Application of system dynamics for analysis of performance of manufacturing systems

被引:36
作者
Adane, Tigist Fetene [1 ]
Bianchi, Maria Floriana [1 ]
Archenti, Andreas [1 ]
Nicolescu, Mihai [1 ]
机构
[1] KTH Royal Inst Technol, Dept Prod Engn, Brinellvagen 68, S-10044 Stockholm, Sweden
关键词
Manufacturing system; Machining strategy; Performance evaluation; System dynamics modelling; Cutting data optimization; Process parameters interaction; RELIABLE PRODUCTION LINES; INTER STATION BUFFERS; THROUGHPUT RATE; SIMULATION; FUTURE; DESIGN;
D O I
10.1016/j.jmsy.2019.10.004
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Machining of parts by using dedicated production systems has been, and continues to be, a viable manufacturing method. There are situations, however, where this type of system is not feasible due to changes in product type, customer demand, work-piece material, or design specification. From a competitive manufacturing environment, production system selection is a crucial issue for all component manufacturing companies. Improper selections could negatively affect the overall performance of a manufacturing system, for instance the productivity, as well as the cost and quality of manufactured components. In this paper, the application of system dynamics modelling and simulation of a complex manufacturing process is presented as a potential tool to investigate and analyse the performance of manufacturing system in response to disturbances in the system's inputs (e.g., volume of products). In order to investigate the model soundness, a case study applied to the manufacturing of an engine block will be examined. The model presented here has been developed based on current engine block production for the vehicle manufacturing industry. Such a model can assist manufacturing system selection-centered round the capacity to control machining system parameters -as a testable way to choose a machining strategy from pre-selected performance criteria. More specifically, the benefit of this research lies in the fact that it will enable companies to implement improved potential manufacturing system optimization that responds during unexpected demand fluctuations. In addition, it will help in understanding the complex interaction between the process and operational parameters of a manufacturing system and help identify those critical parameters, ones that can lead to an optimizing strategy in the manufacturing standards of engine block production.
引用
收藏
页码:212 / 233
页数:22
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