Soft Modeling in Industrial Manufacturing (inbunden)
Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
196
Utgivningsdatum
2019-01-31
Upplaga
1st ed. 2019
Förlag
Springer Nature Switzerland AG
Medarbetare
Grzegorzewski, Przemyslaw (ed.), Kochanski, Andrzej (ed.), Kacprzyk, Janusz (ed.)
Illustratör/Fotograf
70 farbige Tabellen 57 schwarz-weiße und 33 farbige Abbildungen Bibliographie
Illustrationer
70 Tables, color; 33 Illustrations, color; 57 Illustrations, black and white; X, 196 p. 90 illus., 3
Dimensioner
234 x 156 x 13 mm
Vikt
468 g
Antal komponenter
1
Komponenter
1 Hardback
ISBN
9783030032005
Soft Modeling in Industrial Manufacturing (inbunden)

Soft Modeling in Industrial Manufacturing

Inbunden Engelska, 2019-01-31
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This book discusses the problems of complexity in industrial data, including the problems of data sources, causes and types of data uncertainty, and methods of data preparation for further reasoning in engineering practice. Each data source has its own specificity, and a characteristic property of industrial data is its high degree of uncertainty. The book also explores a wide spectrum of soft modeling methods with illustrations pertaining to specific cases from diverse industrial processes. In soft modeling the physical nature of phenomena may not be known and may not be taken into consideration. Soft models usually employ simplified mathematical equations derived directly from the data obtained as observations or measurements of the given system. Although soft models may not explain the nature of the phenomenon or system under study, they usually point to its significant features or properties.
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Innehållsförteckning

Data and modeling in industrial manufacturing.- From data to reasoning.- Data preprocessing in industrial manufacturing.- Tool condition monitoring in metal cutting.- Assessment of selected tools used for knowledge extraction in industrial manufacturing.- Application of data mining tools in shrink sleeve labels converting process.- Study of thickness variability of the floorboard surface layer.- Applying statistical methods with imprecise data to quality control in cheese manufacturing.- Monitoring series of dependent observations using the sXWAM control chart for residuals.- Diagnosis of out-of-control signals in complex manufacturing processes.