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

这个学术联络与工业（GOALI）项目的合作赠款机会将研究战略能力规划决策及其对供应链的影响，在一个按订单生产的环境。 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。为了使按订单生产的战略取得成功，供应和需求需要合理平衡。这可以通过以下方式实现：（1）制造灵活性，使生产能力可以在不同的产品之间共享;（2）价格灵活性，使需求可以得到管理;（3）交货时间灵活性，使来自对时间敏感的客户的需求可以转移，以换取价格突破。 该项目将研究这些杠杆中的每一个对供应链绩效和能力要求的影响，以便为公司设计和管理其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的容量投资决策（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的几个问题是：（1）方案和车型能力决策是相互依赖的。(2)对各种备选方案的需求可能是相互关联的。(3)客户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失的选项，如化妆镜。这就导致了每一个特定选项的能力过剩和能力不足的风险非常不同。因此，本项目将开发考虑客户偏好的能力定价模型，并提供：（1）在按订单生产环境下更好地进行能力规划的分析结果和见解;（2）考虑不确定性、需求管理技术和对运营供应链成本的影响的车辆和选项能力规划工具。 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.