Development of a Spreadsheet DSS for Multi-Response Taguchi Parameter Optimization Problems Using the TOPSIS, VIKOR, and GRA Methods

This paper presents a spreadsheet-based decision support system (DSS) for any parameter optimization problem, in the small- and medium-sized enterprises to help the managers to make better decisions. Microsoft Excel is used as a DSS development platform. The DSS application requires the quality characteristics and the level of parameters affecting the problem. The proposed system considers three multi-criteria decision-making methods: TOPSIS, VIKOR and GRA. These methods are integrated into the Taguchi method to convert the multi-response optimization problem to a single-response problem. The DSS suggests proper Taguchi experimental designs and provides the decision maker with an opportunity to use different metrics and to validate the experimental results. Several issues and an application are provided for illustrative purposes. The proposed DSS is tested on a case study (the performance of the mixed integer programming (MIP) formulation solver) and the results highlight that the system is capable of offering satisfactory outcomes. Using such a quick and flexible DSS might help to reduce the daily workload of the decision makers. The different metrics used for the response variables which results with the different parameter combination. Using the optimal parameter combination of TOPSIS (come to the fore in case MinBest metric used), the MIP formulation solver gives the best integer objective function value of 609 and a GAP value of 1.93%, both of which are less than the values obtained using the other methods. Using the optimal parameter combination of GRA (come to the fore in case OptBest metric used), the MIP formulation gives a best integer objective function value of 632 and a GAP value of 6.52%, both of which are less than the values obtained by using the other methods.

[1]  M. R. Toroghinejad,et al.  Multi-response optimization on the annealing of accumulative roll bonded monolithic Ti and Ti–SiCp composites , 2015 .

[2]  Arif Gok,et al.  A new approach to minimization of the surface roughness and cutting force via fuzzy TOPSIS, multi-objective grey design and RSA , 2015 .

[3]  Jaroslav Ramík,et al.  Microsoft Excel as a Tool for Solving Multicriteria Decision Problems , 2014, KES.

[4]  J. Paulo Davim,et al.  Selection of optimal MQL and cutting conditions for enhancing machinability in turning of brass , 2008 .

[5]  Şefika Kasman,et al.  Impact of parameters on the process response: A Taguchi orthogonal analysis for laser engraving , 2013 .

[6]  Quirico Semeraro,et al.  Critical operating conditions for assemblies with parameter-dependent dimensions , 2013 .

[7]  Yi Peng,et al.  A Group Decision Making Model for Integrating Heterogeneous Information , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[8]  Lee-Ing Tong,et al.  Optimization of multi-response processes using the VIKOR method , 2007 .

[9]  Lin Li,et al.  Multi-objective optimization of milling parameters – the trade-offs between energy, production rate and cutting quality , 2013 .

[10]  V. Anandakrishnan,et al.  Experimental investigation and performance analysis of cemented carbide inserts of different geometries using Taguchi based grey relational analysis , 2014 .

[11]  Jianjun Wang,et al.  A new Bayesian approach to multi-response surface optimization integrating loss function with posterior probability , 2016, Eur. J. Oper. Res..

[12]  P. Jayaraman,et al.  Multi-response Optimization of Machining Parameters of Turning AA6063 T6 Aluminium Alloy using Grey Relational Analysis in Taguchi Method☆ , 2014 .

[13]  Qiping Shen,et al.  Design of spatial decision support systems for property professionals using MapObjects and Excel , 2004 .

[14]  N. C. Hwang,et al.  Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling , 2009 .

[15]  Omar Ahmed Mohamed,et al.  Mathematical modeling and FDM process parameters optimization using response surface methodology based on Q-optimal design , 2016 .

[16]  C. Raju,et al.  Application of a hybrid optimization technique in a multiple sheet single point incremental forming process , 2016 .

[17]  Claudio Barbieri Cunha,et al.  A spreadsheet-based optimization model for the integrated problem of producing and distributing a major weekly newsmagazine , 2007, Eur. J. Oper. Res..

[18]  Ergün Eraslan,et al.  A new usability evaluation approach for touch screen mobile devices , 2016 .

[19]  Ravindra K. Ahuja,et al.  Spreadsheet-Based Decision Support Systems , 2008 .

[20]  Temel Öncan,et al.  A comparative analysis of several asymmetric traveling salesman problem formulations , 2009, Comput. Oper. Res..

[21]  Kadir Gok,et al.  Optimization of processing parameters of a developed new driller system for orthopedic surgery applications using Taguchi method , 2014, The International Journal of Advanced Manufacturing Technology.

[22]  R. N. Rai,et al.  Effect of in-situ processing parameters on microstructure and mechanical properties of TiC particulate reinforced Al–4.5Cu alloy MMC fabricated by stir-casting technique – Optimization using grey based differential evolution algorithm , 2016 .

[23]  B. C. Routara,et al.  An approach for optimization the process parameter by using TOPSIS Method of Al–24%SiC metal matrix composite during EDM , 2015 .

[24]  Yang Chen,et al.  Pairwise comparison matrix in multiple criteria decision making , 2016 .

[25]  Don P Clausing.  Operating Window: An Engineering Measure for Robustness , 2004, Technometrics.

[26]  Rupesh Kumar Pandey,et al.  Optimization of bone drilling parameters using grey-based fuzzy algorithm , 2014 .

[27]  Rupesh Kumar Pandey,et al.  Multi-performance optimization of bone drilling using Taguchi method based on membership function , 2015 .

[28]  Josef Jablonsky,et al.  MS Excel based Software Support Tools for Decision Problems with Multiple Criteria , 2014 .

[29]  Taho Yang,et al.  The use of grey relational analysis in solving multiple attribute decision-making problems , 2008, Comput. Ind. Eng..

[30]  George J. Besseris,et al.  Concurrent multi-response optimization of austenitic stainless steel surface roughness driven by embedded lean and green indicators , 2014 .

[31]  Kevin P. Scheibe,et al.  Fashioning fair foursomes for the fairway (using a spreadsheet-based DSS as the driver) , 2008, Decis. Support Syst..

[32]  J. Paulo Davim,et al.  Taguchi multiple-performance characteristics optimization in drilling of medium density fibreboard (MDF) to minimize delamination using utility concept , 2008 .

[33]  C. Herrmann,et al.  Determining optimal process parameters to increase the eco-efficiency of grinding processes , 2014 .

[34]  Maghsoud Amiri,et al.  Synergy of ICA and MCDM for multi‐response optimisation problems , 2013 .

[35]  S. Ramesh,et al.  Measurement and optimization of surface roughness and tool wear via grey relational analysis, TOPSIS and RSA techniques , 2016 .

[36]  Yusuf Tansel Iç,et al.  Hybridizing a fuzzy multi-response Taguchi optimization algorithm with artificial neural networks to solve standard ready-mixed concrete optimization problems , 2016, Int. J. Comput. Intell. Syst..

[37]  T. Muthuramalingam,et al.  Application of Taguchi-grey multi responses optimization on process parameters in electro erosion , 2014 .

[38]  Biqing Huang,et al.  Cloud manufacturing service platform for small- and medium-sized enterprises , 2012, The International Journal of Advanced Manufacturing Technology.

[39]  Ümit Sami Sakalli,et al.  An optimization approach for brass casting blending problem under aletory and epistemic uncertainties , 2011 .

[40]  Yusuf Tansel İç,et al.  A TOPSIS-based Taguchi optimization to determine optimal mixture proportions of the high strength self-compacting concrete , 2013 .

[41]  Mihir Kumar Sutar,et al.  Multi-objective Optimization of the EMS Processed IC by Grey-fuzzy Method , 2015 .

[42]  Shankar Chakraborty,et al.  Applications of the MOORA method for decision making in manufacturing environment , 2011 .

[43]  K. S. Amirthagadeswaran,et al.  Experimental investigation of machinability characteristics and multi-response optimization of end milling in aluminium composites using RSM based grey relational analysis , 2017 .

[44]  Thong Ngee Goh,et al.  Adapting the Robust Design Methodology to support sustainable product development , 2014 .

[45]  Kumar Abhishek,et al.  Application of NSGA II for Optimization of Multi-performance Characteristics During Machining of GFRP (epoxy) Composites☆ , 2015 .

[46]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[47]  Mohsen Ayaz,et al.  Predicting of mechanical properties of PP/LLDPE/TiO2 nano-composites by response surface methodology , 2016 .

[48]  R. Ramakrishnan,et al.  Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process , 2008 .

[49]  Murat Sarıkaya,et al.  Multi-response optimization of minimum quantity lubrication parameters using Taguchi-based grey relational analysis in turning of difficult-to-cut alloy Haynes 25 , 2015 .

[50]  T. Rajmohan,et al.  Optimization of machining parameters in drilling hybrid aluminium metal matrix composites , 2012 .

[51]  T. Rajmohan,et al.  Optimization of machining parameters in turning of Al−SiC−Gr hybrid metal matrix composites using grey-fuzzy algorithm , 2014 .

[52]  Omar Ahmed Mohamed,et al.  Optimization of fused deposition modeling process parameters for dimensional accuracy using I-optimality criterion , 2016 .

[53]  Vijay Kamble,et al.  Geometrical optimization of strain gauge force transducer using GRA method , 2017 .

[54]  F. Altiparmak,et al.  The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach , 2012 .

[55]  Yusuf Tansel İç,et al.  MOORA-based Taguchi optimisation for improving product or process quality , 2013 .

[56]  Rajesh Kumar Bhushan,et al.  Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites , 2013 .

[57]  Peter Krajnik,et al.  Robust design of flank milling parameters based on grey-Taguchi method , 2007 .

[58]  Yusuf Tansel İç,et al.  Multi-response simulation optimization approach for the performance optimization of an Alarm Monitoring Center , 2014 .

[59]  Fernando P. Bernardo,et al.  Robust optimization framework for process parameter and tolerance design , 1998 .

[60]  Lee-Ing Tong,et al.  Optimization of a multi-response problem in Taguchi's dynamic system , 2005, Comput. Ind. Eng..

[61]  B. Vijaya Ramnath,et al.  A grey-fuzzy modeling for evaluating surface roughness and material removal rate of coated end milling insert , 2016 .

[62]  Andrzej Perec.  Abrasive Suspension Water Jet Cutting Optimization Using Orthogonal Array Design , 2016 .

[63]  Ümit Sami Sakalli,et al.  A spreadsheet-based decision support tool for blending problems in brass casting industry , 2009, Comput. Ind. Eng..

[64]  Suhas S. Joshi,et al.  Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA) , 2011 .

[65]  Reza Baradaran Kazemzadeh,et al.  A novel approach for optimization of correlated multiple responses based on desirability function and fuzzy logics , 2012, Neurocomputing.

[66]  Indrajit Mukherjee,et al.  Production , Manufacturing and Logistics A multistage and multiple response optimization approach for serial manufacturing system , 2015 .

[67]  Arif Gok,et al.  Cutting parameter and tool path style effects on cutting force and tool deflection in machining of convex and concave inclined surfaces , 2013 .

[68]  Valentinas Podvezko,et al.  Multicriteria graphical‐analytical evaluation of the financial state of construction enterprises , 2008 .

[69]  Konstantin E. Samouylov,et al.  Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions , 2019, Knowl. Based Syst..

[70]  An-Yuan Chang,et al.  Analysis model of the sustainability development of manufacturing small and medium- sized enterprises in Taiwan , 2019, Journal of Cleaner Production.

[71]  K. Y. Benyounis,et al.  Multi-response optimization of CO2 laser-welding process of austenitic stainless steel , 2008 .