Unlock the True Potential of Predictive Maintenance in Manufacturing

The manufacturing industry is a fast-growing sector, expected to continue expanding in the next few years. However, there are some complex internal challenges that every manufacturing industry faces today. One such challenge, which has a great impact on the industry’s production line, is downtime. Each and every production and manufacturing sector faces machine failures and downtime practically every day. People may think that machine repair, failure, or breakdown is a normal occurrence in the manufacturing industry.

It’s just a bitter truth when people are handling machinery that performs repetitive tasks. However, it is essential to remember that every second a machine is running earns money. Just think for a while—if a machine sits idle for a prolonged time, you can’t complete your order on time, lose your reputation, and ultimately face a drawback in ROI. No matter what the failure is, it can bring about delays in overhauls, dissatisfied customers, and potential losses in productivity and income.

Then what is the solution for this problem? The answer is Predictive Maintenance. In this article, let us explore how predictive maintenance in the manufacturing industry allows manufacturers to lower maintenance costs, extend equipment life, and reduce downtime.

What’s wrong in reactive maintenance?

Most industries today either follow a fixed maintenance schedule based on manufacturer recommendations or repair machines only after they fail. While this approach may seem practical, it is no longer sufficient in today’s competitive industrial environment. Reactive maintenance often fails to keep systems running optimally and can lead to safety risks and inefficiencies.

Key Reasons Reactive Maintenance Fails:

• Unpredictable Downtime: Machines fail unexpectedly, causing production delays and lost revenue.
• High Costs: Emergency repairs are often more expensive than planned maintenance.
• Safety Risks: Sudden breakdowns can endanger workers and compromise operational safety.
• Maintenance Backlogs: Constantly reacting to failures strains maintenance teams and slows overall productivity.
• Inefficient Resource Allocation: Time and resources are spent addressing urgent failures rather than strategically maintaining critical assets.

Preventive Maintenance: A Step Ahead, But Not Enough

Preventive Maintenance (PM) is a proactive approach where maintenance tasks are performed at scheduled intervals, regardless of the actual condition of the equipment. This method helps reduce unexpected breakdowns compared to reactive maintenance but often leads to unnecessary servicing, increased labor costs, and potential over-maintenance. Since preventive maintenance is based on predefined schedules rather than real-time equipment data, it does not always align with the actual wear and tear of the machinery, making it less efficient in optimizing maintenance resources.

Predictive vs. Preventive Maintenance

While both Predictive Maintenance (PdM) and Preventive Maintenance (PM) aim to reduce downtime and improve equipment reliability, they operate differently:

• Preventive Maintenance (PM) is based on a fixed schedule, meaning maintenance is performed whether the machine needs it or not. This can result in unnecessary servicing and increased costs.
• Predictive Maintenance (PdM) relies on real-time data, continuously monitoring machine conditions to predict failures before they occur. This optimizes maintenance schedules, reduces costs, and extends equipment lifespan.

While PM follows a one-size-fits-all schedule, PdM is data-driven and tailored to the actual condition of the equipment—ensuring smarter, cost-effective maintenance!

Following is a simple snapshot of Predictive maintenance vs Preventive maintenance:

Why Predictive maintenance is key?

Predictive Maintenance is an operation wherein the maintenance demand and prerequisite of machinery in a production line/shop floor are forecasted. That is, the machine failure will be predicted & fixed before it occurs. In contrast with reactive maintenance, predictive maintenance makes use of acquired data from each machine based on its normal pattern of operation or performance. Any tiny or precise variation or instability with the threshold data identified by sensors will fire up subsequent alerts so that production managers can reasonably anticipate the requisite for maintenance work.

By addressing potential failures in advance, PdM not only minimizes downtime and prevents costly breakdowns but also delivers a measurable return on investment (ROI). Studies show that manufacturers can reduce maintenance costs by 10-40% and increase asset lifespan by 20-30% with PdM. The ability to optimize maintenance schedules based on real-time data translates into lower operational costs, improved productivity, and enhanced overall equipment efficiency (OEE), leading to greater long-term savings.

Major Advantages of Predictive Maintenance

The major advantages, the predictive maintenance can provide for manufacturing industry are

• Limits unplanned downtime
• Optimize planned downtime
• Maximize equipment lifetime
• Reduce maintenance Expenses

Let us see the above advantages in brief.

1. Limits unplanned downtime

Unplanned Downtime costs manufacturers approximately $22k per minute and almost every industry loses 10 to 30% of productivity. Therefore, unforeseen failures are one of the key players in maintenance costs because of their pessimistic influence due to reactive and unplanned maintenance action. Making use of predictive maintenance to curb this cost is demanding in highly competitive manufacturing industries. And also, ability to anticipate or foresee system breakdown before failure has a strong optimistic impact on machine running which shoots up productivity and diminishes downtime, breakdown and maintenance costs. Monitoring machines digitally collect streams of data in real-time and the data is subjected to analysis to show patterns on any provided machine. Based on identifying the pattern & historical data, manufacturers can detect the machine it means probably to encounter a failure, and for which maintenance can be scheduled effectively.

2. Optimize Planned Downtime

Planned downtime is scheduled time when production equipment is restricted or close down to permit for planned maintenance, repairs, upgrades or testing. Planned downtime for maintenance is peculiarly necessary for retaining critical assets well & fine, but it can also be used to diminish needless maintenance on fewer vital equipment. Each part of equipment needs maintenance at a certain point, but it can be difficult to stop production assets when you have lots of allocations to meet and machines appear to be operating without a problem. The reality is, planned downtime needs to happen, even if it appears like everything is already working properly.

Preventive maintenance can regularly be scheduled using the collected data from machine functioning & also at times where there is less impact for production order. Not only that there is also an additional benefit which is an requisite maintenance of this nature will constantly lengthen the life on a machine that would be hard, and expensive, to put back. Boosting uptime and the existence of an equipment will eventually bring in remarkable cost savings.

3. Maximize Equipment Life span

Do we really know the life time of our equipments?? We may have the rough estimate how long the assets and equipment will last but how confident are we in that estimate? It could be much more or much less – and we won’t know until it’s too late. However, it is crucial to determine the equipment life and improve maintenance strategy. The inspection of machines will help manufacturers identify the condition of present production equipment and identify upcoming faults. Dealing with predictive maintenance will help them boost accuracy of equipment by the data collected on the manufacturing floor.

As machines get old and based on their degree of usage, the maintenance schedule will vary, which can be overseen through predictive maintenance. Fragment of the machine will react to the manufacturing strain distinctly across time. The ultimate rise in maintenance that is anticipated by the way of data patterns will let out when a machine set foot on a turning point on cost in opposition to performance. The requirement to put back substantial pieces of a machine ultimately, or the whole department, is made to deal with, by being capable to predict that demand and plan for it, both from a money & time view point.

4. Reduce Maintenance expenses

Apart from other necessary expenses in production line, a huge amount of money is spent on maintenance expenses. This will be an average of 40% in the overall revenue. We can’t sit at ease without repairing the machines / equipments but we can avoid / prevent costly repairs and or replacement of parts or machines. This is because predictive maintenance allows manufacturers to detect fault, isolate & fix issues before severe damage occurs. Moreover, since preventive maintenance is intended to pre-empt significant damage to equipment, there will be no need for extensive repair work as well as emergency servicing.