The What, Why, and How of Predictive Maintenance
KOREKORE
With the rapid development of technology and its incredible abilities, predictive maintenance has emerged as an exceptionally useful tool for businesses, especially those whose operations involve complicated machinery or vehicles.
So, what is predictive maintenance and why is it important? In short, it is technology that effectively analyzes historical and current data to predict necessary repairs and maintenance, which can in turn prevent unforeseen or unnecessary costs.
Predictive maintenance starts with sensors collecting information machinery, such as oil measurements, thermal readings, or specific movement scans. Using a combination of historical and real-time data, software that uses artificial intelligence along with the power of IoT can evaluate the information that has been collected and produce detailed reports and predictions. This process helps identify potential issues before they escalate, avoiding unexpected downtime and costly repairs.
Gathering preventative data is beneficial to any company, as it can impact costs, productivity, strategic decisions, and operations. Predictive maintenance seeks to achieve this by leveraging AI and IoT technologies. This makes it an increasingly essential tool for optimal business operations.
As AI and IoT continue to evolve, the prevalence and necessity of predictive maintenance in varying industries is expected to grow.
There are three variations of predictive maintenance: corrective, preventative, and risk-based. Each plays a major part in the effective collection and analysis of data. Here are the differences between the three:
Understanding these forms can help ascertain the value this tool brings to your business.
The key difference between predictive and preventative lies in the type of data that is gathered and used. Preventative maintenance leverages historical data, processing past events to rely on best practices. Predictive, on the other hand, processes measurements from events as they occur in real-time. This allows for critical projections to be made.
Both types are proactive, but each comes with their own set of benefits and shortcomings. This strategy might result in the mistake of presenting issues that don’t exist or need attention. Predictive maintenance is more complex, providing shorter notice as it utilizes a less planned out schedule.
Predictive maintenance offers a wide range of benefits to businesses, including:
Predictive maintenance has evolved into a revolutionary tool over the past few years. We expect most businesses to leverage it moving forward. Analysts anticipate that the industry will continue to develop at a quick pace, reaching a value of $28.2 billion by 2026. This growth is fueled by advancements in Industry 4.0, the Internet of Things, and AI.
If a machine tends to break down after 10,000 hours, a preventative maintenance strategy is completed when the machine reaches the 9,000-hour mark. This approach uses historical data to determine the optimal time for maintenance, ensuring the machine continues to operate efficiently without unexpected failures.
Predictive maintenance is a valuable tool for most companies. It has proven to be an effective way to cut costs, improve strategy, and extend the lifespan of equipment. Studies have shown companies investing in predictive maintenance reduce up to 30 percent of maintenance costs and significantly increase their return on investment.
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