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sczupryna0
Level I

Custom Measurement System Design and Qualification: A Case Study (2019-US-30MP-177)

Level: Intermediate

 

Stephen Czupryna, Quality Process Engineer, Samson Rope Technologies
Canh Khong, Certified Quality Technician II, Samson Rope Technologies

 

Like high-volume manufacturers, specialty manufacturers need to measure important product quality characteristics. However, they often discover that off-the-shelf measurement systems, many of them designed for high volume purposes, do not meet their needs. When this happens, they have no choice but to design and qualify their own equipment. This case study outlines the development of a custom measurement system by a diverse team of people at Samson Rope Technologies, a high performance rope manufacturer.

 

Samson needed the system to measure the tensile strength of twisted HMPE (high modulus polyethylene) yarns used as sub-units in demanding ship mooring, tug and other rope applications. Samson faced four fundamental measurement challenges:

 

  • multi-ton break strengths
  • intrinsically slippery and difficult to grip
  • twisted in 2 directions (S, Z)
  • test is destructive

 

Unfortunately, readily-available tensile testing grips sold by instrument manufacturers were unable to provide acceptable results. This left Samson Rope with only one choice – in-house custom grip development

 

This paper outlines the process approach taken by the development team and how JMP dramatically improved the team's creative thinking process. The first step was to use fundamental engineering principles and the-wisdom-of-colleagues to identify controllable factors and safe experimental ranges. The factors and ranges were used in a Definitive Screening experiment to identify key main effects and, with augmentation, to create a useful predictive model of the measurement process. The team followed the grip design optimization with iterative measurement systems analysis (MSA) to fine-tune the testing procedure and improve the system's signal-to-noise ratio.

 

In summary, the case study is yet another demonstration of the philosophical underpinnings of statistical thinking - to treat all work (including measurements!) as a process, that all processes vary and that the key to success is to understand and reduce variation.