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Multi-objective Optimization Approach to Product-planning in Quality Function Deployment Incorporated with Fuzzy-ANP

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Applications of Multi-Criteria and Game Theory Approaches

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

Technological innovations and changing customer trends brought by globalization has led tough competition among various industries throughout the globe. Their assiduous efforts to develop new product is crucial for survival. To overcome this problem and to develop a quality product that generates revenue, a dynamical multi-objective evolutionary algorithm(DMOEA) incorporated with quality function deployment (QFD) and fuzzy analytic network process (FANP) is proposed. The proposed approach considers goals such as new product development (NPD) time and cost, technological advancement, and manufacturability for selection of the most suitable product technical requirements (PTRs). A case study of software development is included to demonstrate the effectiveness of the proposed approach and the obtained results are discussed.

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Authors and Affiliations

  1. University of Arizona, Tucson, USA

    S. Mungle

  2. Indian Institute of Technology, Kharagpur, India

    S. Saurav & M. K. Tiwari

Authors
  1. S. Mungle
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  2. S. Saurav
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  3. M. K. Tiwari
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Corresponding author

Correspondence to S. Mungle .

Editor information

Editors and Affiliations

  1. LSIS, Aix-Marseille University, Marseille, France

    Lyes Benyoucef

  2. LSIS, CNRS, Marseille, France

    Jean-Claude Hennet

  3. Department if Industrial Engineering and, Indian Institute of Technology, Kharagpur, West Bengal, India

    Manoj Kumar Tiwari

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Mungle, S., Saurav, S., Tiwari, M.K. (2014). Multi-objective Optimization Approach to Product-planning in Quality Function Deployment Incorporated with Fuzzy-ANP. In: Benyoucef, L., Hennet, JC., Tiwari, M. (eds) Applications of Multi-Criteria and Game Theory Approaches. Springer Series in Advanced Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-5295-8_4

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  • DOI: https://doi.org/10.1007/978-1-4471-5295-8_4

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5294-1

  • Online ISBN: 978-1-4471-5295-8

  • eBook Packages: EngineeringEngineering (R0)

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