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- MakaleYalnız künye2024Scopus SJRQ2A risk assessment model with dependent failure modes for the manufacturing and design processes of medical equipment
Lo, Huai-Wei; Gul, Muhammet; Yucesan, Melih; Liaw, Ching-Fang
The reliability of medical equipment is paramount for surgical success. Manufacturers are continuously exploring risk assessment and improvement strategies to prevent equipment malfunctions during surgery. Failure mode and effects analysis (FMEA) can primarily be divided into two types: DFMEA (Design FMEA) and PFMEA (Process FMEA). Traditional FMEA serves as a practical tool for identifying and prioritizing key failure modes (FMs). However, past FMEA research has overlooked the interdependencies among FMs, treating them as independent entities, which does not align with real-world operations. This paper introduces a groundbreaking risk dependency assessment model aimed at addressing the influential relationships among FMs. The modified technique for defining the influential relationship of failure modes (modified TEDIR-FMs) is developed to compute the relative risk scores of different FMs accurately. At its core, this paper integrates concepts from multiple criteria decision-making (MCDM) techniques into FMEA, with a particular focus on the interdependencies of failure modes in the manufacturing and design manufacturing processes of medical equipment. The model’s application is demonstrated through a case study on a medical device for hernia surgery. The introduction of modified TEDIR-FMs not only enhances the accuracy of risk assessments but also offers a fresh perspective on risk management within the design and manufacturing processes. The research results indicate that the three failure modes with the highest risk are “adhesive does not deploy or only partially deploys from the dispenser,” “the mesh does not adhere to the adhesive,” and “the adhesive drips from the tip.” In the manufacturing and design processes of this device, greater attention should be given to improving the adhesive components.
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İncele - MakaleYalnız künye2021Scopus SJRQ1Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making
Lo, Huai-Wei; Liaw, Ching-Fang; Gul, Muhammet; Lin, Kuan-Yu
Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.
AtıfScopus67WoS56OpenAlex64İncele - MakaleAçık Erişim2021Fermatean fuzzy TOPSIS-based approach for occupational risk assessment in manufacturing
Gul, Muhammet; Lo, Huai-Wei; Yucesan, Melih
The importance of risk assessment in the context of occupational health and safety by manufacturing operators strengthens their hands in solving the problems they may encounter in business processes related to health and safety. One of the most important phases of conducting an exhaustive occupational risk assessment is to analyze potential hazards and associated risks quantitatively. Since manufacturing is one of the industries that require workers to be highly exposed to work, creating a safer environment to reduce occupational injuries is an important task. This study proposes a novel fuzzy risk assessment approach developed by integrating Fermatean fuzzy sets (FFSs) and technique for order preference by similarity to ideal solution (TOPSIS) method for ranking potential hazards in manufacturing. FFSs are a new version of fuzzy set theory that covers the intuitionistic fuzzy sets and Pythagorean fuzzy sets. This version of the fuzzy set is crucial in the decision-making process to handle uncertain information more easily and reflect uncertainty better. A linguistic scale under Fermatean fuzzy documentation has also been developed for experts/decision makers to disclose their judgments easily. Occupational risk analysts can benefit from this approach since FFSs are used for the first time in occupational risk assessment, and the approach is presented in integration with TOPSIS. The proposed approach is applied in the aluminum plate-manufacturing process risk assessment. In the conclusion of the implementation, risks arising in the production are prioritized. In addition, this study made comparisons with other fuzzy methods to demonstrate the proposed approach’s difference and practicality. This study’s results can support practitioners and risk analysts in formulating the improvement measures to increase the safety of the work environment further.
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