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During the past decade interest in quality management has greatly
increased. One of the central elements of Total Quality Management
is Statistical Process Control, more commonly known as SPC. This
book describes the pitfalls and traps which businesses encounter
when implementing and assuring SPC. Illustrations are given from
practical experience in various companies. The following subjects
are discussed: implementation of SPC, activity plan for achieving
statistically controlled processes, statistical tools, and lastly,
consolidation and improvement of the results. Also, an extensive
checklist is provided with which a business can determine to what
extent it has succeeded in the actual application of SPC. Audience:
This volume is written for companies which are going to implement
SPC, or which need a new impetus in order to get SPC properly off
the ground. It will be of interest in particular to researchers
whose work involves statistics and probability, production,
operation and manufacturing management, industrial organisation and
mathematical and quantitative methods. It will also appeal to
specialists in engineering and management, for example in the
electronic industry, discrete parts industry, process industry,
automotive and aircraft industry and food industry.
During the past decade interest in quality management has greatly
increased. One of the central elements of Total Quality Management
is Statistical Process Control, more commonly known as SPC. This
book describes the pitfalls and traps which businesses encounter
when implementing and assuring SPC. Illustrations are given from
practical experience in various companies. The following subjects
are discussed: implementation of SPC, activity plan for achieving
statistically controlled processes, statistical tools, and lastly,
consolidation and improvement of the results. Also, an extensive
checklist is provided with which a business can determine to what
extent it has succeeded in the actual application of SPC. Audience:
This volume is written for companies which are going to implement
SPC, or which need a new impetus in order to get SPC properly off
the ground. It will be of interest in particular to researchers
whose work involves statistics and probability, production,
operation and manufacturing management, industrial organisation and
mathematical and quantitative methods. It will also appeal to
specialists in engineering and management, for example in the
electronic industry, discrete parts industry, process industry,
automotive and aircraft industry and food industry.
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