An approach based on fuzzy sets for manufacturing system design
针对中小企业制造系统设计中的信息不完美问题，提出基于模糊集理论的方法，用模糊逻辑聚合需求、部署方案，并用可能性理论分级评估预期性能，帮助工程师灵活实现系统并持续改进。
The aim of this work is to provide Small and Medium Enterprises (SMEs) with adapted design methods for manufacturing systems. In a total quality strategy, the design activity consists of searching for the means able to satisfy all users' needs from company customers to floor plant workers. That includes usual costs, delays and quality targets but also employees' involvement. Due to the variety of data sources and to the continuous changes of goals, the information is imperfect. The main concerns are uncertainty, inaccuracy and vagueness of both objectives and solutions. The fuzzy set theory provides a quite convenient framework to represent all those imperfections using one mathematical objet. Fuzzy logic is used to aggregate specifications and to deploy solutions. Possibility theory finally allows a graded evaluation of expected performances. The obtained result is graded, providing the engineer with some degrees of freedom for the realization of the manufacturing system. The valuation of the design quality is an undeniable progress towards the continuous improvement of the whole system performance. Finally, such a criterion may also be used for an empirical search for a convenient solution, as for the automatic computation of an optimal result.