Optimal machine tools selection using quality function deployment and fuzzy multiple objective decision making approach


JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, vol.24, no.1, pp.163-174, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 1
  • Publication Date: 2013
  • Doi Number: 10.3233/ifs-2012-0542
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.163-174
  • Keywords: Machine tool selection, quality function deployment, fuzzy regression, decision making, GOAL PROGRAMMING-MODEL, LINEAR-REGRESSION, INTEGRATED APPROACH, SUPPORT-SYSTEM, AHP, CELL
  • Karadeniz Technical University Affiliated: Yes


Machine tool selection is one of the most important strategic decisions in production planning because it directly affects production rates, costs, accuracy, flexibility, and design. Improperly selected machines can negatively affect the manufacturer's overall manufacturing capability. Considering the significance of machine tool selection to production planning, there is a great need for a systematic decision-aid tool which can optimize the machine tool selection decision in the presence of wide-ranging alternatives. In response to such a need, we propose a hybrid decision-aid tool that combines the strengths of quality function deployment (QFD), fuzzy linear regression, and zero-one goal programming. QFD is utilized for incorporating the customer service needs into machine tool selection by examining the causal relationships between customer needs and technical tool requirements. Fuzzy linear regression is then used to determine such causal relationships which cannot be expressed in clear and precise manners. Finally, zero-one goal programming (ZOGP) is used to select the most desirable machine tool alternative. To verify the usefulness and practicality of the proposed method, we applied it to solve actual machine tool selection problem encountered by a steel automobile part manufacturer in Ankara, Turkey.