The Model of the Production Process for the Quality Management

2Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

This article is a result of the research on the models of the production processes for the quality management and their identification. It discusses the classical model and the indicators for evaluating the capabilities by taking as its starting point the assumption of the normal distribution of the process characteristics. The division of the process types proposed by ISO 21747:2006 standard introducing models for non-stationary processes is presented. A general process model that allows in any real case to precisely describe the statistical characteristics of the process is proposed. It gives the opportunity for more detailed description, in comparison to the model proposed by ISO 21747:2006 standard, of the process characteristics and determining its capability. This model contains the type of process, statistical distribution, and the method for determining the capability and performance (long-term capability) of the process. One of the model elements is proposed, own classification and resulting set of process types. The classification follows the recommendations of ISO 21747:2006 introducing models for the non-stationary processes. However, the set of the process types allows, beyond a more precise description of the process characteristics, its usage to monitor the process.

References Powered by Scopus

Total quality management and operational excellence: Text with cases

118Citations
465Readers
Get full text

Cited by Powered by Scopus

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Alot, Z. (2017). The Model of the Production Process for the Quality Management. Foundations of Management, 9(1), 43–60. https://doi.org/10.1515/fman-2017-0004

Readers over time

‘17‘18‘19‘20‘21‘22‘2301234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

60%

Lecturer / Post doc 1

20%

Researcher 1

20%

Readers' Discipline

Tooltip

Chemistry 2

40%

Computer Science 1

20%

Economics, Econometrics and Finance 1

20%

Psychology 1

20%

Save time finding and organizing research with Mendeley

Sign up for free
0