Signs that your PM program is ineffective and inaccurate

A good preventive maintenance (PM) program is essential in ensuring an efficient and reliable plant, both in terms of operation and maintenance. Regardless of the industry, if your PM program is inaccurate or ineffective, it will most likely lead to increased expected and unexpected downtime, high maintenance costs, and ultimately reduced productivity and performance. Here are 4 signs that indicate if your existing PM is ineffective: 

1. Subjective Task Description: 

The easiest way to identify if your PM program is inaccurate or ineffective is to look at the content of your tasks. If most of your tasks look like “check pump” or “check motors,” this is a clear sign that your PM is most likely ineffective for several reasons.

Firstly, they lack clarity, leaving room for interpretation and resulting in inconsistent execution among technicians. This inconsistency can lead to unreliable maintenance practices, with some more experienced technicians performing a full inspection of the assets while less experienced ones might only glance at the assets.

Subjective descriptions often omit critical details about which specific components of the equipment should be checked, increasing the risk of overlooked issues. As a result, subjective tasks like “check pumps” and “check motors” often result in a relatively low number of outcomes in terms of potential failure findings.  

Subjective tasks can also lead to accountability problems, as it becomes challenging to determine whether technicians followed appropriate procedures or completed tasks to a satisfactory standard. Lastly, vague descriptions may inadvertently lead to the neglect of critical maintenance activities, increasing the likelihood of equipment breakdowns. 

“If most of your tasks look like “check pump” or “check motors”, your PM program is most likely ineffective”

To mitigate these issues, it is advisable to revamp your existing PM program with a Failure Mode-Based Maintenance strategy. The process of Failure Mode Based Maintenance (FMBM) focused on identifying all possible symptoms that assets and components may experienced in the event of a failure. When doing so, you will then be able to put in place maintenance tasks that will address specific failure modes rather than generic tasks that simply inspect the equipment, without covering any specific symptoms/failure mode.  

Example of Risk Penalty Number calculation for failure modes on a gearbox and their coverage before a PM Optimization exercise 

When doing so, it is advisable to make maintenance tasks as objective and detailed as possible, providing technicians with specific instructions, measurements with min/max, and criteria for equipment evaluation – in a way that the tasks are as little affected as possible by the person performing the task.

For example, a task such as “check pump” should be replaced by several objective tasks such “inspect oil level – it should be within the green zone of the gauge” + “Verify the packing adjustment of the pump shaft” + “inspect for leaks and excessive wear” + “check the pressure and flow measurements. Target flow 5 L/M, Target pressure 100 PSI”. Clear and objective task descriptions are crucial for maintaining equipment reliability, reducing downtime, and enhancing overall maintenance program effectiveness. 

2. Intrusive tasks

Another significant red flag in a PM program is the presence of intrusive tasks. A good example of typical intrusive tasks are “Tear-down inspection” and “Visual inspection of couplings”. Those tasks might seem valuable in theory, but they share a common drawback: they are intrusive, requiring the equipment to be stopped, resulting directly in productivity losses. 

The primary goal of a reliability and maintenance team is to maintain equipment performance and minimize downtime. Therefore, it’s essential to minimize intrusive and over-maintenance tasks in your PM program. With advancements in technology, there are often alternatives that can provide similar inspection outcomes without disrupting productivity. 

For example, instead of stopping equipment to inspect coupling rubber, consider a non-intrusive strobe light inspection. This allows you to accurately assess the coupling for cracks, deterioration, and discoloration while the equipment continues to run, therefore a similar outcome can be expected in terms of the inspection but affecting the equipment’s production and performance. Advanced technologies like vibration analysis, ultrasonics, and IR thermography can offer even more insights into equipment health than visual intrusive inspections. 

Furthermore, intrusive preventive maintenance (PM) inspections often involve disassembling or physically interacting with equipment or machinery to inspect and possibly repair or replace components. Often, those interventions introduce certain risks and challenges, including the potential for reinstallation issues and contamination. Here is a list of typical risks you are exposing your asset’s too when performing intrusive PMs: 

Reinstallation Risks: 

  • Misalignment: Reassembling equipment during inspections can cause misalignment, leading to issues. 
  • Torque Precision: Bolts, nuts, and fasteners need precise torque settings to prevent leaks or damage. 
  • Seal Problems: Disassembly can degrade seals, resulting in leaks and problems. 

Contamination Risks: 

  • Dust and Particles: Disassembly exposes equipment to contaminants, affecting components. 
  • Fluid Contamination: Opening systems with fluids can introduce moisture or foreign substances, reducing efficiency and causing damage. 
  • Cross-Contamination: Prevent mixing incompatible materials to avoid issues 

Therefore, even though your PM program is full of good intention, dismantling equipment to detect potential issues carries a significant risk of introducing new problems that didn’t exist initially, potentially leaving the assets in worse condition than prior to the intrusive inspection.

3. Lack of Predictive Maintenance and Data-Driven Insights

The absence of predictive maintenance (PdM) strategies and data-driven insights within a PM program can lead to over-maintenance tasks, compromising the overall effectiveness of both PM and PdM initiatives. 

Referring to what was mentioned in section #1, often the lack of predictive maintenance is due to the fact that the existing maintenance strategies where not elaborated on a failure-mode based approach – meaning that the maintenance team probably didn’t identify that unusual vibration, rise in temperature, rise in ultrasonics frequencies as potential symptoms, therefore not creating objective tasks to address those. Therefore, without predictive maintenance capabilities, organizations often rely solely on scheduled PM activities based on rigid calendar-based intervals. This approach can result in unnecessary maintenance on equipment still operating optimally, causing excessive downtime and labor costs.  

Example of PM Optimization done with regards to Risk Penalty Number calculated at failure mode level

Additionally, making maintenance decisions without real-time data-driven insights can lead to premature component replacements or repairs, draining resources needlessly. Common examples of over-maintenance tasks include “Bearing replacement” or “Chain replacement” added to the PM program after major unplanned downtime incidents. While these tasks may seem like prudent preventive measures, they will directly lead to increased planned downtime, shorten the components life which will directly lead to higher parts costs (consuming more parts within the same timeframe), and as mentioned above, the more human intervention your plant has, the higher is the potential introduction of new issues. 

In contrast, organizations in the top-performing quartile understand the importance of PdM technologies, such as condition monitoring sensors and predictive analytics. These technologies provide real-time data on asset health, enabling maintenance teams to pinpoint precisely when maintenance is needed. By detecting issues before they escalate, organizations can extend the life of their assets, reduce downtime, and optimize maintenance efforts. Failing to incorporate predictive maintenance and data-driven insights into a PM program can result in over-maintenance tasks, increasing costs and diminishing asset longevity.

4. Lack of Actual Findings

In essence, the primary goal of preventive maintenance (PM) is to proactively detect potential equipment issues before they escalate into costly failures. If your current PM program yields minimal results, it could be due to two reasons. First, your plant may be so reliable that technicians conducting inspections struggle to find any issues. Second, your PM program may mostly consist of subjective, intrusive, and non-data-driven tasks. In most cases, the outcome of a few potential failure identification is due to the second option. 

From our experience, we have detected a strange trend where some plants engage in deploying a PM program for compliance reasons rather than its true purpose. They may implement a basic preventive maintenance program just to fulfill a requirement, essentially checking a box to claim that they are running a PM program. However, PM programs should extend beyond mere checklist completion. Their fundamental aim is to uncover actionable insights that empower organizations to plan and execute corrective actions promptly. The goal is to have maintenance personnel who are not just checking boxes but actively contributing to the identification of potential failures.

Example of Data from APM tool

Technicians performing PM tasks are the eyes and ears of the organization. Their expertise enables them to detect anomalies and irregularities. Shifting the focus from routine tasks to proactive problem-solving allows organizations to maximize the utility of their workforce. Skilled technicians can help prioritize maintenance efforts, allocate resources efficiently, and reduce downtime, contributing directly to cost savings and operational excellence. 


In today’s labor-constrained environment, maximizing resource utilization is imperative. When PM tasks rely on subjective assessments rather than objective data and insights, inefficiency creeps in. Technicians may end up conducting unnecessary maintenance activities, consuming valuable time and resources that could be better allocated elsewhere. 

Preventive maintenance should not be a checkbox exercise. It should be a valuable tool for enhancing plant reliability, reducing costs, and optimizing resource allocation. Embracing data-driven, insight-oriented PM practices is essential. PM should be seen as a means to ensure that every minute of a technician’s time brings tangible value to the organization. 

Ultimately, the essence of PM lies in its capacity to uncover potential issues, allowing for timely corrective actions that prevent costly failures. In today’s labor-constrained environment, PM’s role is more critical than ever. Rather than just fulfilling obligations, PM should be viewed as a strategic investment in enhancing plant reliability, reducing costs, and ensuring that every minute of a technician’s time contributes to the organization’s success.

This article, entitled “Signs that your PM program is ineffective and inaccurate”, highlights the importance of an effective preventive maintenance (PM) program in keeping industrial plants running smoothly. It identifies four signs indicating potential ineffectiveness of the existing PM program: 

Subjective task descriptions: Vague tasks such as “check pump” leave room for varied interpretations, leading to inconsistent execution among technicians. This can lead to unreliable maintenance practices and poor problem detection. 

Intrusive tasks: Intrusive tasks, requiring equipment shutdown, lead to productivity losses. Non-intrusive inspection methods, such as stroboscope analysis, are recommended. 

Lack of predictive maintenance and data-driven analysis: The absence of predictive maintenance strategies leads to over-maintenance, costing time and money. Real-time data is essential for making accurate maintenance decisions. 

Lack of tangible results: If your PM generates few results, it may have been implemented primarily for compliance reasons, rather than to detect problems effectively. Technicians should focus on proactive problem detection. 

In conclusion, the article stresses that preventive maintenance should not just be a box to tick, but a strategic investment to improve plant reliability, reduce costs and optimize resource allocation. Priority should be given to data- and insight-driven maintenance practices to maximize the usefulness of technical manpower and prevent costly breakdowns. 

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