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A solution framework for response surface-based multiple quality characteristics optimization

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dc.contributor.author Bera, Sasadhar.
dc.contributor.author Mukherjee, Indrajit.
dc.date.accessioned 2019-02-01T05:51:28Z
dc.date.available 2019-02-01T05:51:28Z
dc.date.issued 2018
dc.identifier.citation Bera, S., & Mukhherjee, I. (2018). A solution framework for response surface-based multiple quality characteristics optimization. International Journal of Reliability, Quality and Safety Engineering, 25(5). en_US
dc.identifier.issn 1793-6446 (Online)
dc.identifier.uri https://doi.org/10.1142/S0218539318500250
dc.identifier.uri http://10.10.16.56:8080/xmlui/handle/123456789/465
dc.description.abstract A common problem generally encountered during manufacturing process improvement involves simultaneous optimization of multiple ‘quality characteristics’ or so-called ‘responses’ and determining the best process operating conditions. Such a problem is also referred to as ‘multiple response optimization (MRO) problem’. The presence of interaction between the responses calls for trade-off solution. The term ‘trade-off’ is an explicit compromised solution considering the bias and variability of the responses around the specified targets. The global exact solution in such types of nonlinear optimization problems is usually unknown, and various trade-off solution approaches (based on process response surface (RS) models or without using process RS models) had been proposed by researchers over the years. Considering the prevalent and preferred solution approaches, the scope of this paper is limited to RS-based solution approaches and similar closely related solution framework for MRO problems. This paper contributes by providing a detailed step-by-step RS-based MRO solution framework. The applicability and steps of the solution framework are also illustrated using a real life in-house pin-on-disc design of experiment study. A critical review on solution approaches with details on inherent characteristic features, assumptions, limitations, application potential in manufacturing and selection norms (indicative of the application potential) of suggested techniques/methods to be adopted for implementation of framework is also provided. To instigate research in this field, scopes for future work are also highlighted at the end. en_US
dc.language.iso en_US en_US
dc.publisher World Scientific en_US
dc.subject Quality characteristics en_US
dc.subject Multiple response optimization (MRO) en_US
dc.subject Response surface model en_US
dc.subject Manufacturing process en_US
dc.subject Optimization en_US
dc.subject Solution framework en_US
dc.subject IIM Ranchi en_US
dc.title A solution framework for response surface-based multiple quality characteristics optimization en_US
dc.type Article en_US
dc.volume 25 en_US
dc.issue 5 en_US


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