A Model-Driven Decision Support System for Reallocation of Supply to Orders Under Uncertainty in Ceramic Companies

Abstract

Abstract. In ceramic companies, uncertainty in the tone and gage obtained in first quality units of the same finished good (FG) entails frequent discrepancies between planned homogeneous quantities and real ones. This fact can lead to a shortage situation in which certain previously committed customer orders cannot be served because there are not enough homogeneous units of a specific FG (i.e., with the same tone and gage). In this paper, a Model-Driven Decision Support System (DSS) is proposed to reassign the actual homogeneous stock and the planned homogeneous sublots to already committed orders under uncertainty by means of a mathematical programming model (SP-Model). The DSS functionalities enable ceramic decision makers to generate different solutions by changing model options. Uncertainty in the planned homogeneous quantities, and any other type of uncertainty, is managed via scenarios. The robustness of each solution is tested in planned and real situations with another DSS functionality based on another mathematical programming model (ASP-Model). With these DSS features, the ceramic decision maker can choose in a friendly fashion the orders to be served with the current homogeneous stock and the future uncertainty homogeneous supply to better achieve a balance between the maximisation of multiple objectives and robustness.

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

“…There are also other works that study the problem of the LHP, and even in the ceramic sector [31] or [32]. In [33] a review of the works that propose mathematical models to support the order promising process in LHP situations is made.…”

Simulation to reallocate supply to committed orders under shortage

“…Indeed, the solutions to these shortage situations seriously impact the reliability of the OP processing. Therefore, the recognised relevance of the OP processing in the literature to better deal with demand requirements with high standards of service level and customer satisfaction (Alemany et al, 2015a;Grillo et al, 2016) supports the importance of shortage planning (SP).…”