Collaborative Research: A Design Methodology for Operational Flexibility

这笔赠款为建立一种建模和数学计算方法提供资金，以量化服务和制造业供应链中的业务灵活性。它强调在生产来源(例如，工人、机器、工厂等)都是多功能的。这方面的例子包括拥有多种技能的工人、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项的供应链。通过拥有多功能服务器(源)，可以响应于不确定需求的实现而动态分配容量。以排队网络作为生产系统的模型，利用近似确定性柔性度量从各种方案中准确地预测出最佳设计方案。运用了数学规划、排队论、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排队网络与近似确定性网络模型中的特性之间的联系。如果成功，这项研究的结果将导致服务和制造运营以及供应链的设计得到改进，尽管技术的变化不确定，消费者的期望更高，供应链的垂直整合减少，全球竞争加剧，但这些运营和供应链仍能提供高性能的效率和服务水平。这项研究的主要目标是：(1)制定有效的方法来量化灵活性，(2)制定原则和方法，以更好地选择轮班(或工作期间)的灵活工人花名册，从而产生一个稳健的生产力团队，以及(3)发明一种方法，以协助设计稳健的多梯队供应链。这项研究的预期结果是：(1)管理洞察力，加深了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，以及(2)用于分析和设计多层次供应链的易于处理的分析/数值模型和方法。实施后，这些成果将通过提高日常交易中的服务质量来帮助普通人，通过增加职业发展和培训来帮助工人，通过改进管理实践和竞争性运营来帮助企业。

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.