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01.06.2015 | Ausgabe 3/2015 Open Access

Journal of Intelligent Manufacturing 3/2015

Robust product design and process planning in using process capability analysis

Zeitschrift:
Journal of Intelligent Manufacturing > Ausgabe 3/2015
Autor:
Angus Jeang

Abstract

In the past, the process capability index (PCI) was the only method used in on-line quality management. Recently however, attempts have been made to extend the on-line application to off-line applications, such as product design or process planning. Because the conventional PCI index, \(C_{pm}\), does not truly represent the measurement score, alternatives cannot be differentiated during off-line applications. Hence, a new process capability index, \(C_{pmc}\), was developed to reflect the differences among alternatives for easy decision making at the product design and process planning stages; however, the deterministic approach in using this new process capability index has the disadvantage of dealing with uncertainties during the product design and process planning activities. Quality engineering often employs an effective way of ensuring that high product quality and low production cost result from robust design, particularly in terms of its application in an uncertain environment. The new PCI was the score mainly used for off-line applications; thus, there is motivation for using new PCI values, \(C_{pmc}\), as the observed levels in the course of robust design implementation. The associated statistical method, response surface methodology, will be adopted for robust design in this study. Then, for robustness, the mean and tolerance values can be determined appropriately, as well as a measurement score for reasonable comparison and selection among candidates. Consequently, an economical and quality product design and process planning can be achieved statistically for the off-line applications.

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