MACHINE PROCESS CAPABILITY, ITS IMPLICATIONS

       


Process capability is a statistical measure that indicates how well a process or a machine is able to produce output within specified limits or tolerances.

It is typically expressed in terms of the process capability index (Cpk), which is calculated by comparing the actual output of the process to its desired output, and taking into account the variability of the process.

In the case of machine calculations, process capability refers to the ability of the machine to perform calculations accurately and consistently within specified tolerances. This can be evaluated by measuring the machine's accuracy and precision, as well as its ability to maintain its performance over time.

To assess the process capability of machine calculations, one approach is to use statistical process control (SPC) techniques. This involves monitoring the output of the machine over time, and using statistical methods to identify any patterns or trends that may indicate problems with the machine's performance.

Another approach is to conduct a capability analysis, which involves collecting a sample of data from the machine's output and calculating the Cpk value to assess the machine's ability to meet the specified tolerances.

Overall, the process capability of machine calculations is an important consideration for ensuring the quality and accuracy of the output, and for maintaining the reliability and efficiency of the machine over time.

As we know Cp and Cpk are both process capability indices that are used to assess the ability of a process to produce output within specified tolerances. However, there is an important difference between these two indices:

Cp is a measure of the potential capability of a process, which is calculated by comparing the width of the process spread to the width of the specification limits. It indicates how well a process is centered within the specification limits and how much variability there is in the output.

Cpk, on the other hand, is a measure of the actual capability of a process, which takes into account both the centering of the process within the specification limits and the variability of the output. It is calculated by comparing the minimum of the difference between the process mean and the specification limits to the process variability.

In other words, Cp assumes that the process is centered within the specification limits, whereas Cpk considers both the centering and the variability of the process. Cpk is generally considered to be a more robust and informative measure of process capability, as it provides a more complete picture of how well a process is able to meet the specified tolerances.

Process Capability means: Voice of customer /Voice of Process

CPK = Min [(USL – mean/3 * std.),(mean-LSL/3*std.)] To calculate the CPK, take the minimum value of either of the following values. The upper limit minus the mean divided by 3 times the standard deviation or the mean minus the lower limit divided by 3 times the standard deviation

It's worth noting that both Cp and Cpk are used in conjunction with control charts and other statistical process control techniques to monitor and improve the performance of a process over time.

Important Note :

Cpk can never exceed Cp, so Cp can be seen as the potential Cpk if the overall average is centrally set. In the example, Cp is 1.17 and Cpk is 0.67. 

This shows that the distribution can potentially fit within the specification. However, the overall average is currently off-center.

This process center may shift min 1.5 sigma  to go off center during the course of time 

Limitations 

Cpk cannot be used if the:

  1. Data is not a bell-shaped normal distribution
  2. The control chart is not in control and free from special causes.

It is recommended to have at least 25 subgroups and preferably each subgroup having >1 data point. The greater the subgroup's size the higher likelihood the special cause variation is detected and that it exists if it is detected.  

 Prof.PvChandra -Founder & CEO 
 BE Mech , MTech (Industrial Engg), PGD (Operations)
 SRH MANAGEMENT CONSULTANTS AND TRAINERS
 Leading Innovative Strategy in Organization-USA 
 ISO Lead Auditor, Certified Quality Manager
 Data Analyst for Lean Six Sigma (USA)
 Lean Six Sigma Master Black Belt(IASSC -USA)
 Certified Toyota Production System(IIT)



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