Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection

Abstract The selection of the optimal conceptual design of any product is challenging due to the complexity of the customer’s behavior and the competitiveness existing among production companies. The present study introduces a hierarchical group decision-making algorithm supported on Axiomatic Design principles and Best-Worst Method under fuzzy environment. A case study on the selection of conceptual prototype design for a loudspeaker is analyzed using the proposed approach. By employing the proposed hybrid multi-criteria decision-making approach, an optimal conceptual prototype design is selected among four candidate loudspeaker designs considering the problem criteria including inclusive design elements and aesthetic factors as well as environmental and sustainability issues.

[1]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[2]  Yuriko Saito,et al.  Everyday Aesthetics , 2001 .

[3]  Milad Avazbeigi,et al.  A material selection methodology and expert system for sustainable product design , 2011 .

[4]  Joseph H. Saleh,et al.  Flexibility: a multi-disciplinary literature review and a research agenda for designing flexible engineering systems , 2009 .

[5]  M. Xie,et al.  Optimizing product design using the Kano model and QFD , 2004, 2004 IEEE International Engineering Management Conference (IEEE Cat. No.04CH37574).

[6]  Abteen Ijadi Maghsoodi,et al.  Selection of Waste Lubricant Oil Regenerative Technology Using Entropy-Weighted Risk-Based Fuzzy Axiomatic Design Approach , 2018, Informatica.

[7]  Mukesh Mohan Pandey,et al.  Evaluating the service quality of airports in Thailand using fuzzy multi-criteria decision making method , 2016 .

[8]  Panagiotis Platanitis,et al.  The Role of Counselling Psychology on Expatriate Adjustment in East Asia: A Systematic Review , 2017 .

[9]  Mark R. Gander,et al.  Historical Perspectives and Technology Overview of Loudspeakers for Sound Reinforcement , 2004 .

[10]  G. Candan,et al.  Solution of Material Selection Problem Using Fuzzy Axiomatic Design and DEMATEL Methods , 2017 .

[11]  C. Kahraman,et al.  Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic h , 2005 .

[12]  Zeshui Xu,et al.  An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making , 2016, Inf. Sci..

[13]  Xiangning Liao,et al.  Design of a Loudspeaker Array for Personal Audio in a Car Cabin , 2017 .

[14]  Hao-Tien Liu,et al.  An Integrated Product Design and Selection Approach Using Grey QFD and Grey TOPSIS Methods , 2015 .

[15]  Mauricio Camargo,et al.  Improving the idea selection process in creative workshops through contextualisation , 2016 .

[16]  Hongjun Zhang,et al.  Cognitive Best Worst Method for Multiattribute Decision-Making , 2017 .

[17]  Hacer Güner Gören,et al.  A new multi criteria decision making approach for medical imaging systems considering risk factors , 2015, Appl. Soft Comput..

[18]  Reuven Katz,et al.  Experimental method for measuring simplicity in mechanical design , 2018 .

[19]  Petrica C. Pop,et al.  Design and comparison of two evolutionary approaches for automated product design , 2016, Soft Comput..

[20]  Hacer Güner Gören,et al.  A New Fuzzy Multi-criteria Decision Making Approach: Extended Hierarchical Fuzzy Axiomatic Design Approach with Risk Factors , 2013, EWG-DSS.

[21]  Nam P. Suh,et al.  Axiomatic Design Theory for Systems , 1998 .

[22]  Ashkan Hafezalkotob,et al.  Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications , 2015 .

[23]  Francisco Herrera,et al.  Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule , 2018, IEEE Transactions on Fuzzy Systems.

[24]  Anant V. Khandekar,et al.  Small hydro-power plant project selection using fuzzy axiomatic design principles , 2015 .

[25]  Ali Mohaghar,et al.  Appraisal of Humanitarian Supply Chain Risks Using Best-Worst Method , 2017 .

[26]  Jamil Ahmad,et al.  A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information , 2016, Appl. Soft Comput..

[27]  Kampan Mukherjee,et al.  Analysis of product design characteristics for remanufacturing using Fuzzy AHP and Axiomatic Design , 2017 .

[28]  Jafar Rezaei,et al.  Quality assessment of airline baggage handling systems using SERVQUAL and BWM , 2018, Tourism Management.

[29]  Elizabeth Chang,et al.  ZBWM: The Z-number extension of Best Worst Method and its application for supplier development , 2018, Expert Syst. Appl..

[30]  C. Kahraman,et al.  Fuzzy multi-attribute equipment selection based on information axiom , 2005 .

[31]  C. Kahraman,et al.  Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach , 2005 .

[32]  J. Rezaei.  Best-worst multi-criteria decision-making method , 2015 .

[33]  Peggy Zwolinski,et al.  Product-service system design methodology: from the PSS architecture design to the products specifications , 2009 .

[34]  Walid Serrai,et al.  An efficient approach for Web service selection , 2016, 2016 IEEE Symposium on Computers and Communication (ISCC).

[35]  Mingsian R Bai,et al.  Optimal design of loudspeaker arrays for robust cross-talk cancellation using the Taguchi method and the genetic algorithm. , 2005, The Journal of the Acoustical Society of America.

[36]  Yejun Xu,et al.  A two-stage consensus method for large-scale multi-attribute group decision making with an application to earthquake shelter selection , 2018, Comput. Ind. Eng..

[37]  Ali Jahan,et al.  Selection of optimum design for conical segmented aluminum tubes as energy absorbers: Application of MULTIMOORA method , 2017 .

[38]  Lori Tavasszy,et al.  Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight , 2017 .

[39]  Yucheng Dong,et al.  A prospect theory-based method for fusing the individual preference-approval structures in group decision making , 2018, Comput. Ind. Eng..

[40]  Victor B. Kreng,et al.  The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection , 2010, Expert Syst. Appl..

[41]  Jingzheng Ren,et al.  Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory. , 2018, Chemosphere.

[42]  Haoran Zhao,et al.  Comprehensive benefit evaluation of eco-industrial parks by employing the best-worst method based on circular economy and sustainability , 2018, Environment, Development and Sustainability.

[43]  Mohammad Khalilzadeh,et al.  Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy , 2018 .

[44]  Shian-Jong Chuu,et al.  An investment evaluation of supply chain RFID technologies: A group decision-making model with multiple information sources , 2014, Knowl. Based Syst..

[45]  S. Vinodh,et al.  Rapid prototyping process selection using multi criteria decision making considering environmental criteria and its decision support system , 2016 .

[46]  Ashkan Hafezalkotob,et al.  A novel approach for combination of individual and group decisions based on fuzzy best-worst method , 2017, Appl. Soft Comput..

[47]  Geoff Easton,et al.  One case study is enough , 2010 .

[48]  Alireza Arab,et al.  Application of best-worst method in evaluation of medical tourism development strategy , 2018 .

[49]  Cengiz Kahraman,et al.  A new multi-attribute decision making method: Hierarchical fuzzy axiomatic design , 2009, Expert Syst. Appl..

[50]  J. Yang,et al.  Green Supplier Evaluation and Selection in Apparel Manufacturing Using a Fuzzy Multi-Criteria Decision-Making Approach , 2017 .

[51]  Changyong Liang,et al.  Generalized cross-entropy based group decision making with unknown expert and attribute weights under interval-valued intuitionistic fuzzy environment , 2015, Comput. Ind. Eng..

[52]  Ashkan Hafezalkotob,et al.  A decision support system for agricultural machines and equipment selection: A case study on olive harvester machines , 2018, Comput. Electron. Agric..

[53]  Cengiz Kahraman,et al.  Integrated Call Center Performance Measurement Using Hierarchical Intuitionistic Fuzzy Axiomatic Design , 2017, EUSFLAT/IWIFSGN.

[54]  Richard Herriott,et al.  Are Inclusive Designers Designing Inclusively? An Analysis of 66 Design Cases , 2013 .

[55]  Süleyman Çakir,et al.  An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design , 2018, J. Intell. Manuf..

[56]  Ming-Chyuan Lin,et al.  Using AHP and TOPSIS approaches in customer-driven product design process , 2008, Comput. Ind..

[57]  Floyd E. Toole,et al.  Loudspeakers and Rooms for Sound Reproduction-A Scientific Review , 2006 .

[58]  Kazem Askarifar,et al.  An investment development framework in Iran's seashores using TOPSIS and best-worst multi-criteria decision making methods , 2018 .

[59]  D. T. Matt.  Design of a scalable assembly system for product variety: a case study , 2013 .

[60]  Ashkan Hafezalkotob,et al.  Fuzzy entropy-weighted MULTIMOORA method for materials selection , 2016, J. Intell. Fuzzy Syst..

[61]  N. Suh.  Ergonomics, axiomatic design and complexity theory , 2007 .

[62]  Mark A. Poletti,et al.  Design of a Prototype Variable Directivity Loudspeaker for Improved Surround Sound Reproduction in Rooms , 2013 .

[63]  Glen Ballou,et al.  Handbook for Sound Engineers , 2002 .

[64]  Abteen Ijadi Maghsoodi,et al.  Identification and Evaluation of Construction Projects’ Critical Success Factors Employing Fuzzy-TOPSIS Approach , 2018 .

[65]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[66]  Ashkan Hafezalkotob,et al.  Risk-based material selection process supported on information theory: A case study on industrial gas turbine , 2017, Appl. Soft Comput..

[67]  Liya Wang,et al.  A methodology based on Fuzzy Extended Quality Function Deployment for determining optimal engineering characteristics in product-service system design , 2008, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics.

[68]  Nam P. Suh,et al.  Design of Thinking Design Machine , 1990 .

[69]  Guillermo Cortes-Robles,et al.  Lean Manufacturing in the Developing World , 2014 .

[70]  M. Kendall.  A NEW MEASURE OF RANK CORRELATION , 1938 .

[71]  Irem Y. Tumer,et al.  The Function-Based Design for Sustainability Method , 2017 .

[72]  Ali Kazemi,et al.  Identifying and prioritizing the factors of service experience in banks: A Best-Worst method , 2018 .

[73]  Jason Papathanasiou,et al.  Decision Support Systems III - Impact of Decision Support Systems for Global Environments , 2014, Lecture Notes in Business Information Processing.

[74]  Ali Siadat,et al.  Integrated product-process design to suggest appropriate manufacturing technology: a review , 2017 .

[75]  Sen Guo,et al.  Fuzzy best-worst multi-criteria decision-making method and its applications , 2017, Knowl. Based Syst..

[76]  Dilek Akbulut,et al.  On Context, Concepts and Research: An Approach in Basic Design , 2017 .

[77]  Hao-Tien Liu,et al.  Product design and selection using fuzzy QFD and fuzzy MCDM approaches , 2011 .

[78]  E. Zavadskas,et al.  The Interval-Valued Intuitionistic Fuzzy MULTIMOORA Method for Group Decision Making in Engineering , 2015 .

[79]  Eun-Sung Chung,et al.  Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method , 2014 .

[80]  Mohammad Khalilzadeh,et al.  CLUS-MCDA: A novel framework based on cluster analysis and multiple criteria decision theory in a supplier selection problem , 2018, Comput. Ind. Eng..

[81]  Qing Yang,et al.  Evaluation and Classification of Overseas Talents in China Based on the BWM for Intuitionistic Relations , 2016, Symmetry.

[82]  Thomas L. Saaty,et al.  Group Decision Making: Drawing Out and Reconciling Differences , 2007 .

[83]  J. Rezaei,et al.  Evaluation of external forces affecting supply chain sustainability in oil and gas industry using Best Worst Method , 2015, 2015 International Mediterranean Gas and Oil Conference (MedGO).

[84]  Cengiz Kahraman,et al.  Applications of axiomatic design principles: A literature review , 2010, Expert Syst. Appl..

[85]  Yixiong Feng,et al.  Anti-vibration optimization of the key components in a turbo-generator based on heterogeneous axiomatic design , 2017 .

[86]  J. Rezaei.  Best-worst multi-criteria decision-making method: Some properties and a linear model , 2016 .

[87]  M Bracale,et al.  Analytic Hierarchy Process (AHP) for Examining Healthcare Professionals’ Assessments of Risk Factors , 2010, Methods of Information in Medicine.

[88]  Shankar Chakraborty,et al.  Application of fuzzy axiomatic design principles for selection of non-traditional machining processes , 2016 .

[89]  Edmundas Kazimieras Zavadskas,et al.  Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara) , 2010 .

[90]  Xianyi Zeng,et al.  Intelligent decision support tools for multicriteria product design , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[91]  Zeki Ayag,et al.  An integrated approach to concept evaluation in a new product development , 2016, J. Intell. Manuf..