Leaders at any business that depends on complex machinery or devices know that regular maintenance is essential to smooth and efficient operations. Without timely maintenance, machinery breaks down, leading to downtime, costly repairs and sometimes even replacement. The common practice of preventive maintenance entails regularly inspecting equipment and tuning it up, before it needs repairs. But the emerging practice of predictive maintenance aims to build upon preventive approaches and make them more efficient and cost-effective.
Predictive maintenance is the practice of monitoring equipment via sensors, software and data feedback to prioritize equipment for proactive maintenance. It takes preventive maintenance one step further by streamlining the process of identifying which equipment (or even which components) is showing signs of needing attention. Predictive maintenance can save businesses money by identifying exactly when they should tune up equipment, rather than just maintaining a regular preventive schedule that could be directing resources to equipment that doesn’t need maintenance.
Predictive maintenance relies on internet of things (IoT) sensors and devices, which are wirelessly connected to a console that collects and analyzes data from the machine. Sensors detect a variety of data, feeding it to a computer that presents it to you in a manageable form. The data provided from IoT sensors, such as temperature and vibrations picked up with ultrasonic detection, can tell you a great deal about how a machine is running.
Vibration sensors detect any subtle, unusual changes. Thermic sensors determine if there is too much friction on certain moving parts. Other sensors monitor oil and lubricant levels to ensure that there’s enough and that it is clean.
Each sensor feeds data back to a centralized source, where machine learning algorithms break down the data and put it into the context of machine performance and wear. Utilizing the mountains of collected data, IoT programs alert you to when maintenance is needed or if a breakdown is imminent, thereby allowing you to dispatch maintenance teams in a targeted way.
Predictive maintenance combines the internet of things with predictive data analytics to improve the way businesses set maintenance schedules. As a result, businesses can allocate resources more efficiently, boost the longevity of machines and maximize uptime.
Predictive maintenance offers improvements over the current widespread standard of preventive maintenance. This results in several clear benefits:
When you’re implementing a predictive maintenance system, be sure to consider the scale of the operation. Sophisticated systems for different machines can be expensive, and while costs are starting to decrease as the technology becomes more readily available, businesses should consider many factors when establishing a predictive maintenance process.
First, ensure someone on staff understands the system and knows when maintenance should be performed. This role requires a mix of expertise in IT and knowledge of the machines and equipment being monitored. Depending on the scale of your operation, it may be necessary to hire an IoT expert.
Consider the following tips to set yourself up for success with predictive maintenance:
Variable pay is the extra money your sales agents earn atop their base salaries for hitting certain performance marks.
Predictive maintenance can require a substantial investment, but it can also save your company money in the long run by targeting problem areas that preventive maintenance can’t address on its own. Once you understand the costs and benefits, you’ll know whether, and where, predictive maintenance can help your business prevent costly downtime and repairs.
Adam C. Uzialko also contributed to this article.