A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing

Boral, Soumava; Howard, Ian; Chaturvedi, Sanjay K.; McKee, Kristoffer K.; Naikan, V. N. A.

doi:10.1016/j.spc.2019.10.005

Cited by 62 publications

(14 citation statements)

References 55 publications

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“…Similarly, Wen et al [48] focused on the solving of the supplier selection problems with integrating the 2-tuple linguistic representation and soft set. Furthermore, Boral et al [49] identified the important factors that affect the effectiveness of the manufacturing industry. For this purpose, hesitant 2tuple linguistic fuzzy sets are considered.…”

Section: B Literature On the Methodologymentioning

confidence: 99%

Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

et al. 2020

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This study aims to identify quality improvement strategies for energy investments. For this purpose, a model is proposed which includes 4 different stages. In the first stage, the MCDM problem is identified for evaluating the service development for energy industry. In this framework, quality function deployment (QFD) approach is taken into consideration which includes both customer expectations and technical requirements at the same time to improve the quality in the organization. The second stage is related to the calculation of the correlation coefficients of decision matrices for the criteria by considering hesitant 2-tuple interval-valued Pythagorean fuzzy sets. The third stage includes the weighting of the customer expectations with hesitant 2-tuple interval-valued Pythagorean fuzzy (HIVPF) DEMATEL. In the final stage, TRIZ-based quality improvement strategies of energy investments are ranked by using 2-tuple HIVPF TOPSIS. Thus, the motivation of this study is to figure out the weights of the criteria for quality improvement strategies in energy investments. Also, the most important contribution of this study to the literature is related to the originality in the methodology by proposing a new MCDM model while using hesitant linguistic term sets, linguistic 2-tuple information, interval-valued Pythagorean fuzzy sets properly. The findings indicate that empathy is the most significant criterion for the customer expectations in the energy investments. In addition to this issue, it is also identified that customization is the best factor among the technical requirements of energy investments. Moreover, information and communication facilities and organizational background are found as the best competencies of new service development in energy investments. Furthermore, that prior action and periodic action are the most prominent strategies for quality improvement. While considering these results, it can be said that the pricing policy of the energy companies should be fair to increase customer satisfaction. Additionally, offering flexible payment opportunities on energy bills can have a positive influence on the customer satisfaction in this process. Also, preliminary planning of the project should be done in detail in energy investments. Owing to this issue, customers' preferences can be identified before the product is placed on the market. In addition, it can be possible to identify the risks that may arise in energy investments with the help of the periodical audits.

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Section: B Literature On the Methodologymentioning

confidence: 99%

Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

et al. 2020

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“…An interval rough number extended DEMATEL-ANP was introduced for criteria weighting and an interval rough number extended MAIRCA was developed for alternative ranking. Boral et al 55 presented a hybrid MCDM model for risk evaluation in sustainable manufacturing, by combining an IT2F-DEMATEL and a fuzzy MAIRCA. An IT2F-DEMATEL was adopted to calculate the causal dependencies and criteria weights.…”

Section: Studies On Dematel and Maircamentioning

confidence: 99%

Evaluating biological inspiration for biologically inspired design: An integrated DEMATEL‐MAIRCA based on fuzzy rough numbers

Zhu

2021

Int J Intell Syst

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Biological inspiration evaluation has been widely acknowledged as one of the most important phases in biologically inspired design (BID) as it substantially determines the direction of the following-up design activities. However, it is inherently an interdisciplinary assessment, which includes both the engineering domain and the biological systems. Due to the lack of knowledge at the early stage of product design, the risk assessments mainly depend on experts' subjective judgments, which values are vague, imprecise, and even inconsistent. How to objectively evaluate the biological inspiration under such uncertain and interdisciplinary scenarios remains an open issue. To bridge such gaps, this study proposes a fuzzy rough number extended multi-criteria group decision-making (MCGDM) to evaluate the biological inspiration for BID. A fuzzy rough number is introduced to represent the individual decision maker's risk assessment and aggregate respective evaluation values within the decision-making group. A fuzzy rough number extended decision-making trial and evaluation laboratory is presented to determine the criteria weights and a fuzzy rough number extended multi-attribute ideal real comparative analysis is proposed to rank the candidate biological inspirations. Experimental results and comparative analysis validate the superiority of the proposed MCGDM in handling the subjectivity and uncertainty in biological inspiration evaluation.biological inspiration evaluation, biologically inspired design, DEMATEL, fuzzy rough number, MAIRCA | INTRODUCTIONBiologically inspired (i.e., bio-inspired) design (BID) is a promising and rapidly increasing paradigm for design innovation and sustainable design. 1 For millions of years, a huge number of biological functions, behaviors, and structures have been evolved in nature, providing a robust and efficient manner that enables plants and animals to sustain their existence in diverse ways. 2 As a knowledge-driven design methodology, BID aims to systematically mine biological knowledge (e.g., biological functions, behaviors, and structures) to resolve engineering problems, such as eco-design and design creativity-inspiring. 3 It starts with the problem formulation and follows with the problem reframing, biological inspiration identification (i.e., biological solution acquisition, biological solution definition, biological inspiration generation, and biological inspiration evaluation), and the final biological inspiration application. 4 Due to its prominent performance in creativity-inspiring and technical innovation, BID has been widely investigated in various areas and a vast amount of biomimetic applications have emerged in our daily life, such as algorithm development, 5 robotics, 6 material design, 7 optics, 8 and image processing. 9 BID is inherently interdisciplinary. 10 To facilitate the knowledge analogy between the engineering world and biological systems, designers should be equipped with a strong background in the engineering discipline as well as good expertise in the biol...

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“…From this point forward, many GDM studies were mainly focused on Multi-Criteria Decision-Making (MCDM) methods. Some authors have suggested extensions of existing methods like TOPSIS [45,46], FMEA [47] and DEMATEL [48]. More recently, an increasing inclination to use fuzzy MCDM is evident [49][50][51][52][53].…”

Section: Group Decision-makingmentioning

confidence: 99%

A Literature Review of the Concepts of Resilience and Sustainability in Group Decision-Making

Ardebili

Padoano

2020

Sustainability

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The most critical decisions usually involve several decision makers with different roles and opportunities to commit key resources. Several group decision-making (GDM) approaches can support the identification of a joint or compromise decision in less conflicting settings, where there is a group of subjects (e.g’, partners) who pursue a common overall objective. However, considering the uncertainty in future events and complexity of modern-day systems, decision processes do not always produce beneficial results or give the participants a positive perception of their role in the process. Group decision-making should then take into consideration some aspects that might insure future resilience and sustainability, particularly the achievement of the objectives in view of future risks and the transparency and participation that are needed to limit problems in the implementation phase of the decision. The literature survey presented in this study identified a research gap regarding GDM. Differently from traditional GDM, which was first discussed in the early 1980s and whose body of knowledge is pretty defined, resilient and sustainable GDM (R&S GDM) is fairly new. The main objective of this study is then identifying the main attributes for supporting sustainable and resilient group decisions. To this aim, a preliminary focused systematic review was conducted to study the existing group decision-making methods in the literature and how the concepts of sustainability and resilience have been employed. After defining the search keywords and exclusion criteria for the individuation of the articles, the first screening process was carried out and the most relevant articles were selected. The last steps of the systematic review were the classification of the articles and the full paper examination to extract the main factors of R&S GDM. Seven attributes were listed as the key factors of R&S GDM. In light of those factors, a group decision process concerning an injection moulding line in Tajikistan was investigated. The case study highlighted that over self-confidence, information flow and transparency were the main reasons for faulty decisions, thus suggesting that information system and information fluidity play an important role in R&S GDM. Finally, the most important managerial implications of R&S GDM are reported.

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A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing

Cited by 62 publications

References 55 publications

Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

Evaluating biological inspiration for biologically inspired design: An integrated DEMATEL‐MAIRCA based on fuzzy rough numbers

A Literature Review of the Concepts of Resilience and Sustainability in Group Decision-Making

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