An Alternative Ranking Approach and Its Usage in Multi-Criteria Decision-Making

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The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement system, fuzzy control charts are available tools for monitoring and evaluating the process. The main contribution of fuzzy control charts is to provide flexibility to the control limits. When sample mean is too close to the control limits and the used measurement system is not so sensitive, the decision may be faulty. In this paper, the fuzzy standard deviation is firstly introduced to obtain fuzzy X and S control charts and then these fuzzy control charts are employed in food industry to monitor if the processes are under control or not. Additionally, the fuzzy X and S control charts are developed for the case that the population parameters (µ and σ) are known.

Section: Published By Atlantis Pressmentioning

confidence: 99%

Evaluating the Packing Process in Food Industry Using Fuzzy X and S Control Charts

Erginel¹,

Şentürk²,

Kahraman³

et al. 2011

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“…The ranking of fuzzy numbers is important in fuzzy multiattribute decision making (MADM). There exists a large amount of literature involving the ranking of fuzzy numbers [1][2][3][4][5][6][7][8][9] . Roughly speaking, a fuzzy number may be considered as a representation for an ill-known quantity.…”

Section: Introductionmentioning

confidence: 99%

A Ranking Method of Triangular Intuitionistic Fuzzy Numbers and Application to Decision Making

Li¹,

Nan²,

Zhang³

2010

Ranking of triangular intuitionistic fuzzy numbers (TIFNs) is an important problem, which is solved by the value and ambiguity based ranking method developed in this paper. Firstly, the concept of TIFNs is introduced. Arithmetic operations and cut sets over TIFNs are investigated. Then, the values and ambiguities of the membership degree and the non-membership degree for TIFNs are defined as well as the value-index and ambiguity-index. Finally, a value and ambiguity based ranking method is developed and applied to solve multiattribute decision making problems in which the ratings of alternatives on attributes are expressed using TIFNs. A numerical example is examined to demonstrate the implementation process and applicability of the method proposed in this paper. Furthermore, comparison analysis of the proposed method is conducted to show its advantages over other similar methods.

“…In such situations, the use of fuzzy set approach explicitly handles vague and imprecise data in the decision model. In addition, fuzzy set approaches to decision-making are usually most appropriate when expert evaluations are needed (Kahraman & Tolga, 2009). In this paper, this is realized by adopting a Modified Delphi Method with the cooperation of multiple experts to identify evaluation criteria.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Fuzzy Multi-Criteria Decision-Making Approach for Six Sigma Project Selection

Perçin¹,

Kahraman²

2010

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Selecting an appropriate six sigma project is one of the most important problems for a manufacturing company because it impacts the manufacturing costs. Besides, an appropriate choice of Six Sigma projects is very important as it helps to improve quality, reduce variation, and eliminate waste of a manufacturing system. Therefore, the main purpose of this study is to provide a good insight into the use of an integrated decision-making methodology in the evaluation of Six Sigma projects. For this purpose, we integrate three multi-criteria decision-making (MCDM) methods by applying a modified Delphi method, Analytical Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) methodologies. After the evaluation criteria of Six Sigma projects are determined by a Modified Delphi method, the weights of criteria are calculated by applying the AHP method. The FTOPSIS method is then employed to achieve the final ranking results. A real case application along with a sensitivity analysis is presented to show the effectiveness of the proposed methodology. The research question for this methodology is how we can develop an integrated MCDM model to select six sigma projects. six sigma has become one of the most important subjects in business strategy. Thus, six sigma has received considerable attention from researchers. Three research areas for six sigma have attracted interest among the researchers: First, the critical success factors for six sigma implementation, second, the basic concepts, tools, and applications of six sigma approach and finally the selection of six sigma projects for business improvement. This paper focuses on the last area.Six sigma is regarded as a project-based methodology that can help a company achieve expected benefits through continuous project improvement (Su & Chou, 2008). It is originated at Motorola in the early 1980s, and then many companies such as GE