Statistical Procedures for Machine and Process Qualification

USD 149.95 (Print)

incl. taxes, plus possibly shipping costs

published
€129.90 (Print)

incl. taxes, plus possibly shipping costs

published
Description
Statistical Procedures for Machine and Process Qualification
This book has established itself as a standard reference for everyone dealing with statistical problems in industrial production. The focus is put on the application of the procedures required for machine acceptance and process qualification as well as interpretation of the calculated results. Great value is also set on the visualization of results in many different variations. This helps the practitioner to quickly gain insight into the situations he has to evaluate.
Especially the included company guidelines are proof of the practical application and the benefit of the discussed topics in daily practice.
The 6th, completely revised edition takes the latest developments in international and national standards (i.e. DIN ISO 21747) into account. The company guidelines of
Daimler AG
General Motors Powertrain
Robert Bosch GmbH
Volkswagen AG
as well as the Ford Test Examples for the Evaluation of SPC Systems are included.
The case examples included in the book as well as most of the charts and tables can be recreated using the qs-STAT® demo version. You can download this qs-STAT® demo version either from the Q-DAS® website (www.q-das.de) or order it directly from Q-DAS®. The data necessary for handling the case examples are also included in the demo version. For support and for a better understanding of the software we offer a number of eLearning courses you can try out.
Statistical Procedures for Machine and Process Qualification
This book has established itself as a standard reference for everyone dealing with statistical problems in industrial production. The focus is put on the application of the procedures required for machine acceptance and process qualification as well as interpretation of the calculated results. Great value is also set on the visualization of results in many different variations. This helps the practitioner to quickly gain insight into the situations he has to evaluate.
Especially the included company guidelines are proof of the practical application and the benefit of the discussed topics in daily practice.
The 6th, completely revised edition takes the latest developments in international and national standards (i.e. DIN ISO 21747) into account. The company guidelines of
Daimler AG
General Motors Powertrain
Robert Bosch GmbH
Volkswagen AG
as well as the Ford Test Examples for the Evaluation of SPC Systems are included.
The case examples included in the book as well as most of the charts and tables can be recreated using the qs-STAT® demo version. You can download this qs-STAT® demo version either from the Q-DAS® website (www.q-das.de) or order it directly from Q-DAS®. The data necessary for handling the case examples are also included in the demo version. For support and for a better understanding of the software we offer a number of eLearning courses you can try out.
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Author Info

Prof. Dr.-Ing. Edgar Dietrich war Mitbegründer und langjähriger Geschäftsführer der Q-DAS GmbH&Co. KG, die er 2015 an Hexagon MI verkaufte. Zuvor war er Professor für Technische Informatik der Dualen Hochschule in Mannheim und mehrere Jahre Vorsitzender des ISO TC 69 SC 4, das für alle ISO-Normen zur statistischen Analyse im Produkt- und Prozessmanagement verantwortlich ist. 2019 gründete er die IconPro GmbH und ist deren Mitgesellschafter. Er hält die Vorlesung „Industrielle Statistik“ am WZL der RWTH Aachen.

Prof. Dr.-Ing. Edgar Dietrich war Mitbegründer und langjähriger Geschäftsführer der Q-DAS GmbH&Co. KG, die er 2015 an Hexagon MI verkaufte. Zuvor war er Professor für Technische Informatik der Dualen Hochschule in Mannheim und mehrere Jahre Vorsitzender des ISO TC 69 SC 4, das für alle ISO-Normen zur statistischen Analyse im Produkt- und Prozessmanagement verantwortlich ist. 2019 gründete er die IconPro GmbH und ist deren Mitgesellschafter. Er hält die Vorlesung „Industrielle Statistik“ am WZL der RWTH Aachen.

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