We have seen that we can’t change the garage’s width (or customer’s specifications), the only way out is to adjust the process variability (car’s width) according to the customer’s specification. This is done by continuous improvement of the process using 6sigma tools.
6sigma tools is like a clamp where we gradually tighten (continuous improvement) the screw to compress a thing (variability in the process)!
Right now we are not in a position of going into the details of the standard normal distribution hence, for the time being let’s assume that my manufacturing process is stabilized, which is represented by a symmetrical curve shown below
The main characteristic of this curve is that the 99.7% of the product would be between LCL & UCL or within ±3σ distance from the mean (μ). Only 0.3% or 3000ppm products would be beyond ±3σ or defective products. So width of the car is equivalent to the width of the process = UCL-LCL = voice of the process = VOP = 6σ = ±3σ.
Second point is that the curves never touches the x-axis à means that there will always be some probability of failure even if you move to infinity from the mean (probability can be negligible but will be there).
Now let’s overlap the above process curve with the customer’s specifications (=12σ = ±6σ) or the garage’s specifications.
We can see that there is a safety margin of 3σ on both side of the process control limits (LCL & UCL). In layman words, in order to produce a defective product, my process has to deviate by another 3σ, which has very remote possibility. Statistically ±6σ (position of LSL & USL) from the mean would account for only ~3.4 ppm failure (don’t bother about the calculation right now, just understand the concept). For this has to happen, someone has to disturb the process deliberately. Compare this failure of 3.4 ppm at ±6σ level with 3000ppm at ±3σ level!
Even if the mean of the process deviate by ±1.5σ, there is enough margin of safety and it will not impact the quality and in regular production, this deviation of ±1.5σ is quite common.
We have seen that variation is a part of life, we need to learn to live with it. At most we can make an effort to reduce it by using 6sigma tools.
This happens because you can’t control everything involved in any process. There are some uncontrollable factors known as “common causes” in six-sigma. For example
You are producing some part to be used in automobiles, there will be a variation in product specification as there will be wear and tear of machines, change of operators etc.
If we repeat any process 100 times, all product/output of the process would not have same specifications, it might happen all 100 are within the desired specification. If we plot a histogram of the product specification from a stabilized process, it would look like
We can see that maximum products would be clustered around the mean and as we move away from the mean, number of products decreases.
Width of the customer’s specification is analogous to garage’s width and the process variation is analogous to car’s width. If you don’t have proper control on your process (driving) you are going to crash your process (car) against the customer’s specifications (garage walls).
Now I feel that everyone agrees that variation is a part of life and we need to learn to cope with it. The only thing we can do is to minimize it by using some proven methodology so that whatever we are producing (product or services) should always meets customer’s specifications or should have enough safety margin. This proven methodology of reducing variability is called as 6sigma.
Let the width of the garage (D) and that of the car (d) is measured in some units called as sigma or σ, further
Width of the garage is sacrosanct = 12σ (assume for the time being), then following three cases can occur depending on the ratio of D/d = Cp.
The process sigma level is 6σ when the Cp =2, this is represented by case ‘C’ given below. Point to be noted is that there is a margin of safety (=3σ) on both side of the car before car touches the garage. The ideal width of car is taken as 6σ (don’t ask why, right now!)
Process capability Cpk: is measured in the terms of the σ distance between the center of the of the car (C1) and the wall of the garage. Cpk tell us “how far is the car from left wall or the right wall of the garage (or customer’s specifications).
You may argue that what’s the big deal if my existing car doesn’t fit into the garage, I will rebuild the garage that can fit my bigger car.
You can always do it with garage but not with customer’s specifications as you can’t dictate it or simply customer won’t change his processes to fit your defective products. The only way is to improve your existing process or else lose your business to your competitors.
We can easily understand the concept of six-sigma using the analogy of parking a car into the garage and if you want to understand it more seriously, just imagine that you are entering a tunnel (instead of garage) at the speed of 150-200 Km/Hr!
When ever a car is bigger than the garage, it’s not possible to enter the garage. Take another car whose width is slightly less than the width of the car. This time it is possible to enter the garage but we will get frequent scratches unless you are an expert driver! Take a third car whose width is just half of the width of the garage , it’s is now possible for me to enter the garage even if I am drunk.
Car width represents the “current process capability“
Garage width represents the “Customer’s specifications“
We should remember that
“We need to buy a car according to the dimensions of the garage”
“We need to change our manufacturing processes to meet the customer’s specification”
It gives me immense pleasure to welcome you all to this website. This is not just another website on six-sigma as our USP is to make you learn all six-sigma concepts using figures and diagrams. During last 7-8 years we developed our own way of learning applied statistics with the help of diagrams and figures. During this journey we also found that each statistical topic always have some connections with other topics and we can’t study any topic in silos.
We understand that there are many people who want to learn six-sigma but are unable to do it because of the statistics involved. Our website would help all those six-sigma aspirants to understand the statistical concepts with the help of figures and diagrams. This would be augmented by the industry related example. Hence this would be an ideal website if you wish to appear for green/black belt exam from a reputed institute.
Another major issue during applying six-sigma is the “use of right tool at the right place”. Hence our focus would not only to understand the concepts behind any statistical tools but also about selecting an appropriate tool for a given situation.
This website will start posting the six sigma topics (mainly statistical portion) from first week of July, 2016. Hence get registered as soon as possible. The way we are planning to run the course is by posting one topic every week so that we can understand it well before taking subsequent topic. Each topic will be followed by examples so that one can understand not only the concepts but also the use of appropriate tools.
We also understand that many of you won’t be having access to the six-sigma software, so we will be using excel sheet sheet in resolving statistical problems. We are emphasizing on excel sheet as it is available to all. Hope you won’t be having excuse of not learning six-sigma because of non-availability of the software.