A knowledge-based algorithm for supply chain conict detection based on OTSM-TRIZ problem flow network approach

Abstract

The coordination and integration of efforts and activities of Supply Chain (SC) members, which is a key component in the success of the supply chain management, has become a challenging issue due to conicts in such systems. Inability to properly detect conicts in an SC and, therefore, mismanagement of them will increase disruption risk in the SC. In this article, a knowledge-based algorithm is presented based on the OTSMTRIZ (general theory of powerful thinking) problem flow network approach to identify, formulate, and solve the conicts of SCs before they occur and cause harmful effects. The proposed algorithm involves analyzing and developing Network of Problems (NoPs) in order to transfer them into a network of conicts. The algorithm is validated through presenting a case study. After implementation and application, the result demonstrated that this knowledge-based algorithm was able to identify and formulate supply chain conicts before they occurred and, more importantly, it greatly increased the coordination between supply chain entities.