GOALI: Modeling Product Variety Induced Manufacturing Complexity for Assembly System Design

该奖项的目的是开发多阶段、混合模型装配系统中产品多样性引起的制造复杂性的数学模型，并深入了解这种复杂性对系统性能的影响。这项研究将由密歇根大学的教职员工和学生以及通用汽车研发制造系统实验室的研究工程人员合作进行，通用汽车的汽车组装厂将积极参与。具体地说，将建立多阶段模型，通过考虑每个站点引起的选择复杂性和上游站点传递的复杂性来表征复杂性的传播。将开发贝叶斯网络(BN)模型，以量化复杂性对系统性能的影响，包括质量和操作员生产率。验证后，开发的复杂性模型将用于改进装配系统设计，并综合制造系统开发中复杂性管理的指导方针。产品多样性导致的制造复杂性是当今所有制造商面临的一个关键问题？S竞争的环境，因为制造商正在开发定制产品来响应个性化需求。因此，拟议的研究将具有广泛的潜在好处，因为所开发的模型、算法和指南将能够帮助制造系统设计人员在设计制造系统时管理复杂性，这将导致操作员和系统性能的改善。学生将在通用汽车担任实习生，从而直接协助技术转让。研究成果还将通过密歇根大学的技术增强学习计划，在全球范围内提供面向设计和制造的装配建模研究生课程的模块。

This objective of this award is to develop mathematical models on product variety induced manufacturing complexity in multi-stage, mixed model assembly systems and gain insights on the impact of such complexity on system performance. This research will be pursued collaboratively by faculty and students at the University of Michigan and research engineering staff at General Motors R & D Manufacturing Systems Laboratory with active participation from GM vehicle assembly plants. Specifically, multi-stage models will be developed to characterize the propagation of complexity by considering the choice complexity induced at each station and the transferred complexity from the up-stream stations. Bayesian network (BN) models will be developed to quantify the impact of the complexity on the system performance, including quality and operator productivity. When validated, the developed complexity models will be applied to improve assembly system design and synthesize guidelines for managing complexity in manufacturing system development. Product variety induced manufacturing complexity is a critical problem faced by all manufacturers in today?s competitive environment as manufacturers are developing customized products to respond to individual needs. As such, the proposed research will have broad potential benefits in that the developed models, algorithms, and guidelines will be able to assist manufacturing system designers in managing complexity when designing manufacturing systems, which will result in improved operator and system performance. Students will serve as interns at GM, thus directly assisting in the transfer of technology. Research results will also be developed into modules for a graduate course in ?Assembly Modeling for Design and Manufacturing?, offered globally through the University of Michigan technology enhanced learning program.