Maintaining a manufacturing plant is an ongoing process that plays a significant role in overall business success. Unfortunately, traditional maintenance methods are usually followed by long downtimes, leading to production delays and ultimately unhappy customers.
However, as new technologies become available, maintenance practices change faster than ever before. So, as the entire world is entering the 4th industrial revolution dubbed Industry 4.0, technologies such as Internet of Things sensors, machine learning, and artificial intelligence work together to reimagine maintenance completely.
The new approach is called predictive maintenance, so let’s take a closer look at how it works and what benefits it provides.
Predictive Maintenance In More Detail
Predictive maintenance is a new type of industrial maintenance that uses operational data to identify potential problems before a catastrophic breakdown happens.
In order to work, small IoT sensors are placed onto every machine to gather operational data and send it to a central machine learning model.
As the central hub analyzes large amounts of data, it can identify patterns and better understand how the entire system works. It can also identify the exact time when a problem will occur, allowing your engineers to perform repairs before the damage is done.
Traditional maintenance strategies such as reactive, planned, and unplanned maintenance are far less efficient and costly.
The standard approach was to fix only those machines that stop working correctly or break down completely, which is followed by huge costs, prolonged downtimes, output reductions, and other downsides.
The preventive approach is much better than any reactive strategy because it’s less time-consuming and more affordable. Instead of buying spare parts for every machine, manufacturers can now purchase only those identified as faulty by the central system.
With IoT sensors needed for this to work in place, manufacturers get many other benefits, such as the ability to monitor entire factory floors in real-time, an early hazard detection system, and many others.
Predictive Maintenance in Action
Preventive maintenance is by far the most established type of this process. It is based on previous experience, where engineers estimate how much time needs to pass before a machine starts malfunctioning.
All maintenance efforts are then planned a few weeks before a machine should stop working correctly. In other words, the planning and execution depend mostly on guesswork.
On the other hand, predictive maintenance uses data generated by the equipment and sent to the central system. It is a form of prescriptive maintenance that uses condition-based data to predict the state of machinery.
The system then analyzes the data in real-time, detects patterns in the machine’s health, and calculates parts’ lifecycle to reduce maintenance costs. It can be applied to any industry, whether the wear and tear are faster or slower than the considered average since all calculations are based on real-world data.
Once the software learns how the entire system works, it can calculate the state of every machine and alert maintenance staff before the damage is done.
Technicians can then schedule maintenance efforts and perform repairs with minimal downtimes, as they already know which parts need to be replaced. It’s a truly revolutionary type of maintenance that’s already showing some incredible results.
How Predictive Maintenance Improves Overall Performance
Predictive maintenance uses the same approach for maintaining manufacturing equipment and machinery, as other business processes that use data to improve accuracy and flexibility. As such, it provides all kinds of benefits, most of which focus on reducing costs, optimizing downtimes, and minimizing unplanned downtimes. In addition, however, the method also improves employee productivity, equipment lifetime, and many other areas.
The system is constantly fed with real-time, real-world data, making it easier to schedule regular maintenance in a way that has the least effect on production.
In the long run, that helps extend the life of expensive machines and equipment, which is another way to save money. Here are some of the benefits you can expect to get after introducing predictive maintenance.
- Limited Unplanned Downtime
Unplanned downtimes can cost manufacturers a lot of money in lost revenue and repair costs. In addition, the production has to stop whenever a machine breaks down until the repairs are completed.
That can negatively affect production, sales, customer satisfaction, and other essential processes. Predictive maintenance can fix all of those problems at the same time.
It can limit repair costs and ensure that all machines are running smoothly at all times. Further, the ability to analyze real-time data and identify patterns in asset behavior can help reduce downtimes or make better maintenance plans to limit unplanned downtimes.
- Equipment Lifetime Optimization
The ability to monitor every detail of every machine used in production can extend the equipment’s lifetime.
The data collect details about efficiency, output, quality, vibrations, and others to identify when a machine is about to break down. It’s something traditional maintenance techniques can’t do.
Once the system’s central hub has all of the data, it can accurately calculate the lifetime of every machine or part. It can also factor in the level of use, hazardous gasses, stress, and other elements that affect machine health.
Likewise, the data pattern can predict even more details, including overall repair costs and the time needed to make the repairs. Knowing every detail in advance is an entirely revolutionary approach to maintenance, and it can’t compare with any other available method.
- Employee Productivity Optimization
Constant real-time machine monitoring can also help you optimize employee productivity. The predictive approach to maintenance will reduce repair frequency, but it will also minimize breakdowns and accidents caused by human error.
Whenever the system identifies a faulty machine or a potential danger, it will halt production and alert the worker to prevent possible injuries.
Your employees won’t have to fix problems themselves to keep working, which positively affects morale. Also, the overall stress on the shop floor is reduced to a minimum to expect a higher output and better shop floor conditions overall.
- Increased Revenue
Revenue is one of the areas affected the most by predictive maintenance. Moreover, this approach has a direct impact on multiple areas.
For example, it can reduce maintenance costs by up to 40%. Predictive maintenance also reduces waste, energy and labor costs, and machine time by 20%.
However, with an IoT system in place, you can expect to uncover previously unimaginable opportunities and insights on further process optimization.
There are many reasons why predictive maintenance is the best approach to maintaining production in a manufacturing company.
First, it can help manufacturers save time, money, and effort by limiting unplanned downtime and uncovering new opportunities.
However, keep in mind that this technology is still in its earliest stages, so it’s costly and hard to set up. However, if you have the means, the benefits it provides are well worth the trouble.
Once an IoT system is in place, you will prepare your factory for the future.
Rick Seidl is a digital marketing specialist with a bachelor’s degree in Digital Media and communications, based in Portland, Oregon. He carries a burning passion for digital marketing, social media, small business development, and establishing its presence in a digital world, and is currently quenching his thirst through writing about digital marketing and business strategies for SEO turnover.