Reliability Calculation: How to Calculate Reliability?

What sets top-performing manufacturing plants apart from the rest?

The secret is in the way they combine maintenance and reliability activities, rather than using a one-size-fits-all approach across the whole organization. By focusing on the right areas, they manage to reduce downtime, improve productivity, and cut costs. But how do they strike the right balance?

The answer lies in understanding how to calculate reliability.

These calculations rely on data collection from many different sources. In the past, gathering this kind of data was a slow and labor-intensive process. However, with the rise of affordable Industrial Internet of Things (IIoT) devices, it’s now possible to gather real-time data on the health and performance of machines. These devices help track various metrics without the need for manual input.

Additionally, modern software solutions, like cloud-based computerized maintenance management systems (CMMS), make it easier to manage this data. These systems provide helpful dashboards and easy-to-read reports, allowing organizations to better monitor their equipment and improve overall performance.

What is Reliability?

Reliability refers to how likely a system is to keep working as expected over a certain period. For instance, if a system has a reliability of 0.9 over 100 hours, it means that there’s a 90% chance the system will still be operating after 100 hours. In other words, reliability measures the consistency of a system’s performance, giving you an idea of how dependable it is in the long run. This is important for understanding whether a system can continue to meet its purpose without breaking down.

The Impact of Reliability Calculations on Maintenance Strategy

Modern plants rely on various metrics to improve the reliability and maintenance of their equipment. These metrics help plant managers focus their efforts on the most important aspects of maintenance to keep operations running smoothly.

2 important metrics used in this process are Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR). 

MTBF measures the average time between failures, helping to predict when equipment is likely to break down. MTTR, on the other hand, tracks the average time it takes to repair equipment once it’s failed.

Other metrics, such as the system reliability formula, are also valuable tools for understanding how well assets are performing. By using these metrics, maintenance teams can make better decisions about how to allocate resources and improve the reliability of their systems.

Benefits of Using Reliability Calculations for Maintenance

Using reliability calculations for maintenance brings several benefits that can positively impact your operations, both in the short and long term. Here are some of the main advantages:

1. Better Equipment Performance

   When you regularly check and maintain your equipment, it runs more smoothly. This helps reduce wear and tear, which can prolong the life of your machinery and keep it working at its best.

2. Improved Safety

   By spotting and fixing potential problems before they escalate, you create a safer environment for everyone. Early repairs can prevent accidents, protecting both the equipment and the people who work with it.

3. Lower Costs

   Reliability-based maintenance helps focus resources on what really needs attention, instead of doing regular checks that might not be necessary. This helps to avoid extra costs and ensures that money is spent wisely.

4. More Time for Production

   By identifying issues early and performing repairs only when needed, you can avoid unexpected breakdowns. This means less downtime and more continuous production.

5. Smarter Decisions

   Having access to real-time data makes it easier for your maintenance team to make the right choices. With clear information about the condition of equipment, they can plan repairs more efficiently and improve the overall maintenance process.

Calculating Important Metrics for Reliability and Maintenance Teams

How to Calculate Mean Time Between Failure (MTBF)

MTBF is a way to measure how long an asset typically works before it breaks down again. To calculate MTBF, you divide the total amount of time the asset is working (its uptime) by the number of times it failed during that time. If the MTBF is low, it suggests that the asset is having frequent breakdowns and might require more attention or repairs.

On the other hand, if the MTBF is high, it means that the equipment can run for a longer time before it needs maintenance or breaks down. Knowing the MTBF helps decide whether to repair or replace equipment. If a machine has a low MTBF and is breaking down too often despite repairs, it might be more cost-effective to replace it. By keeping track of this, your team can focus on improving or replacing equipment that doesn’t respond well to fixes. It can also help in managing spare parts inventory, as knowing the MTBF can tell you when parts are more likely to wear out and need replacing.

How to Calculate Mean Time to Repair (MTTR)

MTTR tells you the average amount of time it takes to fix a piece of equipment and get it back to work. To calculate MTTR, you divide the total downtime (time the equipment was not working) by the number of repairs done. A lower MTTR means repairs are happening faster, which helps keep equipment running and reduces downtime.

How to Calculate Failure Rates

The failure rate of an asset changes over time. When the asset is new, it typically breaks down less frequently. But as it ages and gets closer to the end of its useful life, the chances of failure increase. To calculate the failure rate, you use the same data you would for MTBF. You divide the number of failures by the total number of hours the equipment was in use.

How to Calculate System Reliability

System reliability refers to how dependable an asset is, especially when that asset is made up of several parts. It measures the percentage of time that the whole system works without breaking down. To calculate system reliability, you need to know the failure rate of each part in the system. Once you have the failure rates, you can multiply them together to get the overall reliability of the system.

The formula for system reliability looks like this: R = (1 – F1) * (1 – F2) * (1 – F3) * (1 – F4) …

Where:

• R is the overall reliability of the system.
• F1, F2, F3, F4 are the failure rates of each part.

This gives you a good idea of how the system as a whole is performing. Understanding system reliability is useful for identifying which components are performing well and which ones might need more attention.By calculating and tracking these metrics, your maintenance team can make better decisions about which equipment to prioritize when to replace parts, and how to keep your assets running smoothly. These numbers help you see which machines are causing more problems, which ones are critical but might not show obvious signs, and ultimately how to improve your asset management strategy.

Improving Maintenance Through Reliability Calculations

• Condition Monitoring with IIoT Technology

  IIoT (Industrial Internet of Things) technology has changed how we monitor the condition of equipment. It’s made the process easier and more reliable. Smart sensors are now placed on important machinery to keep track of things like temperature, vibration, and power quality all the time. These sensors send real-time data, which can then be analyzed to spot any changes or issues in the equipment. By creating a baseline of normal performance, condition monitoring helps maintenance teams spot potential problems early.

  For example, if vibration levels go up, it could mean there’s an issue with a bearing starting to fail. Fixing these small issues before they turn into bigger problems helps avoid unplanned downtime and keeps repair times shorter. This way, maintenance work is done when needed, not too early or too late, improving the reliability of the equipment.

• Using Predictive Maintenance

  Condition monitoring data plays a major role in predictive maintenance, which is an approach that goes beyond just scheduled maintenance. With predictive maintenance, real-time data from sensors is used to predict when something might go 1wrong with the equipment before it actually happens. By looking at patterns and trends in the data, maintenance teams can figure out when a part is likely to fail and plan maintenance around that. This method helps in managing the equipment better by preventing sudden breakdowns and making machines last longer. Predictive maintenance reduces unnecessary routine checks and focuses on the real needs, which cuts down on maintenance costs. It also helps machines run longer without interruptions, making work more efficient and saving time for maintenance teams to focus on other tasks.

• Improving Maintenance Decisions with CMMS

  CMMS (Computerized Maintenance Management System) software helps maintenance teams stay organized by collecting, analyzing, and reporting data. It simplifies the process of making decisions about equipment care and repairs. The software typically has dashboards that display important data, like how often equipment fails (MTBF) and how long it takes to fix (MTTR). These visuals help maintenance managers understand the condition of their equipment and plan accordingly. By using CMMS, managers can decide which tasks need immediate attention, schedule maintenance more efficiently, and assign resources where they’re most needed. When CMMS is connected to IIoT (Industrial Internet of Things) devices, the system can automatically gather real-time data, making it easier to track equipment health and plan for repairs or replacements ahead of time.

Use NEXGEN to Keep Your System Working Seamlessly

Reliability and maintenance play an important role in keeping industrial operations running smoothly. Using reliability calculations along with modern maintenance methods can help factories boost productivity while also reducing maintenance costs. Adopting tools like IIoT devices and CMMS software allows for better collection and analysis of data, which helps in making more informed maintenance choices and improving the overall reliability of equipment.

NEXGEN’s EAM software helps organizations schedule preventive maintenance, identify which assets are most likely to fail based on risk and criticality and accurately predict equipment reliability, all while maintaining service levels.

Start improving your maintenance system today with a focus on efficiency and reliability with NEXGEN!