Bottleneck Detection within Supply Chain Networks beyond the Factory Boundary and Shifting Bottleneck Trajectories

Abstract Many organizations are involved in a supply chain network. However, information such as the average lead time for each process is segregated among them, making it initially unclear where the bottlenecks are, even during crisis periods of supply chain stoppage. This study proposes an information sharing algorithm that can successfully identify bottlenecks while minimizing the amount of information disclosure, thereby being accepted by supply chain participants. Through the simulation, we statistically demonstrate how each entity can choose an optimal information disclosure strategy that enables the quick identification of bottlenecks with minimal disclosure. After adjusting the batch size and Bill of Materials information, we searched for the critical path and began placing sensor checkpoints within suppliers, allowing detectors to observe the Work in Progress passing through. Initially, suppliers did not disclose any internal information. However, if a bottleneck is suspected, the detector requests that sensors be installed on the suppliers until the bottleneck is detected. The efficiency of the seven strategies was assessed based on the number of sensors required. To deepen the discussion, we conducted experiments on a typical dataset and observed how bottlenecks move across the map as improvement activities are implemented. Even with only a 2.8% difference in total length between the critical path and the second longest path, if bottleneck improvements are made at 20% each time and repeated 10 times, the bottleneck will still remain within the critical path. Furthermore, when comparing the accuracy of the three types of bottleneck detection methods in simulations with another typical dataset, we identified cases in which the bottleneck does not necessarily exist on the critical path.