Statistical Process Control (SPC) and Automation

Article

Bajaria, Hans J.   (1986, ASQC)   Multiface, Inc., Dearborn, MI

40th Annual Quality Congress, May 1986, Anaheim, CA    Vol. 40    No. 0
QICID: 3161    May 1986    pp. 76-83
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Article Abstract

Among many viable approaches to improve Quality and Productivity of the manufacturing processes in automotive related industries, the recent thrust continues to be implementation of Statistical Process Control (SPC) and Process Automation. These two items are consuming a significant portion of the automotive industry investment funds. For such an investment to pay off in a timely manner, the inherent ability of process automation to provide a higher level of quality must be integrated with SPC.

In this paper we examine different schemes for integrating SPC and automation. The various elements of the schemes considered are: Forms of Data Collection, Types of Data Analysis and Plotting, Types of Signals for Detecting Incipient Troubles, Discovery of Associated Disturbing Causes and Correction of those Causes. For this integration to succeed, an understanding of both functional and process control automation and their balance is also needed. We discuss the fundamental differences between the deterministic and probabilitistic process control automation and their balancing criteria. To avoid a disproportionate distribution of the invested funds it is necessary to optimize process performance with respect to three forms of automation: functional automation; deterministic process control automation; and probabilistic process control automation.

This paper provides guidance to facilitate automation of manufacturing process or to improve the efficiency and yield of existing automated processes.

Keywords

Statistical process control (SPC),Automobile industry


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