Anyonyvinod

We all know that Binomial distribution is used when we are looking at number of defectives rather than the defect itself. For example, Inspection of a part can have outcome of Pass or Fail, here there are 2 outcomes and we can count the numbers of passed or failed items based on our interest. >This is one of the requirements to have only Two outcomes for a trial for the defectives to follow a Binomial distribution In statistics we collect samples to study the population parameter, say for example a bank manager wants to know how many customers are interested in vehicle loan and out of the 100 customers 40 are not interested. So the answers from each customer was independent (Either they say Yes or No) > The number of such trials needs to be fixed in order to have the experiment follow Binomial distribution. > Because we have independent trials the probability of each outcome is constant.

Gemba refers to work place investigation, where, investigation is focused on a particular topic by concerned stakeholders and some statistical tools like 5why is used to gather data which will be used for root cause analysis. Example- A manufacturing process where a particular process parameter is out of control limits and DPMO is spiked for the targets MBWA refers to work place visit by managers not in particular but in general to ensure there are no surprises on the current process is seen. Just a new eye on the process and people. Example- Shopfloor vist by managers during shift change over or product change over in the line

Cp and cpk are used to study the process which is stable otherwise the samples will not represent the process. about the inference Cp talks about spread of the values of a sample collected from the process compared with the specification limit. Smaller the spread better the Cp but Cpk talks about how far is the sample mean to spec mean. Sample mean closer to spec mean better the Cpk. In other words Cp is Precision Cpk is Accuracy