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Comparative analysis of different digitization systems and selection of best alternative

Author

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  • Syed Hammad Mian

    (King Saud University)

  • Abdulrahman Al-Ahmari

    (King Saud University
    King Saud University)

Abstract

Manufacturing industry plays a very significant role in the economic functioning of any country. In recent times, reverse engineering (RE) has become an integral part of manufacturing set-up owing to its numerous applications. The quality of RE product primarily depends on the quality of digitization i.e., part measurement. There is a diverse range of digitization devices which can be employed in RE. These machines have variability in terms of cost, accuracy, ease of use, accessibility, scanning time, etc. Therefore, the decision regarding the selection of a suitable device becomes important in a particular RE application. The decisions taken in the planning stage for RE can have a long lasting impact on the functionality, quality and the economics of components to be used by manufacturing industries. To accomplish the selection procedure, a comparative study of three digitization techniques has been carried out. The determination of an appropriate digitization system is basically a multi-criteria decision making (MCDM) problem. MCDM techniques are yet to be applied in the selection of digitization systems for RE. MCDM is one of the most widely used decision methodologies in business and engineering spheres. The aim of this work is to describe various MCDM methods in the selection of digitization systems for RE. This paper intends to employ combinations between different MCDM methods such as group eigenvalue method (GEM), analytic hierarchy process (AHP), entropy method, elimination and choice expressing reality (ELECTRE), technique for order of preference by similarity to ideal solution (TOPSIS) and simple additive weighing (SAW) method. In this work, GEM, AHP, Entropy methods has been used to elicit weights of various selection criteria, while TOPSIS, ELECTRE and SAW have been applied to rank the alternatives. A comparative analysis has also been performed to determine the efficacies of different approaches. The conclusion of the paper reveals the best digitization system as well as the characteristics of different MCDM methods and their suitability in RE application.

Suggested Citation

  • Syed Hammad Mian & Abdulrahman Al-Ahmari, 2019. "Comparative analysis of different digitization systems and selection of best alternative," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2039-2067, June.
  • Handle: RePEc:spr:joinma:v:30:y:2019:i:5:d:10.1007_s10845-017-1371-x
    DOI: 10.1007/s10845-017-1371-x
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    1. Matthew Martin, 1997. "Introduction," African Development Review, African Development Bank, vol. 9(1), pages 1-19.
    2. Bentes, Alexandre Veronese & Carneiro, Jorge & da Silva, Jorge Ferreira & Kimura, Herbert, 2012. "Multidimensional assessment of organizational performance: Integrating BSC and AHP," Journal of Business Research, Elsevier, vol. 65(12), pages 1790-1799.
    3. Al-Najjar, Basim & Alsyouf, Imad, 2003. "Selecting the most efficient maintenance approach using fuzzy multiple criteria decision making," International Journal of Production Economics, Elsevier, vol. 84(1), pages 85-100, April.
    4. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    5. Wade D. Cook & Moshe Kress, 1990. "A Data Envelopment Model for Aggregating Preference Rankings," Management Science, INFORMS, vol. 36(11), pages 1302-1310, November.
    6. Wolfgang Ossadnik & Stefanie Schinke & Ralf H. Kaspar, 2016. "Group Aggregation Techniques for Analytic Hierarchy Process and Analytic Network Process: A Comparative Analysis," Group Decision and Negotiation, Springer, vol. 25(2), pages 421-457, March.
    7. Forman, Ernest & Peniwati, Kirti, 1998. "Aggregating individual judgments and priorities with the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 108(1), pages 165-169, July.
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