Trends and Practices in Process Capability Studies

TL;DR

This paper reviews various process capability indices used in manufacturing, discussing their definitions, applications, and statistical properties across different process distributions, with insights into their relationships and inferential aspects.

Contribution

It provides a comprehensive review of process capability indices, including recent developments and methods for multivariate and non-normal processes, enhancing understanding for quality improvement.

Findings

Reviewed process capability indices for normal and non-normal distributions

Discussed relationships among different capability indices

Explored multivariate process capability analysis methods

Abstract

Quantifying the "capability" of a manufacturing process is an important initial step in any quality improvement program. Capability is usually defined in dictionaries as "the ability to carry out a task, to achieve an objective". Process capability indices(PCIs) is defined as a combination of materials, methods, equipments and people engaged in producing a measurable output. PCIs which establish the relationships between the actual process performance and the manufacturing specifications, have been a focus of research in quality assurance and process capability analysis. Capability indices that qualify process potential and process performance are practical tools for successful quality improvement activities and quality program implementation. As a matter of fact, all processes have inherent statistical variability, which can be identified, evaluated and reduced by statistical methods. Generalized Process Capability Index, defined as the ratio of proportion of specification conformance (or, process yield) to proportion of desired (or, natural) conformance. We review the process capability indices in case of normal, non-normal, discrete and multivariate process distributions and discuss the inferential aspects of some of these process capability indices. Relations among the process capability indices have also been illustrated with examples. Finally we also consider the process capability indices using conditional ordering and transforming multivariate data to univariate one using the concept of structural function.