IoT-based milk-run routing for manufacturing system: an application case in an automotive company
研究将牛奶跑系统与物联网集成，提出动态路线规划模型，用Python算法解决NP难问题，在汽车公司实际应用中减少了库存、提高了拖车利用率并最小化了每日路径。
The Internet of Things (IoT) provides new opportunities to improve manufacturing lines’ performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains’ fleet was improved, and (iii) the daily path was minimized.