Design of manufacturing systems for product variety using cluster and statistical analysis

使用聚类和统计分析设计产品多样性的制造系统

• 批准号: RGPIN-2017-04858
• 负责人: Li, Simon
• 金额: $ 1.53万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636716
• 关键词: Design; manufacturing; systems; product; variety

The scope of this research program is the optimization of manufacturing systems to support product variety and sustainability. To stay competitive in the market, original manufacturers (OM) need to satisfy customers with more product options and meet the environmental regulations and societal expectations. In this context, while formal optimization models have been widely used in system design, they often face the challenges of model and computational complexity (e.g., high number of integer variables and convergence issues). Instead of employing optimization methods, this research will investigate and develop clustering and statistical techniques for the design of manufacturing systems. The novelty is to develop a bottom-up approach to address complex structural decisions systematically with the target of better performance on solution convergence and computing time, as well as comparable optimality performance with metaheuristic algorithms.

该研究计划的范围是制造系统的优化，以支持产品的多样性和可持续性。为了在市场上保持竞争力，原始制造商（OM）需要满足客户更多的产品选择，并满足环境法规和社会期望。在此背景下，虽然形式优化模型已广泛用于系统设计中，但其通常面临模型和计算复杂性的挑战（例如，大量整数变量和收敛问题）。而不是采用优化方法，本研究将调查和开发集群和统计技术的制造系统的设计。新颖之处在于开发了一种自下而上的方法来系统地解决复杂的结构决策，其目标是在解的收敛性和计算时间上具有更好的性能，以及与元启发式算法具有可比的最优性能。