What is Mean Time Between Failures (MTBF) ?

Mean Time Between Failures (MTBF) holds significant importance as a performance indicator within the Facility Management sector. It enables the measurement of reliability levels in mechanical and electronic equipment, making it widely utilized in the industry.

For those unfamiliar with MTBF, this article provides comprehensive information on its meaning, importance, and functionality. It delves into the significance of this parameter and offers practical application examples to facilitate a better understanding of its correct calculation.

It is worth noting that the calculation of MTBF relies on the collection and analysis of data, which accurately depicts the behavior of assets over time. To effectively monitor an organization’s resources, the utilization of Facility Maintenance Management software is recommended. This essential tool not only facilitates the prediction of Mean Time Between Failures but also automates data recording for individual assets. Furthermore, it enables the evaluation of equipment performance indices, including MTBF, and aids in scheduling targeted interventions that extend the lifecycle of each component.

What is mean time between failures (MTBF)?

Mean Time Between Failures is a fundamental maintenance metric that represents the average duration between system breakdowns. It holds significant importance in evaluating the performance, safety, and design of critical or intricate assets such as generators or airplanes. MTBF serves as a measure of an asset’s reliability.

Moreover, MTBF plays a crucial role in calculating availability, alongside Mean Time to Repair (MTTR). By combining MTBF and MTTR, organizations can assess the overall uptime and reliability of their assets. It’s worth mentioning that the MTBF formula focuses solely on unplanned maintenance and doesn’t factor in scheduled maintenance tasks like inspections, recalibrations, or proactive parts replacements. By focusing on unplanned failures, MTBF provides insights into the inherent reliability and performance of assets under normal operating conditions.

Who uses MTBF?

Organizations that heavily invest in complex mechanical systems are the ones most likely to utilize key performance indicators (KPIs) such as mean time between failures (MTBF), Mean Time to Repair (MTTR), and planned maintenance percentage (PMP). These might include manufacturers, warehousing, mining companies, and oil and gas producers, all of which rely on KPIs to make sure their assets are working reliably and uninterrupted to meet deadlines, minimize downtime, ensure customer satisfaction, and maximize profitability.

Why is MTBF important?

MTBF rates are invaluable for operations and maintenance managers because they provide accurate insights into asset failures within specific timeframes. This information is often used in conjunction with other maintenance strategies and key performance indicators to effectively address recurring equipment failures at their source.

Implementing comprehensive preventive maintenance strategies that incorporate MTBF data brings two significant benefits. First, it allows managers to minimize unplanned downtime by scheduling routine upkeep at regular intervals, eliminating the need for costly emergency maintenance shutdowns. Second, it enables proactive maintenance planning, which helps to prevent expensive disruptions.

The impact of MTBF-informed maintenance systems cannot be overstated, as they can potentially save businesses hundreds of thousands of dollars compared to the high costs associated with extended periods of downtime. According to Aberdeen Strategy & Research, the average cost of downtime across all industries stands at a staggering $260,000 per hour.

MTBF assists maintenance departments in various essential tasks, including:

1. Optimizing Maintenance Schedules: MTBF serves as a baseline for maximizing PM schedules, enabling leadership to schedule maintenance activities proactively before failures occur. This approach ensures that technicians perform condition-based maintenance only when necessary.
2. Improving MRO Inventory: By tracking MTBF, managers can fine-tune their maintenance, repair, and operations inventory purchasing. Accurate forecasting of parts requirements leads to reduced repair costs, improved capital management, and faster repair times.
3. Asset Replacement: Determining whether to repair or replace critical equipment is often a challenging decision. MTBF plays a crucial role in this decision-making process, as it allows managers to calculate expected repair costs over time. By comparing these costs with the expense of purchasing new machinery, managers can identify the most cost-effective repurchasing date.

In addition, MTBF is a key performance indicator for reliability engineering, particularly in the design of critical assets. Maintenance engineers rely on MTBF data when designing safety, mechanical, and electronic systems to ensure optimal performance and reliability.

What does MTBF mean for maintenance?

Failure is a problem that requires thorough understanding for effective resolution. One way to gain insights and mitigate the impact of the failure is through the measurement and calculation of MTBF (Mean Time Between Failures). Performing an MTBF analysis empowers your maintenance team to reduce downtime, save costs, and work more efficiently.

Calculating the MTBF of an asset serves as a reference point for optimizing your preventive maintenance schedule. By understanding how frequently an asset fails, you can schedule preventive maintenance before reaching that point. This approach allows you to prevent failures while minimizing maintenance efforts and maximizing resource utilization. It’s a significant step towards adopting condition-based maintenance practices.

Taking it further, you can measure the MTBF for specific failures. This not only enables targeted preventive maintenance planning for those failures but also facilitates investigations into the root causes behind lower MTBF values. The causes could range from ambiguous task lists to faulty parts or inadequate training. Armed with this knowledge, you can identify and eliminate the underlying reasons for persistent failures.

MTBF optimization extends beyond preventive maintenance. It can also enhance inventory management by tracking this maintenance metric. Having an estimate of how long equipment will function before a failure occurs allows you to fine-tune MRO (Maintenance, Repair, and Operations) inventory purchasing. This understanding enables you to determine minimum quantities and lead times for achieving just-in-time delivery, resulting in cost savings and faster repair cycles.

Lastly, MTBF can simplify difficult decision-making processes. It is challenging to retire a piece of equipment and invest in a costly replacement. However, if all efforts to improve a low MTBF are unsuccessful, it may be more beneficial to replace the asset instead of continuously investing time and money in repairs. MTBF calculations can help weigh the costs of repair versus replacement, making a compelling case for new equipment acquisition.

How to calculate MTBF?

Mean time between failures is a value typically calculated over a period encompassing multiple failures, allowing for the determination of an arithmetic mean. It is important to note that MTBF is not a fixed value; patterns will change over time as an asset ages.

The bathtub curve provides a model that illustrates how the instantaneous failure rate evolves. In the early stages of an asset’s life, failures are more likely to occur frequently. Throughout most of its useful life, the failure rate remains relatively constant until the asset approaches the end of its lifespan, where the likelihood of failure increases once again. The bathtub curve offers an approximation of the average lifespan of an asset.

MTBF Formula:

MTBF = Total uptime / Number of failures

For instance, if an asset has operated for 2,000 hours in one year but experienced six breakdowns during that time, the MTBF for that asset would be 333 hours.

MTBF Example

To illustrate the concept, let’s consider a mechanical mixer designed to run for ten hours per day. In a scenario where the mixer experiences a breakdown after five days of normal operation, we can calculate the mean time between failures.

In this case, the MTBF is calculated by dividing the total operating hours (10 hours per day multiplied by 5 days) by the number of breakdowns (which is 1). Therefore, the MTBF for this example is 50 hours.

MTBF = (10 hours per day * 5 days) / 1 breakdown = 50 hours

What are some advantages of using MTBF?

Measuring the mean time between failures offers numerous advantages, such as:

1. Determining product life expectancy and assessing product reliability for manufacturers.
2. Identifying potential operational risks, enabling proactive maintenance and repair planning.
3. Assessing the quality of parts and materials used during production.
4. Serving as an indicator of the effectiveness of preventive maintenance and repair procedures.
5. Facilitating performance comparisons between different models and brands of the same product.

MTBF vs MTTF

Mean Time to Failure (MTTF) is a time-based metric that complements Mean Time Between Failures (MTBF) in assessing equipment reliability. While MTBF measures the average time between breakdowns, MTTF specifically focuses on non-repairable items. MTTF represents the duration before an item completely fails, indicating the maximum hours of service it can provide. Unlike MTBF, which considers repairable components, MTTF assumes that once this threshold is reached, the item has exhausted its operational lifespan. By considering both MTBF and MTTF, organizations can gain a comprehensive understanding of equipment reliability and plan maintenance strategies accordingly.

How to Improve MTBF?

Increasing the MTBF of your equipment can have a significant impact on reducing production losses and operational and maintenance costs. Here are several approaches to enhancing MTBF metrics:

1. Improve preventive maintenance (PM) Processes: Implementing an effective preventive maintenance program can greatly improve MTBF. Ensure that maintenance technicians are well-trained, equipped with relevant manufacturer manuals, and provided with comprehensive procedural preventive maintenance checklists.
2. Conduct Root Cause Analysis: Instead of relying on temporary fixes, invest more time in investigating the root causes of equipment failures. Utilize strategies like “The 5 Whys Technique” to identify and address the underlying reasons behind recurring failures, aiming for long-term solutions.
3. Understand Aging Assets: Aging equipment is a significant contributor to unplanned downtime. Equip maintenance professionals with knowledge and techniques to effectively manage aging assets and address preventable recurring issues.
4. Adopt Predictive Maintenance (PdM): PdM utilizes technology-based diagnostics, such as vibration analysis, temperature monitoring, pressure measurements, speed monitoring, and voltage checks. By collecting real-time data and employing problem-solving flowcharts, Predictive maintenance helps determine the optimal timing for maintenance actions, detecting signs of declining performance or imminent failure.
5. Streamline Data Collection: Accurate equipment data is crucial for meaningful MTBF metrics. Utilize sensor devices integrated with computerized maintenance management system (CMMS) platforms to collect reliable data on PM repair dates, parts usage, and associated costs. Cloud-based solutions like MaintainX provide a robust platform for storing and managing this data.

Additionally, using quality replacement parts adhering to manufacturers’ suggested parameters, maintaining comfortable working conditions, and implementing solid onboarding programs for machine operators all contribute to improving MTBF and overall equipment reliability.

How can a CMMS help with MTBF?

A Computerized Maintenance Management System (CMMS) provides the capability to maintain a comprehensive maintenance log, documenting each maintenance instance for individual assets. With a CMMS in place, unplanned downtime resulting from breakdowns can be systematically tracked to calculate Mean Time Between Failures. This maintenance management software facilitates the collection of detailed information on breakdowns, encompassing root cause analysis, countermeasures, corrective actions, and preventive measures. Additionally, it supports the capture of failure modes through issue codes and failure codes, enabling a thorough understanding of asset performance.

By utilizing NEXGEN CMMS software, the system records the date and time when a piece of equipment is reported as inactive for repair purposes. The software then calculates the duration it takes to restore the asset to its normal operating condition, giving rise to another key metric known as Mean Time To Repair (MTTR). It’s important to note that MTBF can only be accurately calculated by collecting data over time, highlighting the significance of utilizing a CMMS for this purpose. The ability to track maintenance activities and analyze downtime data through a CMMS provides valuable insights for optimizing maintenance processes and improving asset reliability.

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