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Stochastic production capacity: A bane or a boon for quick response supply chains?

机译:随机生产能力:快速响应供应链的祸根?

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摘要

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.
机译:可以通过缩短交货时间来应对需求波动的快速响应(QR)系统已在文献中进行了深入研究。现有的许多文献都隐含或显式地假定QR之下的制造商总是能够满足需求,因为生产能力总是足够的。但是,如果在QR下订单的交货期很短,则无法保证制造商的生产能力。这激励我们探索具有随机生产能力的供应链中的QR。具体来说,我们在具有贝叶斯需求信息更新的两级供应链中研究QR。我们考虑在QR下制造商的生产能力不确定的情况。我们首先探讨随机生产能力如何影响供应链决策和QR实施。然后,我们将制造商的能力扩展到模型中。我们探索制造商如何确定最佳的产能扩张决策,以及这种能力对供应链及其代理商的价值。最后,将模型扩展到两阶段二阶情况,并通过动态规划得出最优的排序策略。我们比较单次订购和两次订购的情况,以生成有关在生产能力随机时订购灵活性如何影响QR的其他管理见解。我们还探索了透明的供应链,发现我们的主要结果仍然成立。

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