Lean Six Sigma Green Belt – Six Sigma Analyze Phase Part 4

8. Risk Based Analysis – FMEA_Part 2

Few other definitions of SME template which we have seen current control. How are you trying to control that? Are you having any preventive mechanism? Right. How would you control that? For example, think about this I have an iron box to iron the clothes. I want to iron the clothes and I have an iron box and I forgot to switch it off. Do you think if I forget to switch it off, it’s going to be heated to a temperature of 200 degrees or 300 degrees? Does that happen? No.

Most of your iron box have this mechanism which automatically switches it off. It will automatically get switched off, right? If you keep it for a certain time or if it reaches a particular temperature, it automatically switches itself off. That is a preemptive control. Do you have those kind of a control? And then comes severity, detection and occurrence. But here is a risk priority number and this is how you calculate it. Severity multiplied by occurrence, multiplied by detection is going to give you risk priority number. Based on this number, you are going to prioritize your risks. Let us look into the severity.

How critical or serious a potential failure could be on your product or the process. If the failure is so serious that it can stop your production, it is graded as ten. And if it is not going to have a lot of impact on your project or process or product, then you grade it as one. Then you have another category which we need to understand detection ability to detect the failures. How easy is it to detect the failure? If the potential failure is easy to detect, the grade should be low.

One you rate a particular risk or an event or an activity or a function as one if it’s extremely easy to detect and you rate it as ten. If it is extremely difficult to detect all the natural calamities earthquakes, tsunamis, right? Wildfires in the forest all of a sudden all these are very hard to detect. Hence probably we give a rating of ten when it comes to detection for those kind of events, then comes occurrence. How often does this failure occur? The likelihood of an occurrence is expressed in a ranking of one to ten. One for rare occurrence, all your natural calamities, they might be extremely difficult to identify and they are also very rare, right? Ten for often activities. How often does your wife shout at you? Very often you rate it as ten. Can you detect your wife shouting at you? Yes, almost always. So it’s one extremely easy, right? So jokes are part one for rare event and ten for most often occurring events. Here is the definition or the various definitions of the various ratings which we have. We have already discussed that if severity is given as one, it has no effect, no discernible effect or slight inconvenience cost to operator or to the operation process.

Or there’s no effect. Absolutely right. From there it moves on. And if I’m going to rate something as ten, it is hazardous. Without warning, it might endanger the operator, machine or assembly without a warning. Nine means at least there is a warning. There is a warning symbol from so you can change this definition based on your process, based on your product, based on your industry, your sector, your client and all that. But it is extremely recommended or highly recommended not to make changes to these top set. Ten and nine. Try not to meddle with this. Try not to make any changes to this. So you can use this as a quick reference.

In classifying or putting a number against each and every event, then comes occurrence. How likely is an event to occur? One means failure is unlikely. How unlikely is it? Less than 0. 1 thousand machines. So there might be one failure in probably 100,000 or more entries in CPK. We have already discussed this, right? CPK value would be greater than or equal to 1. 67 if the occurrence is one. Right? What do you mean by CPK greater than or equal to 1. 67? We have discussed in the measure phase also, right? My mean is closer to my target, right?

If this is the dartboard and this is my bullseye, all the points might be falling somewhere here at and around this target. If this is the scenario, my CPK value will be greater than or equal to 1. 67. So almost always I’m on target. That is what it means, right? Only one in 100,000 times I might miss my target. Moving on to ten. Very high. That means there are one in ten errors which might occur in CPK value significantly drops. That is another way of looking into occurrence. This is a reference for you guys. Then comes detection. How likely is it for me to detect something going wrong? If I’m putting as one? That means design control will certainly detect a potential cost, right? And a means something is error proved. I’ll not let you make a mistake.

All your electronic gadgets, right? Think about your USB port, right? It is error proof. I cannot put my USB slot or I cannot put my USB device in my land slot. I cannot put in my VGA slot, HDMI slot or power slot, right? Can I put my USB device in the power slot? Can I do that? No. It is error proof. It will not even let me do that. If I’m using a gauge to detect something. If I’m using a thermometer to measure the temperature, that is your category. B c means I am doing a manual inspection. If I’m doing a manual inspection, it is so much difficult for me to identify something to detect something going wrong.

If I’m using a gauge, it is so much and if I’m using or if I’m trying to error proof, it is extremely easy for me to identify something going wrong. Right. Ten means absolutely certain of non detection. You cannot detect it or you have not checked it or you are not going to check it or you cannot check it. That way you rate the detection as well. And this is how we are going to calculate the risk priority number to prioritize my risks. Right. Severity multiplied by occurrence, multiplied by detection. And if I have a failure mode, I need to know what is the effect it’s going to have, what is causing me? Do I have any controls in place? I multiply all these three to get my risk priority number based on which I’m going to prioritize my events and then come up with an action plan. This is what I do. Let us look into a quick case study. Reduction and risk priority numbers have severity. I have occurrence and AV detection.

Right. I need to reduce, right? How can I do that? Severity. This number cannot usually be changed only if you change the design or process. Only then probably I can reduce the severity ranking. Ranking, look into occurrence design process revisions or preventive controls can reduce occurrence rating detection. How can you reduce that? This number can be reduced by instituting a good detection technique. Probably a good inspection process or a testing or a visual conclusion will help me detect the problem easily. Here is a case study. Now can you help me order the importance of addressing these process steps to reduce the overall risk? All have the same risk priority number. What are you going to prioritize first? Would it be A, B or C or D?

Which one would you rank first? Importance should be given to severity. Right. You will see that severity ten means it’s going to have significant impact. It’s going to be disastrous and this disastrous event is going to occur eight times or it’s going to occur most number of times though it’s great to detect. This is how you prioritize it’s going to occur. Something which is going to be deadly is going to occur most often. So probably if you ask me, I would rate B is number one priority for me, followed by D because it has high severity. And then I would move on to A because A and B both have A and C. By the way, both have the same severity. But this is occurring most number of times. So probably I will say it will be B followed by D followed by A and then C. This is the order in which I’m going to prioritize these events or risks.

9. Pareto Chart

We will move on and discuss a different concept, which is Pareto Chart. It is a visual tool used to identify which problems are most significant. If you look into this Pareto chart, hard disk is supposedly causing most number of problems for me, followed by PCB circuit board, followed by pre, then the CDROM and the keyboard. But do I need to focus on all of these things? No. Pareto Chart says often we use 80 20 rule. 80% of the problems occur because of 20% of the causes. So my hard disk and PCB both put together probably is having 80% of the problems. So if I address these two issues, I’ll address 80% of the problems. I can either represent in this way or I can represent in this way. It doesn’t matter, right? So, Parado Chart focuses on area where we can have the greatest financial impact in the least amount of time or with the fewest resources.

Spend less time, spend few resources, give me the maximum benefits. What would you do? You would end up using Parado chart. Okay, now how do I construct a parado chart? By the way? This is how you do. You identify what is your critical to quality or what is your critical to output. Why? For data collection, select what would the broad categories be to be explored? Sort the data into those specific categories. Graph with the bars which are ordered in decreasing frequency. Beginning from left, check your chart for 80 20 pattern and make sure you have not mixed dissimilar categories into one. If these five steps are sounding alien to you, then bear with me while we do an exercise on this and then things will become even more clear for you. Here is a pareto analysis. It is used to organize the data to show major inputs which are influencing your output. It is frequently referred to as the search for significance. You try to identify the significant things, right?

The basis for building a pareto is 80 20 rule. Typically approximately 80% of the problems result from approximately 20% of the causes. An outcome of the Pareto analysis is nothing but your Pareto chart. Here is a case study which we’ll be focusing on now. Gym promotional Campaign let us read and understand the case study first. After a promotional campaign, number of walk ins to the gym increased from 2500 to 4000. Aspirants would fill in the application form. People who want to join your gym will fill the application farm.

They would usually have 10% incomplete applications. But because of the promotional campaign, because of the increase in the number of applications, they have seen that the percentage of incomplete applications have increased to 20% from 10%. Now, the Gmono is a little concerned. He has listed down all the sections in application form and the frequency of each section not being complete. You are Six Sigma Consultant now, right? You are the Six Sigma consultant. Please carry out appropriate analysis to identify the vital few sections which when fixed, will reduce the percentage of incomplete applications.

What would you do? Now comes a magic box into play. What is a magic box, by the way? Minitab, right? So let us look into Minitab and let us try to solve this problem. Let me go to this. Here is this application form has all this increase. These are the number of incomplete entries out of all application forms. And here are the various remarks on what was missing. In all, that entire name was missing in three entries. Nationality was missing in two entries. Date of birth. People were entering their date and month, but they were not entering their year. Because maybe they do not want to disclose their age and tell to the world that they are old now. Maybe 238 entries, number of children. Only one application, farm have that missing entry, so on and so forth, right? Mobile number. The 132 people did not mention their mobile numbers. So these are the various sections.

And this is the count of incomplete increase. And these are a few of the remarks on what we’re missing, basically. Now I want to do a parado chart on this. I simply go to Stat quality tools and I do pareto chart. Click on that. Here is what I get. Right? Defects. Where are the defects in or in this application form entries? How many defects are the frequencies or in count of incomplete entries? I simply select that and click on okay, here comes the parado chart. Count of incomplete entries is here. And the reasons on why the application form was incomplete or which section was incomplete is on the X axis. Look at this. Date of birth contributes to 238 entries and 23. 8% of the total. Incomplete applications are because of incomplete date of birth. The second one is 189 credit card details.

189 entries were missing. It contributes to 18. 9% of the total. And if I add these 223. 8 and 18. 4, I get 42. 7 which is accumulative percentage. Mobile numbers. 132 entries were missing which contributes to 13. 2% in total. And if I do accumulate, if I add up date of birth, credit card details and mobile number missing entries, the count would come up to 55. 8. And I have to go until I get 80%. Here approximately 79 or 7. 9. And the cumulative is 83. 7. So here I’m touching that 80%. If I go up, go up, go up, go up. It says, okay, here is where you get 80%, right? You can look into that percentage by comparing against us. 80% is here cumulative, right? And that says nearest landmark. What should I do now? Focus on nearest landmark and all the things which are left to this. That means reference, contact details, income details, mobile number, credit card details and date of birth, 123-4516. If I focus on these six sections, I will be able to address 80% of the issues. Wow. In total how many sections do we have out of which you need to focus on only six. How many do I have? Click on this to go back to the worksheet. In total, 19 sections. Don’t focus on all 19, only focus on six out of these 19, it will help you address 80% of the issues. Wow, that sounds cool, isn’t it? Okay, let us go back to this presentation.

Here is the same thing which is attached right for your reference. If you forget on the navigation part, look into this. Go to stat quality tools per chat. This is how you need to fill the details and this is the output that you would get. This is your area of interest. 80%. Draw a line from 80%. Where does it interact here? Somewhere which is nothing but nearest landmark. Everything towards the left of nearest landmark is an area of interest for you. Focus on those, you’ll get 80% result, right? Six out of nine entries. 123456. Focus on six out of total 19 entries and your job is done within less time, you’ll get significant improvement.