Department of Supply Chain Management, University of Business and Technology, University of Business and Technology St, Jeddah 23847, Saudi Arabia.
Department of Industrial and Systems Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC 27411, USA.
Sensors (Basel). 2023 Apr 17;23(8):4041. doi: 10.3390/s23084041.
In today's global environment, supplier selection is one of the critical strategic decisions made by supply chain management. The supplier selection process involves the evaluation of suppliers based on several criteria, including their core capabilities, price offerings, lead times, geographical proximity, data collection sensor networks, and associated risks. The ubiquitous presence of internet of things (IoT) sensors at different levels of supply chains can result in risks that cascade to the upstream end of the supply chain, making it imperative to implement a systematic supplier selection methodology. This research proposes a combinatorial approach for risk assessment in supplier selection using the failure mode effect analysis (FMEA) with hybrid analytic hierarchy process (AHP) and the preference ranking organization method for enrichment evaluation (PROMETHEE). The FMEA is used to identify the failure modes based on a set of supplier criteria. The AHP is implemented to determine the global weights for each criterion, and PROMETHEE is used to prioritize the optimal supplier based on the lowest supply chain risk. The integration of multicriteria decision making (MCDM) methods overcomes the shortcomings of the traditional FMEA and enhances the precision of prioritizing the risk priority numbers (RPN). A case study is presented to validate the combinatorial model. The outcomes indicate that suppliers were evaluated more effectively based on company chosen criteria to select a low-risk supplier over the traditional FMEA approach. This research establishes a foundation for the application of multicriteria decision-making methodology for unbiased prioritization of critical supplier selection criteria and evaluation of different supply chain suppliers.
在当今的全球环境下，供应商选择是供应链管理做出的关键战略决策之一。供应商选择过程涉及基于几个标准评估供应商，包括他们的核心能力、价格报价、交货时间、地理位置、数据收集传感器网络和相关风险。物联网（IoT）传感器在供应链不同层次的普遍存在可能导致风险级联到供应链的上游端，因此必须实施系统的供应商选择方法。本研究提出了一种使用故障模式影响分析（FMEA）与混合层次分析法（AHP）和偏好排序组织法（PROMETHEE）的组合方法，用于供应商选择中的风险评估。FMEA 用于根据一组供应商标准识别故障模式。AHP 用于确定每个标准的全局权重，而 PROMETHEE 则用于根据最低供应链风险对最优供应商进行优先级排序。多准则决策方法（MCDM）的集成克服了传统 FMEA 的缺点，并提高了风险优先数（RPN）排序的精度。案例研究验证了组合模型。结果表明，基于公司选择的标准，供应商的评估更加有效，从而可以选择风险较低的供应商，而不是传统的 FMEA 方法。本研究为应用多准则决策方法对关键供应商选择标准进行无偏优先级排序和评估不同供应链供应商奠定了基础。
