Why Asset Integrity Is Still the Most Difficult PSM Element
CCPS Global Summit on Process Safety
2017
4th Global Summit on Process Safety
2017 Global Summit on Process Safety
Asset Integrity Management, Aging Facilities & Facility Siting I
Tuesday, September 12, 2017 - 2:15pm to 2:40pm
4th CCPS Global Summit on Process Safety
September 12-13, 2017
Okayama, Japan
Why Asset Integrity Is Still The Most Difficult PSM Element
Michael J. Hazzan, P.E., CCPSC, CPSA
Martin R. Rose, CCPSC, CPSA
Richard A, Santo CCPSC, CPSA
AcuTech Consulting Group
1919 Gallows Rd. Suite 900
Vienna, Virginia, USA 22182
Abstract
The quality and health of asset integrity (AI) programs (or Mechanical Integrity (MI) as it is known in some organizations) has improved since Process Safety Management has formally been implemented. But it is still a difficult process safety element to develop and implement. The results of process safety audits still show that AI/MI usually has the highest number of findings, and in the regulatory arena this element receives a large number of citations. Major process safety events have involved mechanical integrity failures.
In many respects, it is still the âlast frontierâ of process safety and has been the last element to be fully addressed. This is not to say that inspection, testing, and preventive maintenance programs do not exist at facilities with process safety programs, nor that the maintenance programs at these facilities are âbreakdown-onlyâ programs. Preventive and predictive maintenance programs have existed in the chemical/process industry for many years. What has been lacking in some cases are complete integrated MI management system programs that address all of the sub-elements of AI/MI. There are several reasons for this continuing situation:
- · When process safety regulations include AI/MI, they are typically written in very broad, performance-based language â even more so than other process safety elements. Certainly this is true in the U.S. in OSHAâs PSM Standard). Interpretation of these broadly stated AI/MI requirements and the matching of these requirements to actual facility policies, practices, and procedures has been a difficult process.
- · Defining which recognized and generally accepted good engineering practices (RAGAGEP) apply in the AI/MI program and how they are interpreted and used is not a simple process. This is because RAGAGEPs do not exist for all equipment types, particularly for inspection, testing, and preventive maintenance activities. The status of old RAGAGEPs that are no longer published or maintained is also a complication that needs to be resolved. RAGAGEPs are also referred to as codes and standards by some.
- · There is still a distinct impression by some that AI/MI means only preventive maintenance and therefore MI is assigned solely to the Maintenance Department/Group. Actually, AI/MI includes a wide variety of tasks and activities, therefore the responsibilities for AI/MI activities are spread widely across the facility and many of these personnel may not realize that their job includes an activity that is part of the AI/MI program.
- · There is also a lingering impression that AI/MI applies only to fixed equipment. This is not true, as rotating equipment, instrument/electrical equipment, and key utility systems are also important to process safety and therefore deserve full consideration in an AI/MI program.
- · AI/MI activities cover the entire life cycle of the covered equipment, not just the ongoing maintenance activities, and therefore many requirements of the AI/MI element may not be completely implemented.
- · Finally, the prevailing process safety culture has a profound effect on the success or failure of an AI/MI program, and a sound underlying culture must be in place first.
This article will explore these issues, including the interpretation issues that challenge many companies, the responsibilities of various site personnel for executing AI/MI activities, typical weaknesses in AI/MI programs, and the effect of the prevailing process safety culture. It is hoped that the information contained herein will clarify these points and thereby help sites to improve their AI/MI programs.