Risk‐based approach for managing obsolescence for automation systems in heavy industries. Issue 6 (19th July 2022)

• Record Type: Journal Article
• Authors: Ault, Trevor; Bradley, Thomas
• Is Part Of: Systems engineering. Volume 25:Issue 6(2022)
• Page Start: 551
• Page End: 560
• Publication Date: 2022-07-19
• Subjects: cyber‐physical systems -- heavy industry -- obsolescence -- reliability -- risk; Systems engineering -- Periodicals; 620.0011
• DOI: 10.1002/sys.21635
• Languages: English
• ISSNs: 1098-1241

Abstract

Abstract: Obsolescence is an important consideration in the management and engineering of heavy industrial facilities. Examples of these could include refineries, chemical plants, and other large‐scale materials processing facilities. These facilities have lifetimes of many decades but operate on software, automation hardware, and other electrical equipment that reaches obsolescence much sooner than the rotating equipment, unit operations, and other major systems of the facility. This work proposes a method to manage obsolescence of automation and electrical systems at industrial sites. This risk management method was developed by first analyzing a database of upgrade projects at several industrial sites and identifying parts that had been replaced due to obsolescence. The analysis was used to prioritize replacement of obsolescent parts based on the average operational lifespans, their criticality in operations, their manufacturer's continued production state, and other factors. Based on those results, a taxonomy of obsolescence risk, and a risk assessment plan were developed to manage the replacement of parts. The value of this proposed management strategy was validated through its application to 13 heavy industrial facilities. The results indicate a reduction of roughly 70% in reactive replacements due to obsolescence after the major upgrade and a 24% reduction in unplanned downtime due to part failure during normal operations. While this study is focused on heavy industries, the proposed method for identifying and managing component obsolescence can be applied to other industries and systems.