Enhancing Material Selection Efficiency: A Multi-Criteria Decision-Making Approach

DOI

10.2991/978-94-6463-406-8_15How to use a DOI?

Keywords

Continuous Stirred Tank Reactor (CSTR); Fractional Order PID Controllers; Multi-Criteria Decision Making (MCDM); Evolutionary Multi-Objective Optimization (EMO); Hybrid Methods

Abstract

The selection of materials plays a pivotal role in product design and development. With a plethora of materials available, making the right choice is crucial for a company’s reputation and profitability. This research aims to establish an efficient and systematic platform for optimal material selection while accommodating conflicting performance requirements. Our approach involves creating a hybrid decision support system to overcome the limitations of single multi-criteria decision-making (MCDM) models. We begin by determining the relative importance weights of attributes using the Shannon entropy algorithm. Subsequently, we integrate six different MCDM algorithms, including the weighted product method (WPM), simple additive weighting (SAW), additive ratio assessment (ARAS), new combinative distance-based assessment (CODAS), complex proportional assessment (COPRAS), and technique for order of preference by similarity to ideal solution (TOPSIS). We employ the COPELAND algorithm to generate a consensus and distinct ranking of material alternatives. The effectiveness of our integrated model is demonstrated through five diverse material selection scenarios. Results indicate that the developed model efficiently solves these problems, whereas individual MCDM algorithms fall short in some cases. Notably, COPRAS and WPM exhibit the highest correlation, making COPRAS the most efficient reference algorithm for material selection. This research highlights the importance of a comprehensive approach to material selection and suggests caution when using CODAS and TOPSIS for similar problems.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Aryo De Wibowo Muhammad Sidik
AU  - Ilyas Aminuddin
AU  - Cahya Laxa Eka Putra
AU  - Edwinanto Edwinanto
AU  - Apriditia Karisma
AU  - Yufriana Imamulhak
PY  - 2024
DA  - 2024/05/13
TI  - Enhancing Material Selection Efficiency: A Multi-Criteria Decision-Making Approach
BT  - Proceedings of the 2nd International Conference on Consumer Technology and Engineering Innovation (ICONTENTION 2023)
PB  - Atlantis Press
SP  - 80
EP  - 85
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-406-8_15
DO  - 10.2991/978-94-6463-406-8_15
ID  - MuhammadSidik2024
ER  -