2015/03/24 by Mahendra Saha, Saha, Mahendra, Sudhansu S. Maiti +1
Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Applications (stat.AP) #FOS: Computer and information sciences #Optimal Experimental Design Methods #Scientific Measurement and Uncertainty Evaluation #stat.AP
paper · pdf · doi:10.48550/arxiv.1503.06885
22 pages
arxiv created 2015/03/24 · openalex publication_date 2015/03/24 · arxiv updated 2015/03/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.