Analyzing Interdependencies between Factory Change Enablers Applying Fuzzy Cognitive Maps
Analyzing Interdependencies between Factory Change Enablers Applying Fuzzy Cognitive Maps
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DOI：
10.1016/j.procir.2016.07.015
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Sven Hawer;N. Braun;G. Reinhart
中科院分区：
文献类型：
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作者：
Sven Hawer;N. Braun;G. Reinhart
在动荡的企业环境中，变革的推动者对具有竞争力的制造系统发挥着重要作用。在设计工厂的过程中，企业面临着选择哪些使能者来处理市场引起的不确定性和模糊计划数据的决定。然而，目前的研究没有提供在实际生产系统中实施时这些促成因素如何相互影响的信息。本文首先在大量文献回顾和专家访谈的基础上，对相关的变革推动因素进行了概述，并根据其抽象程度对其进行了分类。为了建立一种选择可行促成因素组合的方法，开发了一种模糊认知地图来分析不同变革促成因素之间的模糊相互依赖关系。为了在工业实践中验证模糊认知图所建模的关系，提出了一个调查工具，并将其应用于工厂规划领域的企业。所开发的用于模拟改变使能者的相互依赖关系的方法使工厂计划者能够积极地选择相互积极影响的使能者的组合，从而允许在早期规划阶段对改变的工厂布局进行经济高效的设计。
Enablers of change play an important role for competitive manufacturing systems in a turbulent corporate environment. In the process of designing factories, companies face the decision of which enablers to choose for dealing with market-induced uncertainties and fuzzy planning data. Current research, however, does not provide information on how the enablers influence each other when implemented in real production systems. This paper first provides an overview of relevant change enablers and categorizes them with regard to their degree of abstraction, based on an intensive literature review and expert interviews. With the aim of creating a method for the selection of feasible enabler-combinations, a fuzzy cognitive map to analyze fuzzy interdependencies between the different change enablers is developed. To validate the relations modelled in the fuzzy cognitive map in industrial practice, a survey-tool is presented and applied in enterprises from the field of factory planning. The developed method for modelling change enablers’ interdependencies empowers the factory planner to actively select a combination of enablers that influence each other positively and thus allow for a cost-efficient design of changeable factory layouts in early planning stages.