All you need to know about Predictive Maintenance!

Predictive Maintenance

Let’s start with an instance of a second-generation businessman named Mayank. Mayank manages two rice mills single-handedly. He’s tired of following the conventional ways of management passed on from his dad. This forces him to stay at the factory and supervise everything in person. Going on like this, he could never focus on the growth of his plant and he was stuck in that same old process. Machines broke down due to lack of efficient monitoring and also receiving manipulated second-hand data from operators. This led to a significant decrease in production quality and efficiency.

Just when he had lost all hope of effective management and scaling, one of his friends introduced him to Innovation Factory. IF’s IoT based boards convert motors, pumps and mounted bearings into smart wirelessly connected devices which provides real-time alerts of key parameters, such as temperature, current, vibration, etc. to mobile and web app and continuously leverage them to get maximum efficiency. Apart from these an AI continuously works in the background which drives preventive maintenance of key equipment. IF can also automate processes for optimizing quality and power efficiency in production post a thorough audit. Once implemented the entrepreneur could see noticeable RoI in 6-9 months.

Mayank is a free bird now, he manages his time like never before and is already working on setting up new verticals since he need not call 50 people to get individual updates or stay grounded at the factory. He now has a go-to predictive maintenance software for his plants where he can see all the key aspects!

This is how Industrial Automation makes your life easier, and Predictive Maintenance is one of the strongest and most important aspects of Industrial Automation. Now, let’s get into letting you know all that you need to know about Predictive Maintenance.

What is predictive maintenance?

Predictive maintenance is a method through which a production system can be evaluated and maintenance requirements of machines in a factory floor can be anticipated. Patterns are obtained by analyzing operational data from the machines, which help the operators predict when maintenance is to be done on any given unit, before its failure. It aggregates all spheres of data including environmental, process and resource data, and uses AI and machine learning for asset-maintenance.

Earlier manufacturers and factory-owners would rely on reactive maintenance. They would act on servicing their machines only they were broken, and not before that. This was a huge cost both in terms of unplanned downtime and the resulting impact that is cast on the other parts of the machine. The quality of the production was also largely affected.

The mechanism of predictive maintenance could be brought to light with a simple example of ‘vibration analysis’. A system/ device/ model that uses a baseline of performance data for any machine, will detect changes like an increase in the vibration in any specific part of that machine. This could be caused due to any technical malfunction, or damage in parts, or the introduction of some foreign element. Now, any sort of deviation from the baseline data helps the operators to predict a need for maintenance before the trivial issue converts into a serious equipment failure.

Benefits of predictive maintenance:

  • Plant-owners can avoid expensive equipment failures and unscheduled downtime. They can adopt a proactive approach to address the problems and solve them before they significantly influence the production process.
  • Improves production-quality through machine learning and identifies maintenance issues beforehand to increase consumer-satisfaction.
  • Maintenance costs are reduced and equipment life is extended by a significantly visible margin.
  • There as an improvement in production efficiency, asset utilization, and production output.
  • Maximizing uptime and equipment life-span causes significant cost-savings.
  • From the perspective of the employees, reduced breakdowns and accident-prevention systems improve safety conditions within the factory and minimize chances of injuries.All the predictive maintenance advantages mentioned above together work to achieve one exclusive goal- Increasing the Bottom line. With lesser maintenance on healthy components and quicker repair of unhealthy components, repairs can be more effectively handled.

    How predictive maintenance saves cost?

Predictive maintenance does involve some upfront cost in adding the appropriate hardware to facilitate the process, but it saves a huge margin of cost in the long run in the following ways:

Controls system-shutdown and saves costs

Inadvertent system shutdown is the worst-case scenario that could ever be faced by any plant-owner. In such a case, production stops immediately and the owner loses money with every passing second. There also stands a potential risk of the system being repaired incorrectly or incompletely, causing a need for future repairs that would further increase the costs.

Predictive maintenance will help plant-owners/ production-managers to know from beforehand when the system runs the risk of failure. They will, hence, be able to schedule a system shutdown for repairs. This will help repair crews be more productive with a pre-determined agenda in hand.  The manager can plan a temporary production strategy around on-going maintenance, minimizing loss.

Accurate detection of equipment-glitch and Preventing a problem from turning into a catastrophe –

The predictive maintenance software notifies the plant-operations team about the exact problem that has occurred with the exact unit. Since the operations team will already know what exactly has gone wrong, they will not have to rely on any guesswork to proceed with the repair procedure.

Now, the operations team will purchase the exact correct parts required for repair, without any wastage of money. This ensures the most efficient fulfillment of the maintenance process. By doing away with the guesswork and investigating the cause of failure, plant-owners will save money by fixing the system fast and at once.

Conclusion:

Conclusion:

The opportunities to improve a business that predictive maintenance gives us, are too useful to be left unexplored. It is just the beginning of the potential we are about to come across from the significant reduction in the cost of drawing data and calculating predictive outputs. There is a considerable number of Industrial automation companies available now, that are providing predictive maintenance, to make your production processes easier.

For further query and insight on predictive maintenance of your plant/factory, visit https://www.innovationfactory.app/