Journals / International Journal of Intelligent Systems and Applications in Engineering / 2017 / Cilt: 5 - Sayı: 3

A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

Pages
124–131
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The developed model can be used by engineers and operators in manufacturing environment

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Multi criteria decision making models (MCDM) are extensively used in material and process selection in engineering.
📊
Key Findings & Data:In this study, a novel hybrid decision making model is developed.
💡
Conclusion & Impact:The developed model can be used by engineers and operators in manufacturing environment
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Multi criteria decision making models (MCDM) are extensively used in material and process selection in engineering. In this study, a novel hybrid decision making model is developed. Best-Worst method (BWM) is hybridized with TOPSIS, Grey Relational Analysis (GRA) and Weighted Sum Approach (WSA). Developed hybrid models produce similar results in different weight value of decision makers so they are combined. The model is tested in a turning operation and an optimization study is conducted by using Taguchi experimental design. The developed model can be used by engineers and operators in manufacturing environment

🔖

Cite This Article

SOFUOĞLU, M. A., ORAK, S. (2017). A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 5 - Sayı: 3, 124–131. https://ajindex.com/articles/189613

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (1)

  1. . Davim, J. Paulo. (2010). Surface Integrity in Machining. Springer Science & Business Media. [2]. Mardani, A., Jusoh, A., MD Nor K., Khalifah Z., Zakwan, N. and Valipour A., (2015) Multiple criteria decisionmaking techniques and their applications – a review of the literature from 2000 to 2014, Economic ResearchEkonomskaIstraživanja, 28:1, 516-571, DOI: 10.1080/1331677X.2015.1075139 [3]. Jahan, A., Mustapha, F., Ismail, M. Y., Sapuan, S., &Bahraminasab, M. (2011). A comprehensive VIKOR method for material selection. Materials & Design, 32, 1215–1221. [4]. Cavallini, C., Giorgetti, A., Citti, P., &Nicolaie, F. (2013). Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm. Materials & Design, 47, 27–34. [5]. Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2009). Selection of materials using compromise ranking and outranking methods. Materials & Design, 30, 4043–4053. [6]. Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials & Design, 32, 851– 860. [7]. Shanian, A., Milani, A. S., Carson, C., &Abeyaratne, R. C. (2008). A new application of ELECTRE III and revised Simos’ procedure for group material selection under weighting uncertainty. Knowledge-Based Systems, 21, 709–720. [8]. Mayyas, A., Shen, Q., Mayyas, A., Abdelhamid, M., Shan, D., Qattawi, A., & Omar, M., (2011).Using Quality Function Deployment and Analytical Hierarchy Process for material selection of Body-In-White. Materials & Design, 32, 2771–2782. [9]. Streimikiene, D., Balezentis, T., Krisciukaitienė, I., &Balezentis, A. (2012). Prioritizing sustainable electricity production technologies: MCDM approach. Renewable and Sustainable Energy Reviews, 16, 3302–3311. [10]. Chang, A.-Y., Hu, K.-J., & Hong, Y.-L. (2013). An ISMANP approach to identifying key agilefactors in launching a new product into mass production. International Journal of Production Research, 51, 582–597. [11]. Bagočius, V., Zavadskas, E. K., &Turskis, Z. (2013). Multi-criteria selection of a deep-water port in Klaipeda. Procedia Engineering, 57, 144–148. [12]. Jana, T. K., Bairagi, B., Paul, S., Sarkar, B., &Saha, J. (2013). Dynamic schedule execution in an agent based holonic manufacturing system. Journal of Manufacturing Systems, 32, 801– 816. [13]. Tzeng, G.-H., & Huang, C.-Y. (2012). Combined DEMATEL technique with hybrid MCDM methods for creating th