Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.

Introduction to quality engineering. designing quality into products a

https://findresearcher.sdu.dk:8443/ws/files/135384983/Supply_chain_network_design_under_uncertainty.pdf

Supply chain network design under uncertainty: A comprehensive review and future research directions

Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.

/pdf/literature-review-on-disruption-recovery-in-the-supply-chain-1d8xpyuamg.pdf

Literature review on disruption recovery in the supply chain

In this paper, a new multi-criteria problem solving method—the Full Consistency Method (FUCOM)—is proposed. The model implies the definition of two groups of constraints that need to satisfy the optimal values of weight coefficients. The first group of constraints is the condition that the relations of the weight coefficients of criteria should be equal to the comparative priorities of the criteria. The second group of constraints is defined on the basis of the conditions of mathematical transitivity. After defining the constraints and solving the model, in addition to optimal weight values, a deviation from full consistency (DFC) is obtained. The degree of DFC is the deviation value of the obtained weight coefficients from the estimated comparative priorities of the criteria. In addition, DFC is also the reliability confirmation of the obtained weights of criteria. In order to illustrate the proposed model and evaluate its performance, FUCOM was tested on several numerical examples from the literature. The model validation was performed by comparing it with the other subjective models (the Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)), based on the pairwise comparisons of the criteria and the validation of the results by using DFC. The results show that FUCOM provides better results than the BWM and AHP methods, when the relation between consistency and the required number of the comparisons of the criteria are taken into consideration. The main advantages of FUCOM in relation to the existing multi-criteria decision-making (MCDM) methods are as follows: (1) a significantly smaller number of pairwise comparisons (only n − 1), (2) a consistent pairwise comparison of criteria, and (3) the calculation of the reliable values of criteria weight coefficients, which contribute to rational judgment.

https://www.mdpi.com/2073-8994/10/9/393/pdf

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM)

Viability of a product or service in the market depends upon the satisfaction that it can extend to its customers through quality. Quality function deployment (QFD) is a tool that gathers voice of customer (VoC) and inducting the expected features in the final product. It is also desirable that the practitioners of QFD must extend due importance to latent expectations of the customers, which in turn may fulfill overall customer satisfaction for a product or service. Kano et al. (J Jpn Soc Qual Control, 14:39–48, 1984; 1996) and Kano (2001) have suggested a method to identify the different categories of requirements through customer responses. Based on the QFD and Kano model analysis, a function has been proposed to adjust the traditional improvement ratio (Tan and Shen, Total Qual Manag 11:1141–1151, 2000) for each product or service attribute to recognize the importance of a attribute, which can be helpful in developing a product or service in such a manner that maximum customer satisfaction can be achieved. The proposed methodology has been illustrated using customer survey data.

Integration of Kano’s Model into quality function deployment (QFD)

Nowadays, new products have been introduced in the market at an ever increasing pace due to rapid technology advancement. Consequently, products are becoming outdated and discarded faster than ever before. Since the demand for new solutions to economically deal with such outdated products begun to rise, the disassembly line has emerged as a viable solution to this problem. The disassembly line has been considered as a viable choice for automated disassembly of returned products. The problem of sequence generation in disassembly is complex due to its NP-Hard nature and therefore the heuristically solutions are most preferable for these types of problems. In this paper, a heuristic has been proposed to assign the disassembly tasks/parts to the work stations under its precedence constraints. It incorporates Fuzzy analytic hierarchy process (Fuzzy AHP) and PROMETHEE method for the selection of tasks for assignment to the disassembly line. The Fuzzy AHP has been used to find the relative importance of each cri...

A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems

Facility location decisions play a vital role in the strategic design of the global supply chain. Global supply chains are vulnerable towards different types of risks factor that causes disturbance in the allocation of certain goods at the required place and time, and with the required quality and quantity. This paper presents a model of the multi-stage global supply chain network problem incorporating a set of risk factors (such as: late shipment, exchange rates, quality problems, logistics and transportation breakdown, and production risks), their expected values and probability of their occurrence, and associated additional cost. Different scenarios are considered to demonstrate the applicability of the model. Optimal decisions regarding the facility locations and inter-echelon quantity flows in the global supply chain are based on initial information for the risk factors. Further, if any change in the expected value of risk factor has occurred, the inter-echelons shifting take place to minimize the overall cost of the supply chain.

Design of global supply chain network with operational risks

Recovery, recycling or remanufacturing of post-consumed products are viable alternatives for reducing the environmental problems resulting from the huge amounts of waste currently arriving at landfills. Disassembly operations are inevitable for product recovery therefore the disassembly line is an appropriate choice to carry out the same. A disassembly line balancing problem is how to streamline the disassembly activities, so that the total disassembly time required at each workstation is approximately the same. The assignment of jobs to workstations in a disassembly environment has been the matter of concern to researchers because the product, which has to be disassembled, have different types of materials. The main aim of a disassembly process is to reuse components and reduce undesirable impact on the environment. This paper applies a Kano model, fuzzy-AHP, and M-TOPSIS-based technique, shown to successfully find the optimal order of component removal using AND/OR precedence relation. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed technique has been illustrated with an example and the results show improvements in the performance in comparison with other techniques.

Rajeev Jain

Papers

Integration of Kano’s Model into quality function deployment (QFD)

A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems

Design of global supply chain network with operational risks

A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment

A heuristic approach for U-shaped assembly line balancing to improve labor productivity