A Data-based Approach for Quality Regulation

A Data-based Approach for Quality Regulation
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基于数据的质量监管方法

DOI:
10.1016/j.procir.2016.11.086
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发表时间:
2016
期刊:
Procedia CIRP
影响因子:
--
通讯作者:
Schmitt
Schmitt
中科院分区:
--
文献类型:
--
作者:
Schmitt

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在定制生产中,需要更复杂的工艺。公司面临着监控这些复杂过程的挑战,与大规模生产相比,这些过程的标准化程度较低,因此具有较高的不稳定性。质量管理已经开发了各种技术来处理不稳定性,如错误分析和过程监控,这些技术在大规模生产中得到了成功的实施。这些技术是基于因果关系的原则,是有效的识别,监测和调整的主要原因的错误在孤立的影响链。在定制生产中,消除主要的误差原因并不会导致生产质量的持续提高,因为由于要制造的产品不同,误差原因也不同。此外,定制生产的过程越来越意味着不可分割的相互依赖性。因此,质量沿着价值链的出现变得更加复杂,并且不能用因果关系原理的影响链来解释。因此,为了在复杂的生产中实现高质量,开发了基于数据的质量调节。本文概述了基于数据的质量监管以及其研究的必要性。之后,一种基于虚拟生产模型的方法,以验证合适的数据挖掘方法的数据为基础的质量监管。
In the customized production more complex processes are required. Companies are challenged by monitoring these complex processes which compared to mass production show a lower degree of standardization and are therefore characterized by higher instabilities. Quality management has developed various techniques to deal with instabilities such as error analysis and process monitoring, which are implemented successfully in mass production. These techniques are based on the principle of causality and are effective in identifying, monitoring and adjusting the main cause of error in isolated effect chains. Within the customized production the elimination of the main cause of error does not lead to a sustained improvement of production quality since causes of error differ due to varied products to be manufactured. Furthermore, processes in customized production increasingly imply immanent interdependencies. The emergence of quality along the value chain is thus getting more complex and can less be explained by an effect chain using the principle of causality. The data-based quality regulation is therefore developed in order to achieve high quality in complex production. This paper outlines the data-based quality regulation as well as its need for research. Afterwards, an approach based on a virtual production model to validate suitable data mining methods for the data-based quality regulation is provided.
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影响因子: 12.1
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