Predictive maintenance programs (PDM) are increasingly being adopted by asset owners across the globe to meet with demands that the industry poses. The major challenges are the losses incurred due to machine downtime and general asset management when in a non-utilizable capacity.
A Predictive maintenance program helps provide predictions that aid in forecasting when all a machine downtime can occur, especially useful in time-critical industries.
So how can a prediction be done accurately?
The answer is historical data. The performance of a machine is monitored and noted along with calibration data, infrared imaging, and vibration analysis, all of which combined help in the process of prediction. The knowledge of downtime beforehand saves the industry money and time as these downtimes can be incorporated during downtime in production.
The challenge faced with an extensive check or diagnostic analysis of equipment collecting historical data is that of time again. In an industry, such a process would end up costing more time than an actual downtime for the equipment. The solutions to tackle this problem are many.
Laser calibration equipment brings out a faster way of running quick checks on machines providing an early hawk eye view on machines, even without having to remove them from their covers. This quick check method along with a standard PDM procedure can help bring down machine downtimes to a minimum, which is by far the most sought-after end goal in asset management and calibration industries.
Let us look at a detailed example of how these procedures combined help drives us to our desired end goal.
The industry thrives to maintain high-quality standards that drive the faster application of predictive analytics in asset management. Let us take the case of a machine that is calibrated every six months and has an error tolerance of 2%. After 3 checks, it is noticed that this error tolerance constantly occurs. Such a process gives us an insight and helps predict that, the machine even though stable requires to be calibrated every 6 months. The basis of the prediction, based on historical data helps plan on downtimes related to this machine. The industry also utilizes vibration analysis of various machine parts to further analyze the functionality along with wear and tear that could then be used to make informed decisions. A quick check mechanism is also introduced to further fasten the process of proper prediction, wherein infrared rays are played across corners of the machine to map and understand any visible flaws under the cover itself. Such a process itself provides an early deduction and helps document flaws that could play a major role in equipment downtime down the line.
The future prescribes a solution based on online calibration in production. Wherein, during manufacturing itself, assets are calibrated within prediction and corrective measures will be deployed then and there. Live scanning systems are constantly employed to put instruments to check, and corrective procedures will be undertaken.
Even though the future solutions look promising but complex, we have active solutions in place which combine the power of regular checks, an effective mechanism for predictive analysis, and the right tools to aid with the process.
What may happen, is right now in your very own hands!
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