Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry

Abstract

To be able to compete in the domestic plastic industry, small and medium-sized enterprises producing plastic need to proactively find the supply of raw materials, avoiding shortages like in the previous years. Purchasing is extremely important and will create a competitive advantage with competitors in the market, so finding suppliers will determine the success in the later stages of the production chain. With the development of the current information system, selection and evaluation have become important in order to achieve effective decision-making through optimal options. In this study, the authors provide a new approach for decision-makers in evaluating and selecting suppliers, which is formulated based on the supply chain operation reference (SCOR) model, fuzzy analytic network process (FANP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The contribution of this research is to propose a multicriteria decision-making model (MCDM) for raw material supplier selection in the plastic industry. This research also provided a useful guideline for supplier selection in other industry.Mathematics 2019, 7, 981 2 of 17 avoiding subjective factors such as human factors, documents, relationships, etc., that is vague and incomplete in making decisions is crucial [4]. Moreover, most previous studies have assumed that each criterion cluster in the method they use has equal weight to solve the problem with a weighted hyper matrix [5,6]. Therefore, previous studies have not exploited the advantages and disadvantages of the models or methods they have applied. With the development of the current information system, selection and evaluation have become important to achieve effective decision-making through optimal options [7].According to the Vietnam Plastics Association (VPA), each year, Vietnam's plastic industry needs about 5 million tons of plastic materials and hundreds of additives, while domestic production can only supply about 900,000 tons of raw materials/year. According to the data from the General Department of Customs, Vietnam must import 4.54 million tons of plastic materials worth nearly $6.3 billion, up 15.7% over the same period.The reliance on imported plastic materials not only causes businesses to stagnate capital because of stockpiling raw materials, but also has potential risks on exchange rates and world oil prices. Every time the VND/USD exchange rate increases, input costs of plastic businesses will increase accordingly.The primary goal of this research is to propose a multi criteria decision-making model (MCDM) for raw material supplier selection in plastic industry and also provide a useful guideline for supplier selection in other industry.In this study, the proposed model provides a new approach for decision-makers in evaluating and selecting suppliers, which is formulated based on the supply chain operation reference (SCOR) model, fuzzy analytic network process (FANP), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).This paper provides research background, moti...

An Integrated Approach for Fuzzy-Dynamic Multi-Attribute Group Decision Making With Application in Renewable Energy

“…As far as we know, none of the outranking methods available in the literature integrate ELECTRE and VIKOR under uncertainty and dynamic perspectives. The advantages of this integration have been previously discussed [34], [44], [45]. Some of them are accurately proposing a compromise solution, identifying the best alternative, providing a complete ranking of alternatives, offering different ranking orders based on different DM strategies, describing uncertainty, and incorporating it into the problem.…”

“…Considering that this method is conceived to tackle real-world scenarios, it is designed to be easy to understand and easy to replicate. This design sets it apart from other available methods [22], [34], [44], [45], [60]. Although an application for a renewable energy indicator ranking was provided, future work will seek to apply it to investigate problems in areas such finance, artificial intelligence, and the spread of infections.…”

“…However, VIKOR has limitations when dealing with real-world circumstances. For instance, the values of alternative performance related to a group of criteria should be defined as fixed numbers, which is also an important limitation when attempting to accurately describe complex problems [44].…”

“…Due to space limitations, we have referenced only the research relevant to our work, and a small number of studies have been omitted. Exhaustive literature reviews of fuzzy sets, theory, and methods are available in [34], [44], [45]. As far as we know, an integration of ELECTRE I and VIKOR under a dynamic IFS perspective does not exist in the literature yet.…”

A Proposal of an Adaptive Neuro-Fuzzy Inference System for Modeling Experimental Data in Manufacturing Engineering

“…Some other studies are those of Cuka and Kim [8] that developed a fuzzy inference system for tool condition monitoring in end-milling operations and Joshi et al [9] who analyzed surface roughness and material removal rate (MRR) of Inconel 800HT, when machined with copper electrode on electrical discharge machining (EDM). On the other hand, Wang et al [10] employed a fuzzy multicriteria decision-making model (MCDM) for raw material supplier selection in the plastic industry. Likewise, Lin et al [11] applied fuzzy collaborative intelligence approach for fall detection in four existing smart technology applications and a methodology for obtaining technological mean roughness (Ra) for the EDM process, Alarifi et al [42] employed genetic algorithms and particle swarm optimization to determine the parameters of an ANFIS model to predict the thermo-physical properties of Al 2 O 3 -MWCNT/thermal oil hybrid nanofluid and an analysis of the PSO implementation in designing parameters of manufacturing processes as well as a benchmark with other optimization techniques can be found in the review study of Sibalija [43].…”