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Application of a Taguchi-fuzzy approach for prediction of maintenance-production workforce parameters of manufacturing systems

机译:Taguchi模糊方法在预测制造系统维护生产劳动力参数中的应用

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Maintenance workforce evaluation has recently received increased attention due to its significant positive influence on manufacturing. Much theoretical and practical work has been done in this area. However, its optimisation considering uncertainties has not been adequately addressed. The current study develops a novel approach providing an understanding of the uncertainties while including factors for workforce size determination using an integrated Taguchi-fuzzy technique. The feasibility of a fuzzy maintenance workforce model as an expert tool was investigated and the results were validated using a literature model. The current study observed that the developed fuzzy workforce prediction and optimisation tool can be used to avoid complex mathematical expressions for workforce size prediction. Compared to ARIMA, the model offers comparable results and can be easily used by maintenance mangers.
机译:由于维护劳动力评估对制造业具有重要的积极影响,因此最近受到了越来越多的关注。在这一领域已经完成了许多理论和实践工作。但是,考虑到不确定性的优化尚未得到充分解决。当前的研究开发了一种新颖的方法,可提供对不确定性的理解,同时包括使用集成的Taguchi模糊技术确定劳动力规模的因素。研究了模糊维护劳动力模型作为专家工具的可行性,并使用文献模型对结果进行了验证。当前的研究表明,开发的模糊劳动力预测和优化工具可用于避免劳动力规模预测的复杂数学表达式。与ARIMA相比,该模型可提供可比的结果,并且可以由维护经理轻松使用。

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