Developing a Hierarchical Decomposition Methodology to Increase Manufacturing Process and Equipment Health Awareness

Published

March 23, 2018

Author(s)

Brian A. Weiss, Michael E. Sharp, Alexander S. Klinger

Abstract

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; and enables the manufacturer to develop relationships within and across the physical, functional, and information domains to identify impactful health degradations without having to know all possible failure modes. The first two steps of the methodology, physical decomposition and functional decomposition, are defined in detail and applied to a manufacturing multi-robot work cell use case.

Citation

Journal of Manufacturing Systems

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.jmsy.2018.03.002

Keywords

Control, Diagnostics, Maintenance, Manufacturing Process, Monitoring, Prognostics, Robotics, Smart Manufacturing

Citation

Weiss, B. , Sharp, M. and Klinger, A. (2018), Developing a Hierarchical Decomposition Methodology to Increase Manufacturing Process and Equipment Health Awareness, Journal of Manufacturing Systems, [online], https://doi.org/10.1016/j.jmsy.2018.03.002 (Accessed November 21, 2024)