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首页> 外文会议>IFAC Conference on Manufacturing Modelling, Management, and Control >One small change can lead to large complexity: a first glimpse at the Master Data change and its impact on the semiconductor supply chain
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One small change can lead to large complexity: a first glimpse at the Master Data change and its impact on the semiconductor supply chain

机译：一个小变化可能导致大复杂性：首次瞥见主数据变化及其对半导体供应链的影响

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摘要

Modern supply chain is a complex system characterized by an increasing number of interactive and interdependent components with dynamic behaviors working together as an entirety. The system complexity is not only determined by the internal mechanisms of the problem but is also affected by the changing environment. Much research and practice on complexity management is about the structural analysis, concentrating on the components and their interconnections. However, the measurement of dynamic changes has not gained much attention. Therefore, this paper proposes a framework to assess changes in supply chain. A conceptual model is employed to model the hierarchical supply chain and classify changes into different levels. One change scenario can be described as a group of atomic changes acting on the predefined elements and relationships. The impact rules of change are also provided. We thus propose an approach with four steps to evaluate the change impact. A practical example from supply chain Master data is used to illustrate this approach. It's a surprise to see a tiny change from the bottom level could have significant impact on the whole system. The research on change analysis will finally benefit the complexity measurement as an influence factor of metrics.
机译：现代供应链是一种复杂的系统，其特征在于越来越多的交互式和相互依存的组件，具有整体工作的动态行为。系统复杂性不仅由问题的内部机制决定，而且也受到变化环境的影响。复杂性管理的许多研究和实践是关于结构分析，集中在组件及其互连。然而，动态变化的测量并没有得到很多关注。因此，本文提出了一种评估供应链变化的框架。采用概念模型来模拟分层供应链并将变化分类为不同的级别。可以将一个变化场景描述为作用于预定义元素和关系的一组原子改变。还提供了影响的改变规则。因此，我们提出了一种方法，有四个步骤来评估变化影响。来自供应链主数据的实际示例用于说明这种方法。看到从底层的微小变化可能对整个系统产生重大影响是惊人的。改变分析的研究最终将使复杂性测量作为指标的影响因素。

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