<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

The Model of the Production Process for the Quality Management

Foundations of Management

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"The Model of the Production Process for the Quality Management"}

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...

The Model of the Production Process for the Quality Management

Online veröffentlicht: 22. Feb. 2017

Seitenbereich: 43 - 60

DOI: https://doi.org/10.1515/fman-2017-0004

Schlüsselwörter
model of the process, identification, process evaluation, statistical process control, quality management

© Faculty of Management, Warsaw University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The Model of the Production Process for the Quality Management

Online veröffentlicht: 22. Feb. 2017

Seitenbereich: 43 - 60

DOI: https://doi.org/10.1515/fman-2017-0004

Schlüsselwörtermodel of the process, identification, process evaluation, statistical process control, quality management

© Faculty of Management, Warsaw University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
model of the process, identification, process evaluation, statistical process control, quality management