Keeping every element of a plastics processing plant running, starting with the maintenance of primary and auxiliary processing equipment, is a big challenge. And, I find that people meet that challenge in different ways.
So, how do you do it? What’s your “style” of maintenance? And what does the future hold?
‘Run it ‘til it breaks.’ This maintenance style is certainly tried and true, with the advantage that you don’t have to do much in the way of planning until something goes wrong and you have to react. Then, you’ve got to pull out all the stops, call all hands, diagnose the problem, get the parts, and get to work. You’re a hero if you can pull off the fix quickly, but a goat if it doesn’t go well because unplanned downtime can be very expensive. Here’s hoping that you never have a “500-year flood” of maintenance problems.
‘An ounce of prevention.’ There’s a lot to be said for a preventive maintenance style, because it recognizes that a regular routine of maintenance input can prevent many equipment problems and support more reliable production. But the goal of preventive maintenance, like the goal of eating vegetables regularly, is to get enough to be beneficial, but not too much, because more is not better. In fact, providing more preventive maintenance than your equipment needs can be a costly waste of labor and supplies. So, the secret to any PM program is to keep very good equipment maintenance records, then use them to measure and balance the level of routine maintenance inputs you apply to various pieces of machinery, based on their measured levels of reliability.
‘How are you feeling?’ Beyond the realm of preventive maintenance, there are a range of innovative predictive or condition-based maintenance approaches. These generally combine periodic equipment assessments with ongoing process and equipment monitoring and data collection, resulting in measures of the overall “health” of entire production processes or individual pieces of equipment. This proactive approach is very ambitious because it aims not just to reduce unexpected downtime, but to dramatically improve overall asset reliability, productivity, and profit.
The idea is that by monitoring a piece of equipment, or its component parts, you can avoid under- or over-maintaining it. Instead, by “listening” to what it is saying, you can maintain it as needed, achieving both greater reliability and lower long-term maintenance cost. One simple example: Consider a conveyor system that uses pillow-block bearings. A PM approach says that your tech walks that line every week and greases each bearing twice, whether it needs it or not. A predictive/condition-based approach says that the tech inspects the line periodically, checking for signs of stress or wear, then offering a half-pump of grease every few months.
But primary and auxiliary equipment are lot more complicated than bearings, right? So, you inspect them using technology, such as temperature and vibration sensors, electrical consumption, ultrasonic leak detection, heat signatures, flow analyses, and the like. Measurements like these, collected over time, can flag changes in equipment status, highlighting early-stage maintenance concerns when they can be fixed quickly and at the lowest cost.
That technology is available today. For example, you could create a maintenance program to monitor a key aspect of chiller performance – vibration – using either dedicated vibration sensors or sensors that work remotely through a tablet or phone. Through routine monitoring, or by setting a threshold level for a remote alarm, maintenance professionals could quickly identify excess vibration or other equipment problems and respond immediately. In this case, excess vibration caused by an out-of-balance fan could be identified and repaired well in advance of much more serious problems, such as cracked refrigerant lines on the chiller and diminished cooling capacity resulting in product quality problems.
So, what will the future bring? Innovations spurred by Industry 4.0 will automate an increasing share of process and equipment measurement and data collection. Cloud-based analytics will receive and analyze machine data, identify possible problems, then report to maintenance personnel who can complete the diagnosis, prioritize maintenance for immediate completion, or schedule major maintenance during well-planned scheduled shutdowns. You may even enter a relationship with your equipment provider, in which they monitor your equipment using this cloud-based data, and provide predictive maintenance data and services to your maintenance team.
Today, it’s comparatively rare to find plastics processors whose maintenance operations achieve the “holy grail”: total annual maintenance costs less than or equal to 1.5% of Asset Replacement Value (RAV).* But that’s what top-quartile manufacturers do in many global industries. Think of it: running plant equipment with a replacement cost of $2 million for a total maintenance cost of about $30,000 per year—including people, supplies, everything. Can you do that? Would you like to?
*Maintenance cost as a percentage of Replacement Asset Value (RAV) is a ratio developed by the Society of Maintenance and Reliability Professionals and used by the Association of Maintenance Professionals and many of the world’s leading manufacturers.