Maintenance strategies have been around since the industrial revolution, they have also evolved over the years. Starting from reactive maintenance i.e., fix when broken, to scheduled and predictive maintenance,  and now prescriptive maintenance. In this blog, let’s understand prescriptive maintenance in detail.

What is Prescriptive maintenance and how does it work

Prescriptive maintenance (RxM) is an advanced maintenance strategy that utilizes artificial intelligence (AI) and machine learning (ML) algorithms to achieve the highest degree of operational efficiency. It takes into account various parameters (i.e., current & historic performance, operating condition, maintenance schedule, SLA’s, energy efficiency etc) with its holistic approach to reduce costs, improve efficiency, and achieve sustainability. With the advancements in big data analytics, IIoT sensors, and Industry 4.0 technologies, enterprises can now:

1. Pinpoint problems at inception.
2. Establish cause-effect relationships and get recommendations to solve them.
3. Spot areas with potential for improvement.

Pros and Cons of prescriptive maintenance

Pros:

1. Reduce operations & maintenance costs.
2. Increase productivity.
3. Maximise asset life.
4. Improve employee safety.
5. Eliminate unplanned downtime.
6. Aids learning and development of new joiners.
7. Meet organization level SLAs & sustainability goals.

Cons:

1. Critical and non-critical equipment needs to have an adequate number of sensors (IIoT or otherwise) for system-level modeling. Which would increase the CapEx cost.
2. Most of the prescriptions are dependent on data. You need to have sensor data for at least a few months for machine learning algorithms to analyze and draw conclusions and provide recommendations.
3. Prescriptive maintenance software might be expensive compared to traditional maintenance software solutions.
4. Few solutions may not be compatible with 3^rd party solutions like CMMS, SCADA, Historian, APM, ERP, and others present in the plant.

How to implement prescriptive maintenance

Step 1: Assess the current IT and OT landscape.

Understanding how your current information technology (IT) systems and operational technologies (OT) converge is quintessential for planning your prescriptive maintenance implementation. Things to consider are if the deployment would be in the cloud vs on-premise, connectivity between RxM solution with your Historian/SCADA, EAM, ERP, and rest of the OT tools.

Step 2: Identify critical areas for improvement.

Some units or sites may be in need of a prescriptive maintenance solution more than others. Identify such units or sites which will drive the most value for a buck. You may start the pilot with a select few.

Step 3: Ascertain sensor & data requirements.

Since RxM depends heavily on the availability of data, data from various parameters (sensors), the timeframe from when the data is available, and how/where it’s stored i.e., online or offline needs to be ascertained. Your RxM implementation may get delayed if the unit/plant lacks adequate sensors or doesn’t have sufficient historic data.

Step 4: Run a pilot.

You can choose to deploy a pilot at the unit level or the entire site. If you’re uncertain about deploying a pilot in the live environment, you may also provide the vendor with historical data for an offline pilot to run analysis and provide insights from past performance. This will let you evaluate If the tool was able to pick up past issues, if yes, how quickly, and also identify its root cause.

Step 5: Validate recommendations and corrective actions.

Expect alerts for reliability, efficiency, and sustainability. Keep in mind that the system is still learning and may not be perfect. Think of it as a fresh-out-of-college graduate who lacks domain know-how but with a super-computer for a brain. Compared to a DCS or traditional predictive maintenance solution, you will receive far lesser but more meaningful alerts. Validate the same, so the system learns good vs bad behavior.

Step 6: Scale and reap the benefits.

Once the system has been perfected, you can plan a phase-wise deployment across the organization. Keep in mind that, this will need stakeholders from multiple departments (operations, maintenance, IT, and others) working together. As the solution is deployed across the organization, engineers need to be trained and retrained in making the most of the solution.

What are the benefits of prescriptive maintenance?

Prescriptive maintenance offers several advantages over traditional maintenance strategies. It is proactive, preventing equipment failure before it occurs and reducing downtime and costs. It is data-driven, relying on actual equipment performance data for decision-making. Lastly, it is customizable, allowing tailored maintenance plans for individual equipment needs.

Conclusion:

Prescriptive maintenance is a powerful tool that enables organizations to prevent equipment failure, reduce maintenance costs, and optimize operational performance. By harnessing the power of AI and ML, prescriptive maintenance unlocks a new era of operational excellence. To learn more about prescriptive maintenance and embark on a digital transformation journey, reach out to UptimeAI.