scholarly journals Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Atef M. Ghaleb ◽  
Husam Kaid ◽  
Ali Alsamhan ◽  
Syed Hammad Mian ◽  
Lotfi Hidri
Keyword(s):  
Decision Making ◽  
Computational Complexity ◽  
Manufacturing Process ◽  
Group Decision ◽  
Die Casting ◽  
Multicriteria Decision Making ◽  
Sand Casting ◽  
Manufacturing Processes ◽  
Alternative Processes ◽  
Selection Of

The selection of manufacturing processes for a given application is a complex problem of multicriteria decision-making although there have been several different approaches that can be utilized to select a suitable alternative. However, identifying appropriate multicriteria decision-making approach from the list of available methods for a given application is a difficult task. This work suggests a methodology to assess different selection approaches, which are the technique for order of preference by similarity to ideal solution (TOPSIS), analytic hierarchy process (AHP), and VIKOR: stepwise procedure. This valuation was done depending on the following factors: number of alternative processes and criteria, agility through the process of decision-making, computational complexity, adequacy in supporting a group decision, and addition or removal of a criterion. A case study in this study was presented to analyse the evaluation methodology. The criteria used to evaluate and identify the best manufacturing process were categorized into productivity, accuracy, complexity, flexibility, material utilization, quality, and operation cost. Five manufacturing processes were considered, including gravity die casting, investment casting, pressure die casting, sand casting, and additive manufacturing. The results showed that each approach was suitable for the problems of manufacturing process selection, in particular toward the support of group decision-making and uncertainty modelling. Manufacturing processes were ranked based on their respective weights for AHP, TOPSIS, and VIKOR, and sand casting is the best. In terms of computational complexity, the VIKOR method performed better than TOPSIS and AHP. Moreover, the VIKOR and TOPSIS methods were better convenient to the selection of manufacturing processes for agility during the process of decision-making, the number of alternative processes and criteria, adequacy in supporting a group decision, and addition or removal of a criterion.

Computer-aided sensitivity analysis of a multicriteria decision-making methodology for the evaluation of materials requirements stringency in the nuclear components manufacturing

2019 ◽  
Vol 233 (10) ◽  
pp. 2094-2107
Author(s):  
Álvaro Rodríguez-Prieto ◽  
Ana M Camacho ◽  
Ángel Yanguas-Gil ◽  
Miguel A Sebastián
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Power Plant ◽  
Nuclear Power ◽  
Multicriteria Decision Making ◽  
Manufacturing Processes ◽  
Primary Loop ◽  
Computer Aided ◽  
Selection Of

A methodology developed specifically for the evaluation of requirements of materials intended to high-demanding applications is the stringency levels methodology. The objective of this work is to perform a sensitivity analysis of the methodology of multicriteria stringency levels for the evaluation of technological requirements of materials, creating a new methodology that provides a final results studying variability that let us make an objective decision. The case study has been the evaluation of steels used in the manufacture of components housed in the primary loop of a nuclear power plant. To ease the calculation of the stringency levels, the algorithm has been computed in Labview®. Considering the dispersion that can generate the numerical weighting process, the analysis has shown that the variability in calculated values is not significant. The analysis proposed with this methodology could be used, in the future, for the selection of materials for innovative manufacturing processes.

Developing a Capability-Based Similarity Metric for Manufacturing Processes

2017 ◽  
Author(s):  
Kevin Li ◽  
William Z. Bernstein
Keyword(s):  
Decision Making ◽  
Manufacturing Process ◽  
Product Life Cycle ◽  
Process Model ◽  
Die Casting ◽  
Process Models ◽  
Manufacturing Processes ◽  
Design Phase ◽  
Similarity Metric ◽  
On Line

Manufacturing taxonomies and accompanying metadata of manufacturing processes have been catalogued in both reference books and databases on-line. However, such information remains in a form that is uninformative to the various stages of the product life cycle, including the design phase and manufacturing-related activities. This challenge lies in the varying nature in how the data is captured and represented. In this paper, we explore measures for comparing manufacturing data with the goal of developing a capability-based similarity metric for manufacturing processes. To judge the effectiveness of these metrics, we apply permutations of them to 26 manufacturing process models, such as blow molding, die casting, and milling, that were created based on the ASTM E3012-16 standard. Furthermore, we provide directions towards the development of an aggregate similarity metric considering multiple capability features. In the future, this work will contribute to a broad vision of a manufacturing process model repository by helping ease decision-making for engineering design and planning.

scholarly journals Fuzzy Boost Classifier of Decision Experts for Multicriteria Group Decision-Making

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Xiao-yi Wang ◽  
Yi Yang ◽  
Yu-ting Bai ◽  
Jia-bin Yu ◽  
Zhi-yao Zhao ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Subjective Experience ◽  
Group Decision ◽  
Multicriteria Decision Making ◽  
Vital Role ◽  
Classification Method ◽  
Multicriteria Group Decision Making ◽  
Expert Classification ◽  
Selection Of

The expert is a vital role in multicriteria decision-making, which provides source decision opinions. In the existing group decision-making activities, the selection of experts is usually conducted artificially, which relies on personal subjective experience. It has been the urgent demand for an automatic selection of experts, which can help to determine their weights for the follow-up decision calculation. In this paper, an expert classification method is proposed to solve the problem. First, the CatBoost classification algorithm is improved by integrating the 2-tuple linguistic, which can effectively extract the features of samples. Second, the framework of the expert classification is designed. The flow combines the expert resume collection, expert classification, and database update. Third, a decision-making case is analyzed for the expert selection issue. The experiment and result indicate that the proposed classifier performs better than the classic methods. The proposed classification method of the decision experts can support the automatic and intelligent operation of the decision-making activities.

scholarly journals Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen
Keyword(s):  
Decision Making ◽  
Interest Rates ◽  
Small And Medium Enterprises ◽  
Multicriteria Decision Making ◽  
Primary Concern ◽  
Multicriteria Decision ◽  
Financial Leasing ◽  
Criteria Weights ◽  
Leasing Company ◽  
Selection Of

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.

scholarly journals Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 574 ◽  
Author(s):  
Zengxian Li ◽  
Hui Gao ◽  
Guiwu Wei
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Selection Of

In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

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