Document Type : Research Paper
Authors
1
School of Industrial and Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran.
2
School of Industrial and Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran
3
School of Industrial Engineering, K. N. Toosi University of Technology (KNTU), Tehran, Iran
10.22059/aie.2024.349699.1850
Abstract
Product configuration plays a vital role in product customization. Customers require products with reasonable cost and reliability, so manufacturers should exchange between reliability and production cost through product configuration. To investigate this problem, a novel combined FTA-DFMEA method is presented that implements integrated AHP-TOPSIS to improve product configuration. In this procedure, customer’s needs and market’s feedbacks are considered to identify possible product failures, and an integrated AHP-TOPSIS is applied in order to select the most crucial potential failure based on some identified and extracted criteria. Then, minimal paths are obtained through fault tree analysis and an inverse search method is done to identify related functions and defective components. Failure modes and effect analysis is implemented to conclude modes of failure, effects, and causes. Subsequently, a combined AHP-TOPSIS method is utilized for ranking failure modes and selecting the most crucial failure mode. Failure modes are addressed according to their importance and corrective actions are carried out to improve product configuration. Suppliers with various policies, reliability, warranty and purchasing costs are considered. In addition, for the first time all configuration models like series, parallel, and joint series-parallel as well as redundancy allocation are taken into consideration. A minimum improvement index is considered, which is determined by the decision-maker based on risk-averseness. Eventually, a case study of a laptop system is introduced to evaluate the practicality of the developed algorithm. The results indicate that the proposed method creates different efficient alternatives for the decision-maker to enhance reliability, total costs, and product configuration.
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