scholarly journals Maintenance Supplier Evaluation and Selection for Safe and Sustainable Production in the Chemical Industry: A Case Study

2019 ◽  
Vol 11 (6) ◽  
pp. 1533 ◽  
Author(s):  
Lizhong Tong ◽  
Zhongmin Pu ◽  
Jizheng Ma
Keyword(s):  
Sustainable Development ◽  
Chemical Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Sustainable Production ◽  
Equipment Maintenance ◽  
Safe Production ◽  
Maintenance Service

Chemical industry plays a pivotal role in the economy in every country. As chemical hazardous materials are usually characterized as inflammable, explosive, toxic, corrosive, and carcinogenic, if accidents happen in chemical company it can lead to irreversible environmental and health damage to the public. The chemical industry attaches great importance to safe production, technical professionalism, and service standardization. Nowadays, under the trend of equipment maintenance service outsourcing in chemical companies, the selection of maintenance suppliers with safe and sustainable records come first and foremost in the supplier selection process. However, these concerns from the chemical industry are currently inadequately addressed by most general supplier selection models. Therefore, this paper proposes an applicable methodology for selecting and evaluating equipment maintenance suppliers in the chemical industry, compatible with a safe and sustainable production context. To achieve the goal of “safe operation and sustainable development in the future”, we established an evaluation criteria framework for equipment maintenance suppliers by combining the general supplier selection criteria and safe production characteristics together. Eight main criteria and 24 sub-criteria based on market acceptance, resource conditions, and safe production were included. Then a fuzzy TOPSIS model was presented to select the best equipment maintenance service supplier. Finally, by analyzing a case in W petrochemical company, the empirical results indicate that the proposed framework is of great practical value to select and evaluate equipment maintenance suppliers for safety and sustainable development in the chemical industry.

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

Comparison of ANFIS and FAHP-FGP methods for supplier selection

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 474-489 ◽  
Author(s):  
Moloud sadat Asgari ◽  
Abbas Abbasi ◽  
Moslem Alimohamadlou
Keyword(s):  
Performance Measures ◽  
Supplier Selection ◽  
Mean Squared Error ◽  
Selection Process ◽  
Evaluation Criteria ◽  
Absolute Error ◽  
Global Market ◽  
Content Type ◽  
Squared Error ◽  
Fuzzy Delphi

Purpose – In the contemporary global market, supplier selection represents a crucial process for enhancing firms’ competitiveness. This is a multi-criteria decision-making problem that involves consideration of multiple criteria. Therefore this requires reliable methods to select the best suppliers. The purpose of this paper is to examine and propose appropriate method for selecting suppliers. Design/methodology/approach – ANFIS and fuzzy analytic hierarchy process-fuzzy goal programming (FAHP-FGP) are new methods for evaluating and selecting the best suppliers. These methods are used in this study for evaluating suppliers of dairy industries and the results obtained from methods are compared by performance measures such as Mean Squared Error, Root Mean Squared Error, Normalized Root Men Squared Error, Mean Absolute Error, Normalized Root Men Squared Error, Minimum Absolute Error and R2. Findings – The results indicate that the ANFIS method provides better performance compared to the FAHP-FGP method in terms of the selected suppliers scoring higher in all the performance measures. Practical implications – The proposed method could help companies select the best supplier, by avoiding the influence of personal judgment. Originality/value – This study uses the well-structured method of the fuzzy Delphi in order to determine the supplier evaluation criteria as well as the most recent ANFIS and FAHP-FGP methods for supplier selection. In addition, unlike most other studies, it performs the selection process among all available suppliers.

A TODIM-Based Decision Support Framework for G-Resilient Supplier Selection in Fuzzy Environment

2016 ◽  
Vol 33 (05) ◽  
pp. 1650033 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Support ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Selection Problems ◽  
Fuzzy Environment ◽  
Decision Support Framework ◽  
Application Potential

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. In this work subjectivity of evaluation criteria has been tackled by exploring fuzzy set theory. A dominance based approach has been conceptualized which is basically a simplified version of TODIM. Application potential of the proposed dominance based fuzzy decision making approach has been compared to that of fuzzy-TOPSIS, fuzzy-VIKOR and also fuzzy-TODIM. The concept of a unique performance index, i.e. “g-resilient” index has been introduced here to help in assessing suppliers’ performance and thereby selecting the best candidate. The work has also been extended to identify the areas in which suppliers are lagging; these seek further improvement towards g-resilient suppliers’ performance to be boosted up to the desired level.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

scholarly journals An Integrated Interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

2021 ◽  
Author(s):  
Sema Kayapinar Kaya ◽  
Ejder Aycin
Keyword(s):  
Supply Chain ◽  
Industry 4.0 ◽  
Supplier Selection ◽  
Business Models ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Dynamic Structure ◽  
Interval Type

Abstract Supply chain has a very extensive and dynamic structure that incorporates new business models, new customer expectations, market searches and technological developments. With the introduction of Industry 4.0 into supply chain, a rapid and intensive process of digitalization begin to transform every step of supply chain. Supply chain selection is one of the essential decisions in reducing the supply chain cost and improving overall quality of product and services. With the implication of digital technologies and Industry 4.0 on supply chain, the supplier selection process has been significantly changed during the recent years. Companies are willing to need new requirements for their own suppliers in accordance with Industry 4.0 implementations and technologies. This paper aims to identify key criteria to Industry 4.0 technologies and evaluate them to select the right suppliers selection in the era of Industry 4.0 Within the scope of this study attempts to develop an integrated Interval Type 2 Fuzzy AHP and GOPRAS-G methodology to select the appropriate supplier in the face of Industry 4.0 implementations. For this purpose, Interval Type 2 Fuzzy AHP was employed to weight the supplier evaluation criteria and then, Grey COPRAS method has been applied to prioritize suppliers. This paper is to provide practitioners and researchers with insight into how Industry 4.0 strategies influence on supplier selection.

scholarly journals Evaluation of Supplier Selection in Manufacturing Industries using Grey Relational Analysis- A Case Study

2014 ◽  
pp. 104-109
Author(s):  
Veera Bahadur Aravind Reddy K ◽  
Saras Chandra T Reddy ◽  
G. Rajyalakshmi
Keyword(s):  
Grey Relational Analysis ◽  
Supplier Selection ◽  
Selection Process ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Objective Evaluation ◽  
Supply Contract ◽  
Relational Analysis ◽  
Order Quantities ◽  
Grey Relational

Selection of supplier is one of the most critical activities performed by the organizations because of its strategic importance. Over the years a number of quantitative approaches have been applied to supplier selection problems. The selection process is commonly based on their previous performance records, so the ranking determines which supplier will get their supply contract. However a survey on current evaluation methods shows that they are all less objective and lack accurate data processing. These evaluation criteria often conflict, however and it is frequently impossible to find a supplier that excels in all areas. In addition some of the criteria are quantitative and some are qualitative. Thus a methodology is needed that can capture both subjective and objective evaluation measures. In this paper, we presented AHP and Grey Relational Analysis to establish a complete and accurate evaluation model for selecting suppliers based on multiple criteria and places the order quantities among them for a spinning industry

scholarly journals PEMILIHAN SUPPLIER BATA RINGAN SEBAGAI BAHAN BAKU BANGUNAN DENGAN METODE AHP DAN TOPSIS DI PT. CPS

JUMINTEN ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 96-107
Author(s):  
Radifan Dimasyqi ◽  
Dira Ernawati ◽  
Rusindiyanto Rusindiyanto
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Evaluation Criteria ◽  
Raw Material ◽  
Services Sector ◽  
Order Preference ◽  
Aerated Concrete ◽  
Hierarchy Process ◽  
Construction Services ◽  
A Company

Choosing a supplier is a strategic activity, especially if the supplier will supply items that are used for a long period. PT. CPS is a company engaged in the construction services sector which also carries out procurement process activities, including the supplier selection process. In carrying out the building production process, PT. CPS requires the main raw material, namely light brick (Autoclaved Aerated Concrete). PT. CPS does not yet have a main supplier of light bricks AAC, and supplier selection is done subjectively and based on the lowest price without making certain calculations. This resulted in several problems such as miss communication during the process of ordering materials, and delays in delivery that made the company have to order from other suppliers. This study aims to calculate the criteria weight for light brick suppliers and select the best light brick supplier based on the weight criteria specified by PT. CPS. The process of making supplier evaluation criteria is carried out using the Analytical Hierarchy Process (AHP) method and ranking suppliers with the Technique Method for Order Preference by Similarity to Ideal Solution (TOPSIS). From the research results obtained weighting of 5 criteria, namely the criteria of price, quality, delivery, reputation and position in industry, and communication system by placing the price criterion as the criterion with the greatest weight, which was 0.56165. The supplier ranking results obtained the best light brick supplier in the first position, namely PT. Sinar Indogreen Kencana with a Preference Value of 0.76858, the second position of PT. Superior Prima Sukses with a Preference Value of 0.49827, and the third position is PT. Viccon Modern Industry with a Preference Value of 0.49448.

scholarly journals An Integrated Methodology for Supplier Selection under the Presence of Vagueness: A Case in Banking Sector, Turkey

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Semih Onut ◽  
Suleyman Tosun
Keyword(s):  
Supplier Selection ◽  
Quality Function Deployment ◽  
Banking Sector ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Analytic Network Process ◽  
Second Phase ◽  
House Of Quality ◽  
Quality Model ◽  
Technical Requirements

A supplier selection process mainly involves evaluation of different alternative suppliers based on different criteria. This process can be handled as a combination of the customer needs and the technical requirements. Also customers can be considered as the companies to purchase the suppliers’ technical expertise. Hence, this kind of relationship can be analyzed as a house of quality model typical of quality function deployment (QFD). This paper develops a supplier evaluation approach based on the analytic network process (ANP), QFD, and the technique for order performance by similarity to ideal solution (TOPSIS) methods to help an investment bank in Turkey as a real world application. Fuzzy logic is used to capture the vagueness in people’s verbal assessments. In the first phase, matrices used to define the importance of the supplier selection criteria and the technical requirements are calculated with the fuzzy ANP method. The technical requirements and the criteria are combined in the house of quality to evaluate the relationship between them. In the second phase, fuzzy TOPSIS is used to rank the suppliers based on the weighted criteria obtained from the first phase. The study was followed by the sensitivity analysis of the results.

scholarly journals A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

2020 ◽  
Vol 18 (3) ◽  
pp. 375 ◽  
Author(s):  
Krishnapuram Ravi Ramakrishnan ◽  
Shankar Chakraborty
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Cloud Model ◽  
Evaluation Criteria ◽  
Human Cognition ◽  
Green Supplier Selection ◽  
Adopted Model ◽  
Qualitative Attribute ◽  
Green Suppliers ◽  
Topsis Model

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection.

scholarly journals SUPPLIER SELECTION PROCESS IN DAIRY INDUSTRY USING FUZZY-TOPSIS METHOD

2021 ◽  
Vol 4 (1) ◽  
pp. 82-98
Author(s):  
Tarik Cakar ◽  
◽  
Burcu Çavuş ◽  
Keyword(s):  
Supplier Selection ◽  
Selection Criteria ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Fuzzy Environment ◽  
Quality Of Products ◽  
Topsis Technique ◽  
The Right

Supplier selection is one of the most critical processes within the purchasing function. Choosing the right supplier makes a strategic difference to an organization’s ability to reduce costs and improve the quality of products by helping to select the most suitable supplier. Sütaş Dairy Company, which is entered to Macedonia market in 2012. In the dairy company, there is only one purchasing manager who selects the farmers. Importance weights of criteria are determined using his reference, and also the alternatives are evaluated according to each criterion. The most important criteria are product and other costs, the price is also playing an important role, but due to the small marketplace of Macedonia, the prices are almost the same in every region. To select the dairy supplier in Macedonia, Fuzzy-TOPSIS technique is used. The main goal of using fuzzy logic in this study is to help decision-makers for identifying the importance of selection criteria and rank possible suppliers easily. Since the supplier selection process is a Multi-Criteria Decision Making (MCDM) problem, after identify the weights and rankings in a fuzzy environment, TOPSIS algorithm has been used in the rest of the problem. Finally, fuzzy TOPSIS methodology has been implemented successfully, and its result pointed out the most suitable suppliers.

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