Robust supplier-selection and order-allocation in two-echelon supply networks: A parametric tolerance design approach

Abstract

In this paper, we study the integrated supplier-selection and order-allocation problem in a two-echelon make-to-order supply chain motivated by the belt conveyor industry. In our setting, the Original Equipment Manufacturer (OEM) can source its single product from multiple suppliers in the first echelon who themselves source the sub-components of the product from multiple other suppliers in the second echelon. Within the second echelon, the suppliers fall into clusters of product supply networks based on their capability to produce a part. OEM in our setting is interested in determining the optimal tolerances for its supply network members to operate so as to minimize the variability introduced into the total supply chain costs. To obtain the optimal supplier-selection and order-allocations under a periodic review demand policy, we model the problem as a mixed-integer non-linear programming (MINLP) formulation. We further incorporate the Taguchi Method of Tolerance Design (TMTD) into our model, leading to robustness of our solutions while maintaining optimality in supplier-selection and order-allocation decisions. We test our model using a real-world case study and derive critical insights. Our numerical results demonstrate a 51% improvement in coefficient of variation of the objective function when our method is applied to the real life case study. Additionally, we show that as the level of confidence of the decision-maker on the range for a critical parameter increases, the gains from our methodology significantly increase.