Collaborative Research: A Design Methodology for Operational Flexibility

该赠款为创建建模和数学计算方法提供资金，以量化服务和制造供应链的运营灵活性。它强调当生产来源（例如，工人、机器、工厂等）是多功能的。这方面的例子包括具有多种技能的工人，具有灵活或可重新配置能力的机器，以及具有灵活采购和分销选择的供应链。通过拥有多功能服务器（资源），可以动态分配容量以响应不确定需求的实现。以生产网络作为生产系统的模型，采用近似确定性的柔性度量来准确地预测各种方案中的最佳设计。数学规划，决策理论，马尔可夫决策过程和离散事件系统仿真。这项研究阐明了具有灵活服务器的一般网络与近似确定性网络模型中发现的属性之间的联系。如果成功，这项研究的结果将导致服务和制造业务以及供应链设计的改进，即使技术发生不确定变化，消费者期望提高，供应链的垂直整合减少，全球竞争加剧。本研究的主要目标是（1）开发量化灵活性的有效方法，（2）开发原则和方法，以更好地选择一个轮班（或工作时间）的灵活工人名册，从而形成一个强大的生产团队，（3）发明一种方法来帮助设计强大的多级供应链。本研究的预期成果是：（1）加深对如何设计真正灵活和稳健的生产系统和工人/人员安排的理解的管理见解;（2）用于分析和设计多级供应链的易处理的分析/数值模型和方法。 一旦实施，其结果将通过提高日常交易的服务质量帮助普通人，通过增加职业发展和培训帮助工人，通过改进管理做法和竞争性运作帮助企业。

This grant provides funding for the creation of a methodology for modeling and mathematical computation to quantify operational flexibility in service and manufacturing supply chains. It emphasizes the flexibility attained when sources of production (e.g., workers, machines, plants, etc.) are multi-functional. Examples of this include workers with multiple skills, machines with flexible or reconfigurable capabilities, and supply chains with flexible sourcing and distribution options. By having multi-functional servers (sources), capacity can be dynamically allocated in response to the realization of uncertain demand. Taking queueing networks as models of the production systems, approximate deterministic metrics of flexibility are used to accurately predict the best design from various alternatives. Mathematical programming, queueing theory, Markov Decision Processes, and discrete event systems simulation are employed. The research illuminates the connections between general queueing networks with flexible servers and the properties found in approximate, deterministic network models.If successful, the results of this research will lead to improvements in the design of service and manufacturing operations and supply chains that deliver high-performance efficiencies and service levels despite uncertain changes in technology, heightened consumer expectations, decreased vertical integration of the supply chain, and intensified global competition. The primary objectives of this research are to (1) develop effective methods for quantifying flexibility, (2) develop principles and methodology to better select a roster of flexible workers for a shift (or work period) that results in a robustly productive team, and (3) invent a methodology to assist in the design of robust multi-echelon supply chains. The anticipated results of this research are: (1) managerial insights that deepen the understanding of how to design production systems and worker/staffing schedules that are truly flexible and robust and (2) tractable analytical/numerical models and methods for the analysis and design of multi-echelon supply chains. Upon implementation, the results will help ordinary people through increased quality of service in everyday transactions, workers through increased career development and training, and businesses through improved management practices and competitive operations.