同步
供应链
汽车工业
提前期
订单(交换)
计算机科学
总拥有成本
业务
信息共享
运筹学
运营管理
产业组织
风险分析(工程)
营销
经济
电信
工程类
传输(电信)
航空航天工程
财务
万维网
操作系统
作者
Toyin Clottey,W.C. Benton
标识
DOI:10.1177/10591478241260432
摘要
The push for more battery-powered electric vehicles, the COVID-19 pandemic, and other global supply chain destabilizing events (e.g., the war in Ukraine) have made it necessary for manufacturers to consider innovative approaches to sourcing and materials management. This study assesses the value of sharing delivery due date updates, which are then used to convert spent time into a fraction of the expected total time for order fulfillment (i.e., progress updates), to synchronize the delivery of components for an automotive manufacturer who, amid long and variable lead times for semiconductor chips, maintains a strategy of waiting for the delivery of all needed parts before commencing production. Having progress updates in a fractional form puts numerical bounds (i.e., 0% to 100%) on the shared information, and this facilitates closed-form analytical comparisons. We develop analytical models to show decreases in expected assembly-related costs based on the progress update information shared between two suppliers—one supplier has a shorter and more reliable order fulfillment lead time than the other. When there are more than two suppliers, we use a simulation model to estimate the expected value of sharing progress updates. Our results show that increasing the frequency of shared progress updates, and having more suppliers share progress updates, results in increased cost-savings percentages. However, the opposite occurs with increasing uncertainty in suppliers’ delivery lead times. The computational study provides support for the existence of a critical mass level of suppliers needed to achieve a given percentage cost saving. This study can help automakers to make informed decisions on encouraging information sharing among suppliers, by first creating a critical mass of suppliers to share progress updates. Our investigations also help show the conditions in which to best leverage such information sharing strategies while waiting for the delivery of all needed components prior to production.
科研通智能强力驱动
Strongly Powered by AbleSci AI