Strengthening the Foundation for a New Generation of Plant Operators

The Baby Boomer (born 1946-1964) plant operators who adopted and improved what are now modern manufacturing practices, designed reliability programs and installed most of the equipment in use today are retiring. And they are retiring soon. By 2030 all Baby Boomers will be 65 or older. 

While that doesn’t come as a surprise, the global Covid-19 pandemic has accelerated retirement creating a more urgent need to prepare rising leaders for the job ahead.  More than three million baby boomers retired in Q3 2020 than had done so in the same period of 2019 in the United States alone.

Incoming Gen X (born 1965 – 1980) and millennial (born 1981 – 1996) leaders are well equipped to leverage the latest technology advances to welcome in an era of advanced analytics and digital transformation, but the knowledge base being lost with retiring leaders is not to be underestimated.

We can think of it like building a house. Everything rests on the foundation. How it was designed, how it was poured, what was found underneath as it was dug, what materials were used, when it was built and how it was adapted all influence a foundation’s strengths, usefulness and longevity for different applications. New, and rising leaders are standing on the floor Baby boomers built.

Closing the knowledge gap lost with retiring experts is essential for moving forward effectively. To get us started, we’ve built a primer covering the basics related to maintenance strategies.

Let’s begin by looking at the four maintenance strategies a plant might deploy.

1. Reactive Maintenance (RM) – This type of maintenance is performed after a failure or after an obvious, unforeseen threat of immediate failure.  In reactive maintenance, assets are operated in a run-to-failure (RTF) mode, and daily maintenance activities are driven by unforeseen problems from assets breaking down without detection of the impending failure. This is an appropriate strategy for assets that have very low to no consequence of failure.  Example: Replace oil heater element when it fails.

2. Preventive Maintenance (PM) – These maintenance tasks are conducted at regular, scheduled intervals based on average statistical/anticipated lifetime to avoid failure.  This strategy may be effective for assets where the most probable failure pattern is “wear out”. Typical tasks include inspection, service and/or replacement of components. Scheduling intervals may be based on calendar periods or on actual operating time for the asset in question.  Example: Rebuild oil heater and replace elements after every 8000 operating hours.

3. Predictive Maintenance (PdM) – This maintenance is performed based on the actual asset condition (objective evidence of need) obtained from in-situ, non-invasive tests and operating and condition measurements.  It is also called Condition Based Maintenance (CBM). Example: Repair or replace oil heater element based upon changes to its as measured condition such as leaking, does not heat per design, reduced flow from design condition etc.

4. Proactive Maintenance – This is a program of continuous maintenance optimization based on feedback from Root Cause Failure Analysis (RCFA), quantitative PM’s, results of PdM routines, CM systems, technician feedback and operations input.  Feedback is used to update and optimize asset strategies and the resulting controls being deployed. Optimizing RCM, FMEA, RBI, Safety Instrumented Systems and Hazardous Operations asset management strategies drives and enables continuous improvement verse one off actions or tasks based upon PM and PdM findings. Example: Based upon RCFA and technician feedback, rewrite oil heater operating procedures to eliminate element burnout, perform PM Optimization to reduce intrusive inspections that have been determined to lead to early heating element failures and increase data sampling of element condition to provide early warning so maintenance can be planned a minimum of two weeks in advance.

As organizations move away from reactive maintenance, condition monitoring (CM) becomes an essential skill. Condition monitoring is the process of recording measurements that define asset condition without disrupting its normal operation.  Measured parameters include vibration, lubricant properties, electrical characteristics, thermal gradients, thermodynamic performance, etc.  Measured values are compared with established limits in order to initiate notification that further evaluation may be required.  CM is used to enable both predictive (PdM) and Proactive Maintenance strategies.

One of the main differences between PdM and Proactive Maintenance is that Root Cause Failure Analysis (RCFA) is used to make continuous improvements in a Proactive program.  In PdM, condition monitoring or Predictive information gives us warning of an impending failure, allowing us to plan ahead to procure repair parts; schedule a required outage, etc.  But if we never address the root cause of the failure, we may end up repeating the same failure cycle over and over. 

RCFA allows us to identify the fundamental cause(s) that, if corrected, will prevent recurrence of an event or adverse condition.  By actually implementing the findings of RCFA, we can break the cycle and improve the reliability and availability of the affected assets. In this model rather than implement one-off actions, recommendations are considered in the context of the main asset strategy itself informing both an immediate instruction, and informing longer term changes to address the root cause. Other differences can include feedback from the maintenance craftsmen executing the corrective actions, planning, and operations, alongside input from advanced analytics that can advise of what were in the past hidden failure modes and often times drove unplanned events. All of these should drive optimization of RCM, FMEA, RBI, Safety Instrumented Systems and Hazardous Operations asset management strategies.

The methodologies listed here are commonly used to evaluate possible failure modes and effects for assets and systems of interest.  Based on the results of these evaluations, appropriate mitigation strategies can be implemented.  These include the four Maintenance Strategies listed above, as well as additional measures such as engineered design changes and administrative procedures.

Reliability Centered Maintenance (RCM): A systematic, disciplined process to ensure safety and mission compliance that defines system boundaries and identifies system functions, functional failures, and likely failure modes for equipment and structures in a specific operating context.  RCM develops a logical identification of the causes and effects (consequences) of system and functional failures to arrive at an efficient and effective asset management strategy to reduce the probability of failure.  RCM is a rigorous and time-consuming process and is typically only applied at a system level to the assets that are highly critical and critical to the business.

Failure Modes & Effects Analysis (FMEA): A methodology for identifying the functions of an asset, ways it can fail to perform those functions, the causes of those failures, and the methods for detecting or mitigating those failures.  FMEA is applied at the asset level and as such is a simpler and less time-consuming process than RCM.  It is typically used to evaluate assets that have critical to mid-level criticality.

PM Templates: A collection of OEM, Equipment SME and or industry-accepted best practices for addressing the most common failure modes for a specific asset class – or if possible, sub-class.

When establishing effective monitoring strategies for an asset or system, it is important to consider the time that it takes for an identified failure mode to progress from its first possible detection to functional failure of the asset or system.  EXAMPLE: For typical wear out of a rolling element bearing, the deteriorating bearing condition can often be detected for a few months until the bearing finally fails.  With such a long failure cycle, it may be appropriate to monitor the bearing by taking monthly vibration measurements.

The figure below shows that the P-F interval, which is the interval between the occurrence of a potential failure (P) and the decay into a functional failure (F).  Time (on the x-axis) can be measured in seconds, minutes, days, months or years.  There may be many different failure modes for an asset and hence many failure cycles which demand different strategies to address each asset effectively. One key here is to understand what the desired P to F interval for your specific class, subclass of asset and most importantly asset criticality. We will talk about Criticality in an upcoming blog.  Understanding this is key to applying the right mitigation controls based upon the failure modes and the failure cycles. This introduces the concept of enabling proper planning and strategy optimization.

Note: Functional failure simply means that the system is no longer capable of performing its intended function.  For example, a pump that is required to produce 100 gpm flow at 200 psi discharge pressure is considered to have functionally failed if it can only produce 90 gpm at 200 psi.

Today, the top performers in industry are deploying more effective maintenance strategies, supported by technologies, resources, sound procedures with continuous optimization to keep their assets performing high on the P-F curve and delivering business value.