Development of a fuzzy-TOPSIS multi-criteria decision-making model for material selection with the integration of safety, health and environment risk assessment

Rahim, Aamir Aa; Musa, Shamsudeen; Ramesh, S.; Lim, Ming K.

doi:10.1177/1464420721994269

Cited by 16 publications

(8 citation statements)

References 72 publications

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“…The variables of the suggested models indicated that at the maximum and minimum levels of health risk, compared with the average levels, the "safety efficiency" was more significant on "safety view". The results confirmed the acceptability of the suggested and tested model [28].…”

Section: Selection Of the Right Modelsupporting

confidence: 78%

Investigation and Optimization of Air Pollution Risk by a Multi-criteria Decision Making Method Using Fuzzy TOPSIS: A Case Study of Construction Workers

Sekhavati,

Jalilzadeh Yengejeh

2121

JAEHR

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Background: Investigating human health during work importantly affect the safety and efficiency of the society. Different types of activity, including industrial, constructional, heavy duty ones, etc., affect the health of workers during their activities. In this study, the Multi-Objective Decision-Making (MODM) method was combined with fuzzy TOPSIS to investigate and optimize the air pollution risk affecting the health and safety of construction workers of Lar City, Fars Province, Iran. Methods: The comparison matrices (binary) and the Phillips–Perron test of different criteria and sub-criteria of health risk, including safety view, safety efficiency, understanding the risk, and risk investigation, were assessed to find the most influential factors for the optimization of the health risk of the workers. Results: Accordingly, the results indicated that “understanding the risk” followed by “safety efficiency” affected the health risk of the construction workers the most. However, among the sub-criteria, the most effective ones were “worker knowledge”, “manager knowledge”, “logistic specialized managers”, “modern facilities”, and “modern technology”. The selection of the linear and non-linear models was conducted according to the F values, and the model parameters were estimated using the Newton-Raphson test. Most coefficients were significant at P= 0.99. The model also has a high describing value of 0.97. The final estimated homogeneity coefficient was equal to 1.31, and it ranged from 0.86 to 2.72 for the critical risk investigation. The significance of the present research is to increase the health and safety of workers during work resulting in a more sustainable and healthier environment. Conclusion: Accordingly, the managers could handle the risks, determine the tolerable risks, indicate the risk of each process to control expenses, and take the essential measures for optimization.

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Section: Selection Of the Right Modelsupporting

confidence: 78%

Investigation and Optimization of Air Pollution Risk by a Multi-criteria Decision Making Method Using Fuzzy TOPSIS: A Case Study of Construction Workers

Sekhavati,

Jalilzadeh Yengejeh

2121

JAEHR

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“…At the same time, the stability and validity of the developed approaches are further proved by sensitivity investigation and comparison with existing approaches. It is very meaningful for the proposed methods to be extended in other fuzzy environments [51][52][53][54][55][56][57], uncertain MAGDM problems [58][59][60][61][62][63][64] and risk assessment [65][66][67][68], etc.…”

Section: Discussionmentioning

confidence: 99%

Spherical fuzzy hamacher power aggregation operators based on entropy for multiple attribute group decision making

Zhang

Wang

Cai

et al. 2023

IFS

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As an improved form of fuzzy sets (FSs), spherical fuzzy sets (SFSs) could provide decision makers (DMs) with more free space to express their preference information. In this article, we first develop some Hamacher power aggregation operators under SFSs by power operators and Hamacher operators, including spherical fuzzy Hamacher power average (SFHPA) operator, spherical fuzzy Hamacher power geometric (SFHPG) operator, spherical fuzzy Hamacher power weighted average (SFHPWA) operator, spherical fuzzy Hamacher power weighted geometric (SFHPWG) operator, spherical fuzzy Hamacher power ordered weighted average (SFHPOWA) operator, spherical fuzzy Hamacher power ordered weighted geometric (SFHPOWG) operator, spherical fuzzy Hamacher power hybrid average (SFHPHA) operator and spherical fuzzy Hamacher power hybrid geometric (SFHPHG) operator. At the same time, some properties of the proposed operators are investigated, and the relationships between these operators and existing operators are discussed. Furthermore, a novel spherical fuzzy entropy measure is introduced to calculate unknown attribute weights. Then, some novel multiple attribute group decision making (MAGDM) methods are established by the proposed operators as well as entropy measure under SFSs. Lastly, the practicability of the presented methods is verified with a numerical case. Moreover, the robustness, availability and superiority for the developed methods are demonstrated via sensitivity analysis and further comparation with the existing methods.

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“…In general, in implementing FMEA or EFMEA, three categories are most often considered: severity (S), occurrence (O), and detection (D); they are generally evaluated on a numeric scale of 1 to 10 (Kardos, Lahuta & Hudakova 2021). At the same time, according to the literature, depending on the needs, 9-, 7-, 5-and 3-point scales can also be used (Rahim et al 2021, Wiśniewska 2022. The severity rating ranks the importance of a risk to end-user requirements.…”

Section: Efmea Methods and Its Applicationmentioning

confidence: 99%

Environmental Failure Mode and Effect Analysis and Its Application in a Seafood Company

Wiśniewska

Grybek

Szymańska-Brałkowska

2023

KREM

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To present an EFMEA analysis using the example of a seafood organisation, including risk identification, in the context of a potential negative impact on the environment. Research Design & Methods: Methods used include a case study with analysis of secondary data (documents), semi-structured interviews with a representative of the organisation, synthesis and logical reasoning. Findings: EFMEA is a very complex analysis and is extended with additional considerations that are important for the organisation. Process EFMEA and its implementation was facilitated by Małgorzata Z. Wiśniewska, Tomasz Grybek, Małgorzata Szymańska-Brałkowska 74 experience gained from the earlier implementation of the HACCP method and ISO 14001 system. The requirements of customers for conducting analysis in this area played a role. Implications / Recommendations: The greatest environmental risk is associated with servicing refrigeration/cooling equipment, handling operations, maintaining social infrastructure and cargo storage. An obstacle to conducting the analysis was the lack of access to all comparative data. The leading benefit of the study was that it makes it possible to manage environmental consideration and then monitoring them effectively. Contribution: The article is the first in Poland to look at the practical implementation of EFMEA. Thus, the spectrum of scientific knowledge has been expanded on the possible applications of this method in a food company and, more generally, how to control and minimise negative environmental impacts in the seafood industry.Article type: original article.

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Development of a fuzzy-TOPSIS multi-criteria decision-making model for material selection with the integration of safety, health and environment risk assessment

Cited by 16 publications

References 72 publications

Investigation and Optimization of Air Pollution Risk by a Multi-criteria Decision Making Method Using Fuzzy TOPSIS: A Case Study of Construction Workers

Investigation and Optimization of Air Pollution Risk by a Multi-criteria Decision Making Method Using Fuzzy TOPSIS: A Case Study of Construction Workers

Spherical fuzzy hamacher power aggregation operators based on entropy for multiple attribute group decision making

Environmental Failure Mode and Effect Analysis and Its Application in a Seafood Company

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