Stable Process
A simpler definition : A process which can be consistent over a period of time, in producing its output is a stable process
Capable Process : A process which can meet the target mean and customer specification limits . Process capability can be measured by two terms , Cp & Cpk. Cp talks about Process Capability and Cpk talks about process performance.
Cp is a ratio of tolerance of width to the short term spread of the process. It does not consider the centre of the process. Cp assumes that the process is stable
- If Cp < 1, process is incapable.
- If Cp=1, then this process meets the expectation barely , there could be defects atleast .3 %
- If Cp > 1, then this process output falls within specification, but defects could be there if the process is not centred .
- If Cp=2 , then we achieve 6 sigma
Cpk on the other hand, considers process centring. It is a ratio of the distance measured between the process mean and the specification/tolerance limit closer to half of the total process spread. It assumes that the process is stable
- If Cpk=Cp, the process mean is on target
- If Cpk=0 then the process mean falls on one of the specification limits, 50% of the process output falls beyond the specification limits
- If Cpk<-1 the process mean falls beyond both specification limits and therefore 100% of the process output is out of specification limits
A process is assumed to be statistically stable before we calculate its capability. So process stability is of paramount importance for all types of processes, especially if we are running a DMAIC project. But if we are not able to control the existing process and are unable to make it stable or if the improvements that we make on the existing process do not yield the necessary or expected results, then its better to go for a new process through DMADV or DMAODV
Now as we have seen what stable and capable process are all about, let us see the impact of a process being unstable.
What could be the reasons for a process to be unstable
1. It could be because of special cause variations of different nature. Common cause variations are inherent to the process and hence cannot be a cause
2. It could be because the design of the process may not be good enough to meet the customer expectations.
Eg:1
Let us see how special causes can impact stability
Everyday , the local agent for Aavin milk, needs to provide milk to all of his customers between 5 AM – 5:15 AM IST. He chooses a pre-defined route on a routine basis and goes by the same route daily and delivers milk, by a bicycle. But every now and then, he misses the timelines by 10-15 minutes and delivers late ranging from 5.25 AM to 5.30 AM IST.
This is because , one day he sees road blockage in few lanes due to plumbing work done for water connection. As a result, he has to take a circuitous route and then on an another day, sees a road blockage because of telephone work happening. On some other days, it could be because the milk delivered to the agent was delayed and in a different occasion, because stray animals were there in the street, he has to take a different route and this delayed his delivery timelines.
As we can see here, these are all different reasons and all of them special causes which make this process of - delivering the milk, unstable. So we need to find an alternative way of improving this process (DMADV or DMAODV). One way is the agent having a motorbike to improve his speed of delivery. Other option is to find better or closest alternate routes for each of the problematic lanes/streets. First option is much better though
Conclusion: All processes need to be stable in general. A capable process is assumed to be statistically stable as well. When an improvement is being done for an existing process which requires stability, and if we are not able to see the necessary yield or stability in the process, then we go for a DMADV or DMAODV project.