GOALI/Collaborative Research: Capacity and Flexibility Investment Decisions in a Make-to-Order Environment

这个学术与工业联络合作资助机会（GOALI）项目将研究战略产能规划决策及其对订单环境下供应链的影响。该项目将构建分析模型，并开发将在通用汽车环境中进行测试的分析、数值和仿真方法，以指导研究方向，并确保其实用性和易于实施。为了在合理的交货时间内以有竞争力的价格为客户提供定制产品，企业需要转向按订单生产，在这种情况下，充足的产能决策比过去更加重要。订制策略要想取得成功，就需要合理平衡供需关系。这可以通过以下方式实现：(1)制造灵活性，以便在不同的产品之间共享产能；(2)价格灵活性，以便对需求进行管理；(3)交货时间灵活性，以便对时间敏感的客户的需求进行转移，以换取价格优惠。该项目将研究每一种杠杆对供应链绩效和产能需求的影响，为公司设计和管理按订单生产系统提供指导。此外，该计划还将整合产品和附加功能或选项（例如车辆和真皮座椅）的产能投资决策。在对这些选项进行容量分析时，需要考虑以下几个问题：(1)选项和车型容量决策是相互依赖的。(2)对各种期权的需求可能是相关的。(3)客户对不同选择的态度不同。例如，他们可能不会购买没有自动变速器的汽车，但可能会接受其他缺少的选项，例如化妆镜。这导致每个特定选项的产能过剩和产能不足的风险非常不同。因此，该项目将开发考虑客户偏好的容量定价决策模型。该研究将提供：(1)分析结果和见解，以更好地在订单环境下进行产能规划；(2)考虑不确定性、需求管理技术以及对运营供应链成本的影响的车辆和期权产能规划工具。此外，预计的结果是开发可用于广泛行业的通用模型，并通过在通用汽车公司实施/测试来展示其实际影响。

This Collaborative Grant Opportunity for Academic Liaison with Industry (GOALI) project will study strategic capacity planning decisions and their impact on the supply chain in a make-to-order environment. The project will construct analytical models and develop analytical, numerical, and simulation methods that will be tested in General Motors' environment to guide the research direction and ensure their practicality and ease of implementation. To provide their customers with customized products within reasonable lead-times at competitive prices, firms need to shift to make-to-order production where adequate capacity decisions are even more important than in the past. For a make-to-order strategy to be successful, supply and demand need to be reasonably balanced. This can be achieved through: (1) manufacturing flexibility, so that capacity can be shared among different products, (2) price flexibility, so that demand can be managed, and (3) delivery-time flexibility, so that demand coming from time-sensitive customers can be shifted in exchange for a price break. The project will study the effect of each of these levers on supply chain performance and on capacity requirements to offer guidance to companies on the design and management of their make-to-order production systems. In addition, the plan is to integrate the capacity investment decisions for products and additional features or options (e.g., vehicles and leather seats). Several issues need to be considered in the capacity analysis for these options: (1) The option and vehicle model capacity decisions are interdependent. (2) Demand for the various options might be correlated. (3) Customers have a different attitude towards different options. For example, they might not buy a car without an automatic transmission, but may accept other missing options, such as a vanity mirror. This leads to very different risks of over- and under-capacitizing for each particular option. Thus, the project will develop models that address capacity-pricing decisions considering customers' preferences.The research will provide: (1) Analytical results and insights for better capacity planning in a make-to-order environment, and (2) Tools for vehicle and option capacity planning that consider uncertainty, demand management techniques, and the impact on operational supply chain costs. Also, the projected outcome is to develop general models that can be used in a wide range of industries and demonstrate their practical impact by implementing/testing them at General Motors.