Fixing your maintenance strategy with planned maintenance optimization (PMO) and FMEA

In industrial maintenance, a broken maintenance strategy can be frustrating and costly. Despite the resources poured into preventive maintenance (PM) (opens in new tab), equipment breakdowns still occur more frequently than expected. A poorly optimized maintenance strategy often leads to unscheduled downtime, which can be extremely costly. For instance, in the manufacturing sector, unscheduled downtime can cost companies up to $260,000 per hour (opens in new tab).

This paradox often arises because either work is done incorrectly, or too much maintenance is performed in the first place. Surprisingly, what’s labeled as preventive maintenance can sometimes have the opposite effect, contributing to equipment failures instead of preventing them.

Why is maintenance strategy optimization crucial?

Planned maintenance optimization (PMO) strategies is essential for maximizing equipment reliability, reducing downtime, and minimizing operational costs. A well-optimized strategy (opens in new tab) ensures that resources are being used efficiently, focusing on the most critical assets and maintenance tasks that have the highest impact on performance. Not only does it save money, but it also improves the lifespan of machinery (opens in new tab) and ensures smoother operations. With organizations increasingly facing the challenge of balancing maintenance costs with the need for high uptime, strategy optimization becomes crucial for long-term success.

Key elements of an effective maintenance strategy

A successful maintenance strategy should include a mix of reactive (opens in new tab), preventive (opens in new tab), and predictive (opens in new tab) approaches, tailored to the needs of specific equipment. Reactive maintenance is often necessary for unforeseen breakdowns, but relying solely on this approach can lead to high costs and equipment downtime. Preventive maintenance (PM) involves scheduled checks to avoid potential failures, but it’s only effective when optimized. Predictive maintenance leverages data to anticipate failures before they occur, allowing teams to act at the right time.

Combining these strategies, driven by data and continuous improvement, is key to an optimized approach. The goal is to strike a balance where the right tasks are completed at the right time, using the fewest resources while providing maximum value.

Get the guide to choosing your maintenance strategy (opens in new tab)

Reactive, preventive and predictive maintenance: Which is best?

Below is a table that highlights reactive, preventive and predictive maintenance approaches, their pros and cons, best use for and industry examples:

Steps to optimize your maintenance strategy

Optimizing a maintenance strategy starts with a detailed assessment of current processes. By analyzing existing maintenance schedules, failure data, and equipment performance, organizations can identify areas for improvement. Next, planning involves prioritizing maintenance tasks based on asset criticality and failure risk.

From there, organizations can implement preventive maintenance optimization techniques, including reliability centered maintenance (RCM) and failure mode and effects analysis (FMEA). FMEA is a step-by-step risk management process and analysis tool for identifying where, when, how, and why a failure might occur in a design, manufacturing, or assembly process for a product or service. It determines the impact of different failures to identify the parts of the process that need to change.

These methods provide a systematic way to identify potential failure modes and optimize the maintenance schedule accordingly.

Continuous monitoring and adjustment ensure that the strategy stays relevant and effective over time. The process is iterative, ensuring that improvements are ongoing and aligned with operational goals.

Discover different maintenance strategies and how to use them (opens in new tab)

Leveraging technology for maintenance strategy optimization

Modern technologies such as CMMS (computerized maintenance management systems), IoT sensors, and data analytics play a crucial role in optimizing maintenance strategies. A CMMS helps track maintenance activities, providing valuable insights into equipment performance, work order history, and failure trends. IoT sensors can provide real-time data on equipment conditions, enabling predictive maintenance to prevent failures before they occur. This integration of technology ensures that maintenance strategies are data-driven, proactive, and highly efficient.

Measuring success and continuous improvement

Once an optimized maintenance strategy is in place, measuring its success is crucial. Key performance indicators (KPIs) such as equipment uptime, maintenance cost per asset, and mean time between failures (MTBF) provide insight into the effectiveness of the strategy. Regular assessments and continuous improvements ensure that the strategy remains effective, delivering long-term benefits in reliability, efficiency, and cost savings.

In summary, optimizing your maintenance strategy through a structured approach, leveraging technology, and continuously improving is the key to preventing equipment failures and enhancing operational efficiency. By embracing techniques like PM optimization and FMEA, organizations can ensure that their maintenance strategies are both effective and efficient, providing lasting value to the bottom line.