5 Steps To Successfully Implement Predictive Maintenance

Predictive maintenance is a holy grail for manufacturers: 

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The ability to predict when machines are going to fail and take preemptive action to prevent downtime.

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Industry experts agree unanimously that predictive maintenance has the potential to save manufacturers a lot of money. It ensures more consistent productivity levels and cuts down on overall repair and replacement costs.

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But where do you start when trying to implement a predictive maintenance program? 

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The following 5 steps will get you to think deeply about your overall maintenance strategy and implement it successfully.

Step 1 – Define what predictive maintenance means for you

Before you start creating a plan and spending money on technology, you need to get a firm grip of what predictive maintenance actually is and what it means for your business.

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The best place to start is to define predictive maintenance alongside some other maintenance strategy types, by way of comparison.

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• Reactive maintenance  –  A basic maintenance style that involves repairing equipment and sorting out faults as they arise. It may work for machinery that isn’t critical for operational success and is considered to be low value, but it is definitely not ideal for high-value, operationally-critical equipment.
• Preventative maintenance – A traditional way to perform machine maintenance. It involves setting up a predetermined maintenance schedule to inspect equipment and change components based on their average lifespan. You can think of it as similar to servicing your car at frequent intervals. 
• Condition-based maintenance – Carrying out maintenance tasks based on the condition of the asset. It involves monitoring the state of the machinery and various components and flagging up when they are getting close to failure. 
• Predictive maintenance – Predictive maintenance is similar to condition-based maintenance, but uses smart technology to monitor the condition and performance of equipment and machine learning to highlight when maintenance is needed.

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Step 2 – Set your predictive maintenance goals

Once you have a firm understanding of what predictive maintenance is, the next step is to identify how it can enhance your manufacturing operations.

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Let’s imagine that you have a set of three CNC milling machines that are in almost constant use. You also have a CNC lathe that is used infrequently. If one milling machine breaks down it can slow down your entire production process. Therefore, any predictive maintenance technology that you implement should probably be applied to the milling machines first. Make sure that you keep your goals realistic, for instance you may set a goal to reduce the average downtime of each milling machine by 30% in the first year. 

Step 3 – Connect your data

The first stage of predictive maintenance implementation is to gather data from the relevant machines, either through the use of built-in technology or through the addition of IoT sensors such as vibration sensors, temperature sensors, or imaging technology. 

Next, the data needs to be connected to your local network or the cloud. At o3, we have defined four maturity levels of connectivity:

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• Level 4 – Capturing data manually using pen and paper - least mature
• Level 3 – Modern PLC controllers without a connectivity port - a retrofit is needed
• Level 2 – PLC with a serial port - an adaptor is needed
• Level 1 – PLC with an internet port - most mature.

Step 4 – Apply smart manufacturing software

Once there is a system in place to collect the data, you need to find a way to process it and analyze it. A modular smart manufacturing platform such as o3 allows you to install a specialist predictive maintenance module that acts as a digital twin. 

The module has a range of built-in statistical predictive models to choose from. Machine learning algorithms will learn from your dataset to improve the model and automatically recommend maintenance tasks based on the results. 

As a first step, you may want to consider O3's autonomous maintenance module, which assists operators in carrying out basic preventive maintenance and managing defects. It's the perfect foundation for smart management of maintenance.

Step 5 – Configure alerts and notifications

The purpose of a predictive maintenance program is to automatically monitor your machines, analyze the data, and alert you when you need to take action. Therefore, you need to configure the system to alert you when data anomalies are found or parameters reach certain levels. 

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You can configure the system to send notifications to operators and maintenance technicians through mobile devices. They can also view automated task instructions on their device and access key information and specifications. The whole process will be streamlined.

Automate your predictive maintenance for swift results

The high level of automation throughout the system allows you to fully optimize your machine maintenance. From data capture and processing to insight generation and alerts – each step is automated. 

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At o3, we have a supply chain and value engineering expert in our team who can help you to identify the key areas to implement smart solutions.

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If you’re interested in finding out more about o3 smart manufacturing and how we can help you to implement predictive maintenance in your business, get in touch and book a demo.