
The growth of the manufacturing sector in the past couple of decades have been commendable and overwhelming. With the development of population, global demand has increased leaps and bounds. Hence, intending to hit the nail on the head, the manufacturing sector expanded pervasively. The 90s witnessed another revolution with the advent of the internet. The terms "big data", "machine learning", "Internet of Things" have been sprinkled in most tech articles in the last couple of years. These emerging technologies have been significantly aiding to maintain overall production processes. However, all of them have a common denominator, that connects them all, which is known as Predictive Maintenance, reason why a proper Predictive Maintenance Plan is very crucial. The potential of this market is so huge . Studies show that the predictive maintenance market is said to grow to 6.3Billion by 2020.
What is Predictive Maintenance (PdM)?
Predictive Maintenance is a practice primarily directed towards Maintenance of overall health of machinery or equipment in a manufacturing unit. It is a proactive manoeuvre that is undertaken to predict if there is any faulty piece of the machinery which might stop working and thereby disrupt the entire manufacturing process. Predictive Maintenance is designed to assess the condition of the in-service equipment so that necessary maintenance steps can be taken to restore the same so that the day-to-day production process is not hampered. With the advances in telecommunications, Artificial Intelligence(AI), predictive Maintenance is getting its recognition which was long overdue.
Predictive Maintenance plan involves the analysis of asset metrics, that lead to savings of enormous maintenance expenses. The underlying idea of predictive Maintenance is to allow an efficient mechanism of corrective Maintenance so as to avoid unexpected equipment failure. This can consequently help in reducing accidents with negative environmental impact by increasing the safety measures of the overall plant.
Predictive Maintenance also helps in stretching the overall useful life of the machinery by predicting any fault or glitches in advance. It also helps in reducing unplanned downtime costs incurred due to some failure, which ultimately tampers the profits of the organization. It is more about predicting the future trend of the condition of the equipment. It studies various performance or maintenance data points to analyze the present health condition of the machine. Predictive Maintenance is incredibly helpful in estimating the future degradation probabilities of the machinery and optimizing the production capacity. Its huge benefits is what makes it very crucial to have a proper Predictive Maintenance Plan
Steps of Predictive Maintenance Plan
Predictive Maintenance is the buzzword among executives and business professionals. It is a cutting-edge maintenance strategy that needs to be adopted by the manufacturing industry at the earliest. Given below are specific steps of Predictive Maintenance Plan.
Determining the goal
It is necessary to have a clear and crisp definition of the scope of implementation of Predictive Maintenance in the business process. The company should know precisely why it is taking up the project of predictive Maintenance. The most prevalent glitch in these projects is that most companies are oblivious of the fact that what they want to predict. Hence, before transitioning into predictive Maintenance, it is necessary to determine precisely what is required to be expected. With different assets, the approach of predictive analysis is also different. So, having a clear goal is of utmost importance.
Data Quality
The next step of this maintenance manoeuvre is data analysis. Data should be of both historical nature and real-time data. The sources of such information must also be reliable like IoT devices, back-office systems etc. Data should be primarily about past performances, failures, maintenance history, current condition etc. Reliability and quality of data should also be taken into account.
Data Analysis and Conclusion
Once the data is collected, the analysis of the past and present performance of the asset will help in reaching conclusive insights about the health of the same. With today's technological advancements, processing of data has been automated in most cases and the system is able to predict the upcoming failures, which the asset is susceptible to encounter. This, in turn, helps in providing preventive measures to increase the efficiency of the purchase.
Creating a Plan
A road map needs to curate based on the data analysis of the previous step. It is advisable to create a list of all the part of the assets, where predictive Maintenance is intended.
Communication
It is not only the machines and technologies that do the necessary alterations and predict failures, but professionals also play a pivotal role. It is advisable to conduct meetings among the team members that are involved in machine maintenance and repairs so that communication becomes easy and straightforward. Suggestions and opinions can be exchanged regarding the health of the assets, manufacturing information, etc., which will help in creating a road map ahead with everyone onboard.
Condition Monitoring Program
At this step, the concept of condition monitoring becomes very important. Condition Monitoring or colloquially known as CM is the process of deciding upon a parameter of condition in machinery like vibration, temperature etc. and thereby monitor the same so as to identify a substantial change which is indicative of a developing pitfall in the machine. It is also advisable at this stage, to do a pilot study of a small piece of the plant so that nothing gets missed out.
Implementation
Once, the pilot study is successfully done, the next step is to implement the plan on the entire asset. The necessary course of action should be adopted, so as to ensure smooth implementation of the same.
Feedback
Predictive Maintenance is a continuous process. Hence a good Predictive Maintenance Plan should always have room for feedback and opinions. This will help in adjusting the task, routes, frequency and duration of activities.
Conclusion
It is necessary to have a reliable predictive maintenance plan to ensure the proper functioning of the machinery and equipment so that the production process is not disrupted and profitability does not get compromised.
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