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

该合作助学金项目将研究战略产能规划决策及其在定做环境下对供应链的影响。该项目将构建分析模型并开发分析、数值和模拟方法，这些方法将在通用汽车的环境中进行测试，以指导研究方向，并确保其实用性和易于实施。为了在合理的交货期内以具有竞争力的价格向客户提供定制产品，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。要想让按订单生产战略取得成功，供需需要达到合理平衡。这可以通过以下方式实现：(1)制造灵活性，以便在不同产品之间共享产能；(2)价格灵活性，以便管理需求；(3)交货时间灵活性，以便可以转移来自对时间敏感的客户的需求，以换取价格优惠。该项目将研究每一种杠杆对供应链性能和能力要求的影响，以指导公司设计和管理其按订单生产的生产系统。此外，该计划将整合产品的能力投资决策和其他功能或选项(例如，车辆和真皮座椅)。在对这些方案进行能力分析时，需要考虑几个问题：(1)方案和车型的能力决策是相互依存的。(2)对各种选择的需求可能是相关的。(3)顾客对不同的选择有不同的态度。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择，如化妆镜。这导致每个特定选项的容量过大和容量不足的风险非常不同。因此，该项目将开发考虑客户偏好的能力定价决策模型。研究将提供：(1)分析结果和洞察力，以便在按订单生产的环境中更好地进行能力规划，以及(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选件能力规划工具。此外，预计的结果是开发可在广泛行业使用的通用车型，并通过在通用汽车公司实施/测试它们来展示它们的实际影响。

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.