This paper studies whether and how a manufacturer can mitigate the effects of demand uncertainty during production ramp up by jointly managing inventory and capacity development, determined by the productivity of a heterogeneous workforce. One way the manufacturer can direct its capacity development is by recognising that workers become more productive as they gain experience when making scheduling decisions. We consider a situation in which demands for multiple products are periodically revealed and a manufacturer must decide what each individual does in the production process, how much inventory is accumulated, and how demands are met. To study the potential benefits, we formulate a Markov decision process model which we solve using a one-step lookahead approximation. Results of an extensive computational study show that, given the effectiveness associated with both directing capacity and holding inventory, manufacturers should consider the workforce's capacity to learn when making job assignments during production ramp up. Analysis of the results suggests that inventory and capacity building patterns depend on product value and the workforce's experience levels. Further analysis shows that slower learners and those with the potential to achieve higher productivity should specialise more. Faster learners, on the other hand, are best suited for cross training.

本文研究了制造商是否以及如何通过共同管理库存和产能发展来减轻生产增加期间需求不确定性的影响，这取决于异质劳动力的生产力。制造商可以指导其能力开发的一种方法是认识到工人在制定调度决策时获得经验会变得更有效率。我们考虑这样一种情况，其中对多种产品的需求会周期性地暴露出来，制造商必须决定每个人在生产过程中做什么、积累了多少库存以及如何满足需求。为了研究潜在的好处，我们制定了一个马尔可夫决策过程模型，我们使用一步前瞻近似来解决该模型。广泛的计算研究结果表明，考虑到与指导产能和保持库存相关的有效性，制造商在生产加速期间分配工作时应考虑劳动力的学习能力。结果分析表明，库存和能力建设模式取决于产品价值和劳动力的经验水平。进一步的分析表明，学习速度较慢的学习者和有可能实现更高生产力的学习者应该更加专业化。另一方面，更快的学习者最适合交叉训练。结果分析表明，库存和能力建设模式取决于产品价值和劳动力的经验水平。进一步的分析表明，学习速度较慢的学习者和有可能实现更高生产力的学习者应该更加专业化。另一方面，更快的学习者最适合交叉训练。结果分析表明，库存和能力建设模式取决于产品价值和劳动力的经验水平。进一步的分析表明，学习速度较慢的学习者和有可能实现更高生产力的学习者应该更加专业化。另一方面，更快的学习者最适合交叉训练。