Manufacturing systems are becoming increasingly complex as more advanced and emerging technologies are integrated into the factory floor to yield new processes or increase the efficiency of existing processes. As greater complexity is formed across the factory, new relationships are often generated that can lead to advanced capabilities, yet produce unforeseen faults and failures. Industrial robot arm work cells within the manufacturing environment present increasing complexity, emergent technologies, new relationships, and unpredicted faults/failures. To maintain required levels of productivity, process quality, and asset availability, manufacturers must reconcile this complexity to understand how the health degradation of constituent physical elements and functional tasks impact one another through the monitoring of critical informative measures and metrics. This article presents the initial efforts in developing a novel hierarchical decomposition methodology. The innovation in this method is that it provides the manufacturer with sufficient discretion to physically deconstruct their system and functionally decompose their process to user-defined levels based upon desired monitoring, maintenance, and control levels. This enables the manufacturer to specify relationships within and across the physical, functional, and information domains to identify impactful health degradations without having to know all possible failure modes. The hierarchical decomposition methodology will advance the state of the art in terms of improving machine health by highlighting how health degradations propagate through the relationship network prior to a piece of equipment compromising the productivity or quality of a process. The first two steps of the methodology, physical decomposition and functional decomposition, are defined in detail and applied to a multi-robot work cell use case.

中文翻译：

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开发分层分解方法以提高制造过程和设备健康意识

随着更先进和新兴的技术被集成到工厂车间以产生新流程或提高现有流程的效率，制造系统变得越来越复杂。随着整个工厂形成更大的复杂性，通常会产生新的关系，这些关系可能导致先进的能力，但会产生不可预见的故障和故障。制造环境中的工业机器人手臂工作单元呈现出不断增加的复杂性、新兴技术、新关系和不可预测的故障/故障。为了保持所需的生产力、流程质量和资产可用性水平，制造商必须调和这种复杂性，以通过监控关键的信息性措施和指标来了解组成物理元素的健康退化和功能性任务如何相互影响。本文介绍了开发一种新颖的层次分解方法的初步努力。这种方法的创新之处在于，它为制造商提供了足够的自由裁量权，可以根据所需的监视、维护和控制级别对他们的系统进行物理解构，并将其过程功能分解为用户定义的级别。这使制造商能够指定物理、功能和信息域内部和之间的关系，以识别有影响的健康退化，而无需知道所有可能的故障模式。分层分解方法将通过突出显示健康退化如何在设备损害过程的生产力或质量之前通过关系网络传播，从而在改善机器健康方面推进现有技术。该方法的前两个步骤，物理分解和功能分解，被详细定义并应用于多机器人工作单元用例。