How much would you pay for an outside consultant to tell you where to spend your spare parts budget so that you don’t overfill your shelves with idle components? Would it be valuable to know which parts are nearest to their end of life so that you could appropriately schedule off-shift maintenance? The solution to these key issues may already lie inside your database.
Preventative maintenance schedules have long been published by the equipment manufacturer, for individual components based on historical data and accepted mean time between failures. However, these schedules are developed based on a cross-section of data that does not consider the specific location, utilization, or application for which the components are actually operating.
Hear us out. Your automation system software logs each time a valve opens, a paddle extends, or a fault occurs with a timestamp. It also stores all data on system input and output. All of this data is exactly what you need to compile a report that displays plant operating efficiency. The next step for your automation software is to move away from Preventative Maintenance and move towards a Predictive Maintenance Model. Should a solenoid switch be replaced every 2 years, or should it be replaced every 1.5 million cycles? Even better, should it be replaced after 1.2 million activations because the average time between activation was 3 minutes, not a rapid firing 5 seconds? What information is buried in your database that could be leveraged to better optimize how you run your operations and how do we utilize mobile technology to enhance your process?
Make your reporting software do more than report on what you have done, have it tell you what you should be doing.