9-5

Verification of the quality of a product before the product can be built into the market is necessary so as the selected production process is able to perform at the set quality level. The process sometimes uses involves forms of trial run or a pilot test. Executives have to duplicate as closely as possible the real operating environment when the trial runs occur. The test runs involve the use of same equipment’s, procedures, workers and also the same suppliers since the deviations from a realistic operating environment may invalidate the result of the process. The output in this case is measured against a standard using rigorous statistical analysis so as the overall process capability can be assessed (Akpolat, 2017). 

The capability ratio aids in assessing the process ability in achieving a required quality level. The ratio indicates whether if the process is able to consistently produce good quality parts when comparable acceptable are compared with the process variation.

I = U – L where: U= upper specification limit

L= lower specification limit

i =standard deviation (process variability)

This standard deviation is then calculated by the use of an actual output from the trial run then using a multiplier of six in the establishment of the degree of confidence. The process output hence falls within the upper and the lower limits. A correlation factor k which reflects differences between the actual process mean (m) and a design target (D) is introduced as most of the preferences doesn’t yield process mean that’s exactly equal to the process mean (Boakye,2017).

Cpy = Cp (1-K) where K= (D-m)

= (U – L)/2

DPMO= (Total number of defects found in a sample/total number of defects opportunities in the sample) X 1000000

Dividend yield = (Annual Dividend /Current stock price)

A CPK of 1.5 and above shows that the process meets its desired quality levels.

Example of a

Suppose that the design engineering team set the specifications for length of a stamped sheet-metal part at 10 inches (D) with acceptable tolerances of ±.05 inches (U and L). The average length of the products produced by the actual stamping process is 9.99 inches (m) with a standard deviation of .015 inches (s). The calculations for the CP and CPK are as follows:

                        CP = (10.05-9.95)/6(.015)

= .10/.09

= 1.11

                        K = (10 – 9.99)/ ((10.05-9.95)/2)

= .01/.05

= .20

                        CPK = 1.11 (1-.20)

= 1.11(.8)

= .88

Processes that function with "six sigma quality" over the short term are presumed to crop long-term defect levels below 3.4 defects per million opportunities

References

Akpolat, H. (2017). Six sigma in transactional and service environments. Routledge.

Boakye, K., Hanna, M. D., Apenteng, B. A., Kimsey, L. G., Mase, W. A., Opoku, S. T., ... & Tedders, S. H. (2017). Adopting Lean Six Sigma Operational Improvement Principles in Critical Access Hospitals: Lessons Learned from an Academic-Practice Partnership.

Furterer, S. L. (2016). Lean Six Sigma in service: applications and case studies. CRC press.