A decision-making method for supplier selection in industrial manufacturing industry: A mathematical framework of integrating analytical hierarchical process and reliability risk evaluation in the field of industrial engineering sectors

The supplier is a crucial component of the supply chain, with the supply chain encompassing vendor management. Selecting an industry-appropriate supplier involves assessing the supplier’s performance. This selection process not only satisfies customer requirements and generates profit for the organization but also ensures compliance with all defined supplier attributes. The task of choosing an appropriate supplier is essential and can often be challenging. The objectives of the supply chain include enhancing productivity, reducing costs, and meeting the demands of emerging markets. This thesis introduces the concept of relative reliability risk assessment, particularly for new suppliers. Measuring performance is critical for vendor selection, as failure to do so can negatively impact the organization’s reputation. The paper employs a four-tier method: establishing a functional structure, applying the Analytical Hierarchical Process (AHP), utilizing the entropy method, and organizing alternative functionality graphs. The model’s effectiveness is demonstrated through empirical case studies and comparisons with traditional supplier selection methods, showcasing its capability to manage uncertainty and improve decision accuracy.Multiple alternatives and criteria are considered to facilitate the decision-making process for selecting suitable vendors. The AHP is utilized for multi-attribute decision-making among various vendors, effectively addressing the inherent biases, vagueness, and subjectivity in human decision-making. The Eigenvalue of the AHP is calculated in Excel using specific formulas, with the consistency index being determined each time. The entropy method is applied to calculate the weights of different attributes, which are then used to compute the Relative Reliability Risk Index. The alternative functionality graph displays the strengths and weaknesses of all alternatives concerning multiple attributes. A real-life case study demonstrating the application of Multiple Attribute Decision Making (MADM) with the proposed method is presented in this paper. The suggested model offers valuable insights for practitioners aiming to enhance supplier selection strategies and boost overall supply chain performance.