 20 is defective then that means something unnatural is happening if the average is average should be around 11. So, out of 50 my process is like that. So, on an average I am getting 11 types of 11 number of defective items like that and the lower limit is around 2. So, and here we can see two abnormal scenarios which is coming up like that. So, it becomes easier for the operator to understand this type of representation of the data otherwise P and N P are both used for defective. So, any of the one you can use like that ok. So, only one thing is that there can be variable sample numbers like that. So, it can it can also vary. So, maybe some example this is variable subgroup size what you see C 9 and C 10. So, defective number of defective sample size changes and in that case also if you if you plot this one. So, control chart and attribute chart N P charts like that and I mentioned that I want to see defectives and instead of 50 I say that this is in column C 10 and I want to see what happens like that. So, then what you get is that this type of control chart you will get. So, this is N P charts where N is varying. So, number every time I am inspecting is changing. So, in this case limit lines are also changing like that. So, central line is changing because it is multiplied by N. So, N is changing. So, central line is changing upper limit is also changing and lower line what you see is that this is taken as 0. So, minute I was considering this as 0 because every calculation is negative coming out to be. So, whenever you see attribute charts and this is coming out to be negative what happens is that I freeze that point to 0 because negative defects or defectives does not make any sense in this case. So, that is why you do not see uniform uniformity in central line and the upper control limit line and lower control limit line. So, that will always happen. So, when we are talking about defects and defectives it cannot be less than 0. So, that is the constraint that we have. So, and underlying distribution I told that this is binomial based on which this control chart is developed. So, this is a prominent chart which is used nowadays in any quality control aspect. So, these are the main control charts. So, when we talk about control chart generally we try to understand X bar R, X bar S, individual moving range and C chart, P chart, NP charts like that. So, these are the common types of control chart that is used to monitor any CTQs like that. CTQs if it is in continuous variable. So, that can be otherwise if it is attribute like the defects and defectives like that we can use this type. But it is always preferable to go to a CTQ which can be measured in continuous scale like that I have mentioned earlier also. So, with this information over here we will move on to a different topic which is also an important topic in quality because we are assessing the quality before we go into improvements. So, we are trying to control and we are trying to see that what are the measures that that will help us to go towards improvement like that. So, one of the measures that is used is known as process capability. So, earlier what we are talking about is the natural variability based on which I am giving upper UCL control limit line and LCL control limit line. So, but when we are talking about process capability we are talking with respect to customer specification basically. So, our natural behavior with respect to tolerance where we stand basically ok. So, what you see is the natural variation over here, what you see is the natural variation over here. So, this is the region of my natural variation of the process and then I compare it to the upper specification which is known as upper specification limit and this is known as lower specification limit which is the LCL over here. So, on an average my process average is around 25 let us say, but my specification given is between 20 and 30 like that. So, with respect to my tolerance how I am how I am basically performing. So, that comparison when I am doing that is known as process capability analysis or we will use some indices for this. So, that will be known as process capability index ok. Some index we will use to express this one process capability. So, that is known as process capability index So, it is basically how where is my process as compared to the specification width that is given by the designer ok. So, voice of the customer is what you see is that lower specification to upper specification. So, this is the voice of the customer we can say and if I consider this one the plus or minus 3 standard deviation this is voice of the process basically. So, I am just comparing voice of the process with voice of the customer ok. So, that will give me process capability measures like that ok. So, before I go into process capability we should have stability in the process. So, that is the primary condition. So, before we calculate the process capability my process should be stable. So, that is the basic criteria which is used ok. So, in this case how this calculation is done. So, every time process is moving. So, in this case with respect to time what you see over here. So, in control scenarios is taken to calculate the process capability and in that case this is upper specification, this is lower specification and how the process is behaving. So, where we stand with respect to my variation with respect to specification that is what is seen in process capability analysis like that ok. Based on which I will decide whether I need to improve and how much improvement is needed like that ok. So, this is graphical representation with respect to normal distribution what you see is that this is a just capable process. So, this is the tolerance that is given by the designer which is voice of the customer like that and we are performing exactly we are matching with the specification over here. My voice of the process is about using the same width like that because and if you are using that one I am just capable basically. So, I am just fitting into the specification like that my variation is there and if you see you on this side. So, my mean as if I am assuming mean equals to target over here. So, I am I am exactly on the target as far as accuracy is concerned, but precision voice I am using the total tolerance like that whatever whatever is given by the designer ok. Here what you can see is that variation is high, but I have shifted to the lower specification side this is also I have moved away from the target values. So, this is undesirable. So, we have variation we are also moving away from the target values like that. Similarly, what you see over here is that I am moving away to the other targets I am moving over towards the upper specification. So, I am moving to the one end of the customer given specification like that. So, which is known as upper specification limit and this is known as lower specification limit which is which designer this is defined from the upper control limit and lower control limit. So, lower control limits are defined by the process variability and process centering process process mean and this is defined this is defined by the designer over USL and NSL like that ok. So, and if we are producing if my variation is very high. So, in that case what you can expect is that there will be certain fallouts over here because if you remember normal distribution in that case some fallouts will happen over here and this is rejection basically. So, this is reject whenever some products are falling within this. So, normal distribution if you can think of a normal distribution graph you know that does not touch the axis over here there will be certain rejection. But in this case because we are centered and this scenario is much better this scenario is much better because the tail is much thinner as compared to this one. So, whenever it touches so there is some probability high probability over here which is greater than this one what you see over here. So, this scenario is what scenario this is also a what scenario. So, this is just capable and this will not be capability will be much less also as compared to this this will also be less capability over here ok. So, most suitable scenario is that I am hitting the target and my variability is also less like that. So, I have less variability like that. So, that is the scenario we were looking for over here ok. So, there are different index to measure the capabilities and we will talk about two index over here. So, what do you see if you want to visualize this one? So, if we divide this we call it as process capability index. So, process capability visualization is that if this is the scenario I am using the full tolerance and if this is the scenario I am using much less tolerance as compared to what is given by the designer like that ok. So, index CP is expressed as tolerance divided by so we can say that what is voice of the customer and this is the voice of the process which is known as 6 standard deviation and as standard deviation may be estimated over here. So, this is the expression for this so one is tolerance divided by so how much of the so this is the voice of the voice of the customer and this is the voice of the process. So, voice of the process means how much of the tolerance I am basically using my process is basically using that ratio is known as CP. So, earlier examples what you see is that total my voice of the process is this much and my variability plus or minus 3 standard deviation I am using the full tolerance I am using basically. So, in this case the ratio will be same. So, our ratio will be this voice of the customer will be exactly equals to voice of the process. So, this will be equals to 1 what what you see in the earlier diagram like that and in this case second scenario what you see is that my tolerance is just maybe double of the voice of the what we are using over here. So, in this case a voice of the process basically. So, voice of the process is just half of voice of the customer. So, this will be we can represent this as if I represent this one as 1 this will be half. So, CP index will come out to be equals to 2 what you see is shown over here. So, favorable scenario is that I am using less as compared to what is given by the designer and I want to reduce it further like that. So, it is like you are moving car in a tunnel like that and if I am if I am just fitting into that is not the best scenario if I can go into the tunnel with ease. So, that is the open that is the that is the best scenario what we can think about. More and more I reduce the variability more and more favorable situation assuming the target remains same like that. So, this CP index what it shows is that it shows how much of the variability my variability is with compared to the tolerance that is given by the designer or given by the customer like that. So, if you have one-sided scenarios. So, in this case you can calculate a CPU and CPL like that. So, MINIDAP does it automatically for you. So, just capable process we can think of CP is equals to 1 industry standard I am talking about. This may be scenario some of the industries follows that you should be CP should be exactly equals to 1.33 or more than that is acceptable scenario or somebody can say it should be greater than equals to 1.67 that is the most favorable scenarios over here. And if it is excellent means if it is more than 2 it is always excellent. So, process capability if it is 2 if it is greater than equals to 2. So, in that case that is the most favorable scenarios and excellent performance we can say for the process like that ok. So, this can be calculated and this will be done automatically like what do you see over here like philosophy of Six Sigma which we will discuss afterwards maybe in some of the sessions where it says that higher the capability better is the process condition like that and less variation. So, less rejection basically. So, if you see with respect to specification in that case lesser is the width of this. So, thinner is the proportion which is going outside over here or the probability of falling outside the specification like that that is the philosophy of Six Sigma. So, I hit the target and it reduces the variability like that generally CP equals to 2 indicates that is a Six Sigma process, but there are other conditions which needs to be satisfied for that ok. So, how do we calculate process capabilities that we need to see in Minitab. So, in this case for a given set of data I want to calculate the process capability like that and what is the option that we have. So, in this case we will take some example maybe and we will see how this capability index can be calculated. So, let us take some data set what is provided in this. So, this is one bursting strength of 100 containers like that. So, at a given time point it was taken some observation was taken container 1 to 5, 5 subgroups were taken over here and this is observation that we have and for this data set some specification is given customer specification lower specification limit is given over here and we want to calculate or we can take this piston ring which is both sided specification over here. So, this becomes easier to understand. So, this is 74 plus 0.035 like that and 74 minus 0.035 that will be the specification for this product over here. So, and we will place this into Minitab and try to figure out what is the CP index, what is the value of CP index. So, this is the data that was collected at a given time point. So, piston ring 74 and this is the data set that we have every time we have 5 subgroups. So, we will calculate the process capability index over here. So, if you go to the data set, so we will close this one and we will open capability analysis process capability analysis Minitab file which is already stored with me and this is the piston ring examples that we are taking over here and this example we are taking first. So, in this case, we have both sided specification what you have seen. So, plus or minus 74 plus or minus 0.035, this is taken from Montgomery's book example. So, we will try to illustrate that one. So, what you do is that stat quality tools and capability analysis over here. So, assuming normality over here, there are various options over here. I will take the simplest one assuming normality over here, normality can be checked. So, we are not doing that at present. So, are they in single column? No, they are in subgroups are in different one. So, this is ring 1 to ring 5, we will highlight this one and enter over here. Now, specification, lower specification we will enter like that. So, this is given us. So, let me just check this one. So, 73.965, 73.965 that I will put as lower specification 73.965 that is the specification mentioned by the designer. And the upper specification will be equals to 74.035. So, that will be 74.035, 74.03. So, now options over here. So, this transformation you ignore at present estimation over here. So, this is we can ignore at present. We will only see the CP index what is the value of that. So, this analysis is not required at present. So, these things we can ignore at present whatever value comes. So, I want to see only the CP values. So, from here we can see. So, if you click ok, what will happen is that it will do some analysis and it will come up with some diagram over here. At present we do not want to see all of that. So, what do you see is that just note that LSL is taken as 73.965, USL is taken as 74.035. I have not given the target over here. I have only given the width band that is given by the customer and then I will only see the CP index that you see over here. So, this CP value is 1.16 and that is the formula that we are using over here CP formulation will be this one. So, which I am using over here. So, this is the formulation which uses USL minus LSL that is the tolerance or delta values over here. So, that is plus or minus 0.034 that is the total width of that 2 times of that and divide by 6 into standard deviation over here. So, there is a method of calculation of standard deviation. So, that we have to discuss afterwards. So, at present we will assume that Minitab has calculated some standard deviation. So, this is taken and the output given over here is CP is 1.16. So, some way they have calculated the standard deviation which we will discuss in the next session how Minitab is calculating this one. And I also told that we do capability analysis whenever the process is stable like that. So, we will check that whether the process is stable and then if the process is stable how do I calculate the standard deviation which will be used in process capability analysis to calculate CP index that means delta divided by when I am doing the specification total tolerance that is given and divided by 6 process voice of the process. So, voice of the process this sigma is calculated based on certain assumptions like that that is process is under statistical control and then we can calculate sigma and there are ways to calculate sigma which is calculated from X bar R charts like that. So, R is used as a measure R bar is used as a measure and number of subgroups here it is 5. So, that ratio is used R bar by D2 is used to calculate the process standard deviation. So, that multiplied by 6 gives you the denominator and numerator is the tolerance that we are having like that. So, based on that we will discuss we will start discussing about how they calculate this CP indices like that. So, sigma calculation we will see and that sigma calculation is given over here what you see standard deviation within what you see over here and this is basically calculated based on control chart concept and R bar by D2 is the formulation that is used to calculate standard deviation within and many other calculations we will see. So, ignore all other information just see USL and LSL that is given and the difference between them will give you the voice of the process voice of the customer and 6 multiplied by the standard deviation within what is the way we will calculate next time and that will give you the voice of the process. So, ratio of this gives me 1.16 and we can say just capable it has not reached 1.33 which was the standard in many of the companies, but it has just crossed 1 we can think of. So, there is a need for improvement of this process we need to reach around 2 CP values like that. So, that is our objective we want to reduce the variability and more and more I reduce the variability more and more my CP index increases like that. So, that will be our point of discussion. So, we will see first how the sigma is calculated and based on the concept that whether they are under statistical control that we will also cross check with these examples like that and then we will see other measures which is used to check capabilities like that. So, we will stop over here and we will continue discussion of this capability analysis. So, these two example we will use to illustrate our many of the measures that we will see that MINITAB provides and what is the meaning of each of these outputs that you see that you see in MINITAB like that. Thank you for listening. This session we will continue in the next session from here. Thank you for listening.


Hi, my name is Brenda and I'll be talking about how to set yourself up for success. One important step in setting yourself up for success is picking the right company specifically for you. I'm currently a senior product manager at Slack, but I've been a product manager of a few other companies before. Over the past nine years, I've worked at six different companies. I started my career at General Mills, then went to Glassdoor as an analyst, then Dropbox as a product manager, and I've been a product manager since at Lumosity, Alto, and Slack. So why am I talking about this topic? I would love to help others have a better time than I did. Being at many different companies, I've gotten many data points. Through the different industries, company sizes, stages, products, I've gotten through a lot of experiences such as layoffs, roadmap thrash, and organizational chaos. I think many of my unpleasant experiences could have been either preventable or better mitigated if I were aware or prepared. I also think conditions now are tougher than ever. There are more and more frequent large-scale layoffs, difficult economic conditions, a competitive job market, ultimately coming to even harder conditions for newer New York P.M.s. So the goal of today's talk is to help find a match fit specifically for you. I'll go through how to evaluate a company's level of volatility through their business strategy and organizational structure, as well as helping you understand your tolerance for volatility. I won't be talking about other dimensions that are important, such as culture, values, mission, compensation. I think those are widely discussed and have many other great resources. The things that I talk about will be general guidelines, not rules, to help you understand your own trade-offs. There are many more ways to understand volatility. This will cover some of the biggest signal so that you can make quicker decisions. So why volatility? Volatility is a trade-off cost to evaluating match fit. It's a critical factor that leads to burnout, stress, or could slow down learnings and career progressions if unprepared or unaware. You can see different things that volatility indicates, such as changing roadmaps, attrition, and under-delivered promises. However, you can gauge volatility by following the money and the leaders. When looking at business strategy, short-term strategies lead to more volatility. The less money a company has on hand, the more likelihood there will be company volatility. From product leadership and their organizational structure, the less maturity of a leadership organization, the more volatility. The lower index the company has towards product-led strategy, the more product level volatility there will be. Now I'll go deeper into these dimensions. So a key indicator of short-term strategies is poor cash flow or low-free cash flow. They're nuanced, but I'll be using them interchangeably to essentially mean the money a company, the amount of money that a company has on hand. This is an indicator of a company's agility and ability to react to big changes and think of it kind of like your personal emergency fund. The less money a company has on hand means the less room they have to react to a market downturn or lower earnings. Surprise costs, such as regulatory changes or supply chain disruptions. This is typical to companies who have a growth at all cost strategy. Another key indicator is large funding rounds at a high valuation. This becomes an indicator of a company's obligation and timeline to deliver on those obligations. Bigger obligations mean the company's focus, not necessarily only on the customers or the product, but is more on what the investors want. With the expectations are not met, there could be more severe consequences, as well as fewer options for where the company can go after this valuation. So when a company has poor cash flow, you'll see what we're seeing now with the market downturn. Companies who don't have cash on hand are more likely to have layoffs or more likely to have larger layoffs. Companies who have good cash flow are ones like Apple, Microsoft, Duolingo, who typically are good signals or things like recurring revenue or a long-term profitability strategy. Companies with poor free cash flow are ones with very high operating cost, high expenditures, acquisitions, and low margins. Some companies that had poor cash flow or Uber before this year, Meta recently has lowered their free cash flow by 90% and other companies like Peloton. So when a company has large fundraising rounds at high valuation, the company tends to expand insides and quickly needs to drive growth. This means the strategy and organization can become inefficient where leadership wants to do many things at once and everyone is thrown into many different priorities, potentially conflicting priorities as well. Large funding does not necessarily mean long runway. Not all the money is directly going to the business or supplying cash on hand. There are companies where this goes into other costs like acquisitions such as Hoppin where they had a large round at a very large valuation. If a company does not deliver quickly, there could be quick loss cutting-edge response or eventually a downturn like Clarnasaw. Investors are not necessarily investing because of a long-term payout. So large investment does not necessarily mean long-term stability. Investors have different goals and employees and they could be looking for a short-term return. So another point of volatility is on the organizational level. A product org's maturity will have a big impact on the volatility on your day-to-day as a product manager. How long has the product team been around? A product org that is just new to the organization maybe one years old compared to the organization's four years will have a long learning curve in learning how to work with product. How much experience leading does the product leadership team have? The skills that make a great IC do not necessarily mean the greatest skills for people managing or senior leadership. Having a lot of experience in that does mean more stability for product managers. How much industry experience leading at a high level through the strategy, keeping the business stable does take more experience and even better our experiences within the industry. Does the product leadership team have value or strategic thinking that aligns with yours? This is about match fit. Does the leadership team style specifically for product match your style as a product leader? Another component is who makes strategic decisions. So leadership teams and different functions all work together to make strategic decisions, but companies do index more heavily towards a certain function. It's intuitively better for product managers that it is a product-led organization. However, there are other organizations such as Airbnb that are more heavy on the design side but also have great collaboration with product management. So how well do other functions work with product that will impact your day-to-day volatility? And then on the executive team side, team level changes are frequent.  However, those things do change frequently. Executive leadership, however, should be lower frequency and change. So understanding your own tolerance for volatility helps make a better match fit decisions. Sometimes the trade-off could be worth it. There are many opportunities that provide learning growth and great experiences. So having the right match fit is not just understanding the trade-off and being willing to make that kind of trade-off, but also intentionally planning for it, understanding what it comes with, and maybe positioning yourself better. So your tolerance for volatility might be higher if you have genuine and natural interests in the challenges that come with any job. There's industry excitement, product excitement, strategy and customer problems that could be very interesting for you and that makes the volatility either more bearable or you're able to cut through the noise. Specific clarity to what you want out of the job ties into this interest. What do you need out of this stage in your career? What kind of learnings, what kind of guidance, what kind of team collaboration? More clear on what you need, the more you can understand if the trade-offs conflict with that or they're a natural byproduct of any imperfect job. And finally, you hear many people say that the best part of their job, big part of their satisfaction with their role are the people that they work with. And similarly, your own tolerance for volatility will probably be higher if you have a strong support system with you in the job. And you might be wondering how to find more information to make your decisions. Researching information about your company's business model, major financial decisions, strategic direction, industry trends can be found online. Reading all the articles or information, not just the positive press, will help give a more full picture of what's going on. Look for specific details in these articles like major financial decisions, numbers, strategic decisions. And there are many resources out there like Glassdoor, Blind, TechCrunch, Huckabees. Some people also can tactfully reach out to employees who've recently left their company or reach out to current employees to ask questions and understand what's going on. In interviews, you could also ask to interview with the skip level to pick their brain on more strategy and organizational context. And most importantly, feel free to ask in general, whether it's to the recruiter or other interview panels, fill in the gaps in your understanding by asking directly things you would like to know to make a better decision. Thank you for listening to my talk. Good luck to all of the people job hunting out there. And feel free to connect with me on LinkedIn.


Come to the bad MGM studio and the Mike Vrable show presented by seat geek with the head coach I'm Mike Keith. Hope everyone had a fantastic Christmas. Hope you had a little time with family a little bit Okay, you didn't work too much yesterday. I mean, I thought we came in and it was able to get prepared for today And then you know practice tomorrow. So, you know, I think that there's a good balance All right. We got a little balance and the Titans needed to restock the practice squad after having to call So many guys up last week. So today the Titans signed five players to the practice squad two guys really jump out to me Devon I saw I saw I saw you see I see I see I see Devon I see I see I'll have it my Sunday I promise tight end out of UCLA and Then take router linebacker from Georgia a couple players that we knew a lot about in the 2020 draft Four of the five guys you actually signed are veteran players. Is there a feeling you may need them? Well, I think so, you know at this point in time. You just want to make sure that guys You know, this isn't a developmental process now. This is you know, who are we gonna need? To fill out the game day roster whether that be in offense defense and especially special teams So, you know, we'll see where these guys go and they progress worked out well and I've already started meeting with the coaches and We'll see how they work their way through the week. I see I see I see I see I see I see There we go, how about Mike variable six pack so I can get myself out of trouble already six of the best plays from Sunday's game Let's see a little defense. Let's see a little pass rush. Let's see a little ardent key. Well, good get off You know, that's a good job on the back side, you know, it's four by one You know the quarterback looked over to the weak side on the slant had that covered Came back and again, this is an example of us, you know Complimenting each other working together letting the back end, you know help the pass rush if the quarterback does that he pumps and Comes back where we have to be able to get there and make a play and he did fumble But unfortunately for the Titans, he fell right on it. Yeah, you know We just had to continue to Tomahawk the ball continue to attack the ball and hopefully we'll get it out Let's see another defensive play Aziz al Shire with an outstanding effort to help keep These guys these Seahawks out of field goal range at the end of the first half Yeah, and third and long and this does it, you know, Aziz does a nice job of getting off a little bit But then, you know, again the quarterback has nowhere to go with the ball You know progresses over and then Aziz is able to really get a tackle for loss and you know an excellent play That they ended up forcing them to punt Zach Charbonneau taking out a bounce for minus four there. All right one more defensive play This one came from early in the third quarter and it forces The Seahawks into a field goal try good effort by Terrell in it really was and you can see, you know We I don't know if we're gonna get another look at it, but they're in a bunch and they work their way through a bunch We you know communicate they tried they were they were expecting one coverage here He dips in like what's gonna be cover for and then goes vertical and and Terrell stays square And really you could argue that this is OPI, you know DK runs into him basically we're square and Terrell does a great job of being square Challenging not backing up and then going up there and stabbing through the pocket You know a really nice play there on third down battled him all the way to the ground too Which you have to do with that big yet you better and that was a heck of a job All right, let's look at a good offensive play here one that Mike variable had to challenge and went on Super catch and a good throw as the Titans complete it from Tana Hill to Berks Yeah, I didn't have a very good look at it. Obviously just had to rely on you know upstairs and trailing keeps running and You know the officials come in and again all you have to do is say incomplete or catch and then you know One of us has to go about their business of challenging and so we waited they said incomplete We got another look and decided to challenge so good job by the guys upstairs and communicating Trailing does an impressive job to get the feet down at first look It didn't look like he did and then when you saw the replay he clearly did those are some tight ones on the sideline They happen fast and so you know you just You have to see what they call and then decide if you're going to challenge it or try to go on the football Those are our bang bang place Let's see a Derek Henry touchdown run that put the Titans in front in the fourth quarter Nice effort from two yards out by everybody involved. Yeah, it was it was a good job on the backside You know and Derek goes back here cuts back on the backside and andray Dillard and and and John OJ And trailer, you know are involved here and you can see where the back side ends up being really the point of attack You know we're able to wash everybody in there to the right and and Derek's able to pretty much go in there Close to untouched. So let's see another good executions another quarterback sack here from Harold Landry coming in the fourth quarter Landry now has nine and a half on the year. Yeah, and again the quarterback has to go and look somewhere else and again Harold's trying to get the ball out. These are the ones that we have to come in here on first glance here and try to come down With the right hand Tomahawk as he's bringing him to the ground. He goes with the rake but we have to start, you know Trying to get the ball from the quarterback. That's the easiest target and you know These are good opportunities and as he's going down you can see where Harold's trying to get the rake So big play in the game and just you know need some more of them All right, let's take a look at one bonus play from the goal line Marlon Davidson number 92 Does the job here and he's playing good football for you right now. Well, he's getting an opportunity and He's taking advantage of it Working extremely hard, you know, we're lined up, you know ready to go We got two off the edge So the quarterback can't really read it and pull it because there's Harold and so when a block down Marlon does exactly what he was coached to do Which was tackle a dive and good things happen and next time it'll be a fumble So he comes through with two tackles in the ballgame that tackle for loss marlon davidson also three quarterback pressures So effective snaps overall for the titans Okay, when we come back We've got to see the half back pass and the only way for us to see it is through The Vrabel straighter it's over there. I want to take a I'm dying to know how this worked so well That's next when the mike Vrabel show presented by seat geek continues from the bet mgm studio. Stay with us The mike Vrabel show in the bet mgm studio presented by seat geek time now for the Vrabel straighter here we are and the half back pass Derek handery who's now eight of 10 for 40 yards and five touchdowns passing in his career Counting what's that rating? He's got a rating on that. It's pretty hot. It's pretty darn high. It's pretty high 158.3. No, it's not 150. It's not it's not it's not quite that high because his yards per attempt Hurt him, but He does throw it well Yes, and I think titans fans love to see the king throw the ball And the setup on this play was fascinating. Well, you know he starts here with you know trying to be better in the red zone And certainly when when derrick's running the football some of these plays Can start to to work off each other and build off each other So, you know three tight ends one of them being an excel alignment So john uh ojikoya comes in and reports is eligible You know, you got hot back sides So if they start to cheat the post safety, you know a way those are options over there one on one But just really a base run here for us This is going to be a gap scheme power and you're going to see everybody Blocking back blocking down protecting the gap inside Uh peter pulling around ryan in the in a pistol with derrick widen the pistol just to give us a little bit more time Okay, you know felt like you know to show us some different things Derrick's going to take the handoff and chig, you know is going to come in and briefly sell this And and try to get you know this guy to bite up It's the guy back here who who really You know, I think just was being patient But I didn't think that he was going to stand there flatfooted You could see the puller and derrick gets this guy to bite gets the corner to bite And then now we're just able to run away From the post safety Obviously there and and the biggest thing is you want to make a platform for derrick You want to give him an opportunity to sell the run? Like we've done here, but also build a Somewhat of a pocket and make him protected to still have to throw the football You know to a guy that's a moving target and you know, we tried it earlier with uh indianapolis And and we were just a couple inches, you know too far here now I thought just a great job of chig of running away from this thing Derrick giving them a good ball and like you said, that's the longest half second in the game right there When we when we look up, you know doing the game on the radio We look up and you see the guy is all alone and you're like, oh, please catch it Look at that. That's a thing. It is a thing of beauty but I love that the pistol part was I wanted to ask you about why don't you run it out of the pistol and A jukku with a block here man. He takes his guy that that guy gets after it He did he played about 16 plays for us and and helped us in a run game You know and we'll get better. You know, that's his first action That's his first game action as a as a Tennessee titan Whether that's pre-season or regular season excited for guys like that John a jukku number 61 when we come back Epic western spotlight with a pretty good story about a guy on the titans coaching staff who Didn't get right into coaching after his playing career ended. That's next on the mike verbel show presented by seat geek Welcome back to the bike verbel show presented by seat geek in tonight's epic western spotlight We share a story of a titan's offensive coach who was working in a different field roughly 20 years ago He was actually in charge of an nfl stadium It was a super job and he was successful But charles london's heart told him that he wanted to be on the field on the sidelines to be exact So he gave up this great job and started at the bottom of the coaching ranks The move has totally paid off Charles london is wrapping up his first season as the titan's quarterback coach and passing game coordinator He came to tennessee from the atlanta falcons where he was an important part of arthur smith staff london chose a move to the titans for a multitude of reasons Including familiarity. This is kind of my second stent heroes here in uh, 2011 as well So very fond memories, but uh, you know the chance to work for coach rable and to work with tim kelly again And a lot of guys on the offensive staff and defense staff who i was familiar with had worked with Whether i was at penn state or at houston with the texans So tim and i were together for uh, you know two years at penn state and four years together at houston and obviously we've remained In touch since then but uh, I understand what he's trying to do understand how he thinks to understand how charles london thinks You have to understand how he came into coaching when he finished playing football at duke He didn't think becoming a football coach was in the cards He thought instead about going into the secret service or the cia But he loved sports so he accepted an internship under future nfl announcer charles davis At disney's wide world of sports in orlando and then i got into stadium and event management. So i was uh 1999 and went to cleveland brown stadium to help them open their new stadium as the assistant manager And then eventually got hired by the new england patriots as their director of Stadium operations for gillette stadium and then one day you say I want to coach. Yeah, I was probably 29 30 years old I mean, did you did you think to yourself at that point? Look, this is what I want to do, but I can't give this up You know, I did there were some it was some tough decisions to make but I told myself look I don't want to regret this for the rest of my life I think I want to coach and if i'm going to pull the trigger I got to do it now So um I left my job in new england went back to duke where I played and started as a graduate assistant Attack it attack it attack it attack it attack it Charles london went from duke to a quality control job with the bears He scouted for the philadelphia eagles. We mentioned that he spent 2011 on the offensive staff with the titans Then it was on to happy valley Another great experience for london his time on the staff at penn state when I went to penn state I was a recruiting coordinator and running backstote So the evaluation of talent really carried over to recruiting coordinator aspect of for the last 10 seasons He's been back in the nfl with the houston texas with the chicago bears with the atlanta falcons and now Back with the tennessee titans real life experiences chasing his passion 20 plus years learning every aspect of the game being willing to do any job That's why charles london is the perfect coach to develop will levis And why he enjoys working with head coach mike fray You know, I I he's demanding, but he's fair and I and I think that's all you could ask for I think he's got a great relationship with the players Um, obviously he's been a player so he can relate to him in that way And I think the players really appreciate that but he's direct and he's honest and he's fair And that's all you can ever ask for for a coach and I think he's a great motivator And I haven't been with him for a season in a while since we were together in houston But the way he prepares the team is very Wanted to give you a chance to meet charles london who took a big chance. I mean that's a pretty good job You've got running gelette stadium and then you say one day That's not my passion and to start over It wasn't like it was come to duke to be the receivers coach or the offensive coordinator. It was to come to be a ga and uh You know that that's just following what you what you love and what you believe about yourself You try to have a lot of people like that around you People who love the game and have that sort of passion well and that shows and I and I really was excited about being able to add charles this off season and You know it worked out and giving him the opportunity to work here with the quarterbacks is something that he wanted uh an opportunity at and I have an interview them for the offensive coordinator Realized that uh, I would want him a part of our staff and that worked out Epic western spotlight enjoyed bringing that to you when we come back Kids ask coach verable That's next on the mike verable show From the bedmgm studio presented by seat Glad to have you with us on this tuesday night for the mike verable show presented by seat geek We're in the bedmgm studio and it's time time now For the best part of the show Kids ask coach verable. Hi coach verable. My name is seven and i'm seven years old And I was going to ask you.  I would say that there is a wide range of emotion Uh throughout the week and through in preparation um That the game takes a lot of different flows and So I would imagine much like the fans You know that we're we're go through the same types of emotions and You know try to be a play ahead and and thinking about what the situation may be and making corrections and How much do you spend on corrections as opposed to going over there? uh looking ahead Or assisting in corrections. I mean the all three sides are making corrections when they're not out there um, but there is a wide range of emotion from excitement to disappointment and and if we win or lose Uh if a player is injured right that all these things that go on throughout the game Uh mistakes positive plays negative plays, but You know you have to I think the biggest thing is try to keep your composure and get back to to center After each and every play in every situation people say to me mike verable enjoys what he does I would say that I love what I do And not even enjoy I I love this and it's a challenge Uh certainly this year But uh, we're we're going to we're going to see through this thing and there's a lot of good stuff out there right now That's hard to see because it's all about wins and losses But there's there's still some some really good things going on in there Mike verable's Nissan keys are up next on the mike verable show presented by seat geek stay with us titans taking on the houston texans for the second time in two weeks at n rg stadium this sunday kickoff set for 1202 Last week the keys the nissan keys to success were a lot more about Intensity and performance of the titans and a lot less about specific things Are we going to see the same sort of things this year? Yeah, I mean we are I mean there's obviously things that we could talk about with cj stroud and eco collins and Noah brown or the run game or making sure that we take care of these down linemen is penetrating front Finding ways to run the football protect the quarterback You know being able to continue to try to move the ball down the field averse You know quarters or their Three-week coverage But this is going to be about us and about our ability to continue to invest in this football team and making sure that the people here And the players here continue to invest And their teammates in this football team. Let's blow through these nissan keys to success Up first it's pretty obvious. You've got to be Ready to go ready to play and play fast and aggressive Well, I think that's the only way you have to have confidence in what you're doing to go out there and and not you know Just there's got to be a certain play speed. This is a fast team This is a fast defense that we're going to play We're going to have to challenge that with some speed and aggressiveness All right second key for mic for ables keys to success Energy and passion for the team which you certainly had on sunday.  I would say that I think he has a chance. All right. Good to know remember It's titans at houston this sunday 12 o 2 the kickoff We're on the air on 1045 and the great titans radio stations throughout the region at 11 a.m With titans countdown looking forward to having you there with us for that and looking forward to another afc south showdown The final game of 2023 for mike verbel i'm mike key. Thanks for joining us for the mike verbel show presented by seat


the paper proposes a comprehensive review and classification of previous design and creativity for with through additive manufacturing AM approaches which are then integrated into a modular framework called design by additive manufacturing DB AM methodology to promote AM in the design process a validation of the method is proposed on an industrial case study from the aeronautics and defense sector to exploit AM potentials and develop AM conformal designs this article was authored by Frederick Seggins


Welcome, this is Melissa Armel with the stock swishing them here reviewing UA. This looks great It's gonna break the low and a couple of pennies here, but a very very very long trade And let me tell you why we didn't get this out of the gate. Nobody saw the gap. Nobody saw it early I didn't see it didn't come up anywhere and that was really quite frankly a bummer and even though we took this in the morning it was profitable at one point in the morning but then it really wasn't enough or what I thought and I thought this would keep going and it is continuing to go, but this is one of these trades It just took pretty much all day Okay, so if we had done this out of the gate, which we didn't it would have been a quick trade We would have been up and out But we didn't see it That's unfortunate in fact shower singer brought this up in the room I don't remember the time that he brought it up. Anyways long story short We did it like it was right around this period here And then I said, you know what it looks good to even add and then we did more and then it broke And then it went down to 1881 and then it had this tremendous rally And actually we ended up moving to stop so but 1965 would have held but I said put it at 70 and then I said 75 Anyways, then we did a third add or you could have done a third add or actually let me just move over here On the five-minute chart, but long story short This this was one of those ones that you had to be patient with if you couldn't be patient with it You could have scalped out of it this morning for 20 25 cents Again, we just didn't get this immediately if we had I would have never had to wait in it forever But this first entry here in the morning was profitable if you got out, okay, but because I did not We you know, we had to suffer through the rally, but I really did think this was lower I never thought even with the rally that it would a hundred percent flip and go green It didn't so this looks great and in a couple pennies here It's gonna break the loan if it doesn't then I will be out of it But I think that it does why one o'clock this is weak Let's look at the market Yeah, I mean, I think you I keeps going look at the market here, so So we'll see If it doesn't if it's done, we're gonna have to be out, but I believe that this will Go at least in the 60s 1860 1850 Be careful here with it now though But the third ad we took one trade and add actually be second at the third trade Really did help this make it worthwhile because it was it pulled our price up, which is rare, but did happen here We'll see where this goes, but this is gonna turn out to be a decent one here And I'll be watching it every second here every penny counts with this So once we get through the loaf we do I think it they should keep going So go look everyone if you're still in it and we'll see what we get tomorrow