Manufacturing companies need to produce, sell and maintain their products in a fast-paced, cost-effective manner. In order to achieve this, manufacturers must implement a solid strategy for maintenance. Pundits refer to this process as predictive maintenance or proactive maintenance. According to an article by KPMG in 2016, predictive maintenance is more effective than reactive maintenance because it can identify potential issues before they become costly problems. This blog discusses the basics of predictive maintenance and its importance in manufacturing companies. We will also look at some of the examples of manufacturers that have adopted this strategy so that you can make informed decisions about your own operations.
What is predictive maintenance?
Predictive maintenance in manufacturing is the strategy of collecting performance data on equipment and assets, and using that data to predict potential problems before they occur. This enables manufacturers to increase the availability of their assets and reduce the number of downtime incidents. If a problem is identified early, it can be corrected before it becomes critical. This form of maintenance is essential to the operations of manufacturing companies. It helps companies reduce their costs by discovering problems before they cause damage to equipment and assets. The more data that is collected and analyzed, the more accurate the predictions will be.
Why is predictive maintenance important?
As the global manufacturing industry continues to evolve, the performance of existing assets will become increasingly important. Asset reliability, availability, and maintenance costs will all increase as the demand for products change. If a failure affects a specific batch of products, customers will be less likely to buy those products. This affects all manufacturers, but companies that commit to predictive maintenance will be able to respond to these changes more quickly than their competitors can.
Examples of successful implementations
A beverage company had been experiencing extended machine down times due to a complicated machine architecture and a large number of discrete parts. The company implemented a predictive maintenance solution that monitored machine usage and reported machine downtime based on machine utilization. The solution reported when the machines weren’t in use and enabled the company to avoid extended downtime. Another manufacturing company’s defective product caused millions of dollars in damages to their customers’ products. The company implemented predictive maintenance solutions to monitor the inventory of the products that were damaged during the incident. The solutions enabled the company to detect potential inventory issues and prevent unnecessary damages.
Challenges in implementing predictive maintenance
Predictive maintenance has many potential benefits for manufacturing companies, but implementing it successfully can be challenging. Customers may have high expectations of the predictive maintenance solution’s performance, and manufacturers will need to overcome the skepticism of their employees. The solution will require significant investments in both people and technology, and manufacturers need to ensure that they have identified the right people with the right skills to implement the solution.
Predictive maintenance is a strategy that uses machine data and performance information to predict potential problems and minimize the likelihood of downtime. It can reduce costs and improve asset reliability.