How To Use Predictive Maintenance in Construction

How To Use Predictive Maintenance in Construction

March 27, 2024
How To Use Predictive Maintenance in Construction

Predictive maintenance is the process of monitoring equipment to identify potential sources of wear or failure. If a company can catch a potential issue before it causes something to break down, the business can save money and continue to use that asset. According to Deloitte, predictive maintenance reduces breakdowns by 70% and increases productivity by 25%. 

What Is Predictive Maintenance?

Predictive maintenance is a key part of the takeoff stage of construction. Teams will evaluate the equipment and tools they need, then consider if any of those items need repairs or serving before they can be used. This can prevent delays because teams won’t have unexpected breakdowns or discover the equipment is worn out when they need it. While the architects work on the building information modeling (BMI) process, the mechanics can prepare the equipment. 

You can improve maintenance within your business by being proactive with repairs and using the following steps to implement an efficient predictive maintenance system 

Inventory Assets

Your assets are appliances, equipment, and other tools that make your operations more effective. By accruing assets over time, your organization can start projects faster. Your team won’t have to rent equipment and can use advanced systems to complete jobs more efficiently. 

To start with predictive maintenance, create an inventory of your assets. Your system can include information like the cost of the asset, the date it was acquired, and potential maintenance. For example, a work truck would need regular oil changes and tire rotations.   

Train your team on some of the best practices for inventory management. This includes forecasting demand and maintaining quality control if you keep construction materials on site. These habits will help you better track your assets and understand potential maintenance issues.  

Identify Priority Assets

Once you have an inventory process in place, you can identify priority assets for maintenance. These will likely be a mixture of assets that need immediate repairs and assets that are used frequently to complete your work. 

Few companies have the time and money to repair all of their equipment at once, so you need to take a triage approach to getting the work done. This involves ranking maintenance tasks based on their importance, urgency, and payoff to prioritize your actions.  

Analyze Historical Data

If you aren’t sure where to start with maintenance tasks, look at past data. Historical data will tell you how long machines run before needing maintenance and the types of problems that can occur. 

There are multiple ways to gather this data. First, look within your team. Your staff likely knows which appliances and tools are likely to break and why. Next, check third-party sources. There might be publications online highlighting how certain pieces of equipment could break down in specific conditions. Even if your equipment is working fine, this information can prepare you for potential issues.  

Set Clear Parameters for Maintenance

Maintenance parameters list out exactly when a machine needs to be serviced and checked for potential issues. This allows you to proactively work on the equipment instead of unexpectedly taking it out of service. Here are a few examples of parameters you can set: 

Each asset should have its own specific service parameters. These will relate to the durability of the machine and the type of wear it will experience.  

Create Specific Procedures

Along with setting parameters for when equipment needs servicing, you also need to document the type of servicing it needs. This will ensure the repairs are long-lasting and effective. For example, a work truck might need a tire rotation and an alignment. If the tires are the only service they receive, the truck could be unstable and difficult to handle. 

When a service technician starts working on a piece of equipment, they should have a checklist for exactly what needs to be done and how the item should be tested for efficiency and durability. The more details included the better. Using the work truck as an example again, a vague parameter would say “check tires for wear,” while a specific one would provide actionable steps to evaluating the wear and reporting it. 

Up-train the Maintenance Team

Training is a significant part of predictive maintenance. Work with your service team to follow these procedures and complete different tasks to keep your equipment running. Your training processes might include administrative reviews — like teaching staff how to log inventory or create service reports — or could involve hands-on sessions on maintenance tasks. 

Once you are done training, start retraining. Refresher sessions and repair reviews can keep service information fresh so your team can apply it to their work. 

Utilize Automated Predictive Maintenance Tools

You don’t have to create and manage predictive maintenance systems manually. There are plenty of tools that can streamline your processes and alert you to potential maintenance needs. Here are a few to consider: 

Additionally, look into construction takeoff software that can help you keep track of various projects. You can better survey and measure materials, estimate costs for the work, and provide accurate information to your customers before the project even begins. This is a useful tool for managing all arms of your business. 

AI in Predictive Maintenance

Both AI and machine learning (ML) can be valuable tools for predictive maintenance. ML systems collect countless data points and learn the patterns of your team. AI tools analyze data and make recommendations — or actively implement decisions — from it. 

By investing in the right AI and ML software, your project managers can receive alerts when equipment needs to be serviced based on observed wear and tear. While it always helps to have humans look over equipment to make sure it’s safe to use, these tools can catch issues or potential problems that are hard to notice. Even if your tools only handle basic tasks like checking fluid levels, your team will still be more informed and make better decisions from the information they provide.  

Integrate and Regularly Update Technology

The tech tools that you invest in shouldn’t operate in a silo. Advanced systems can work together and share information for better management. For example, if your inventory tracker reports that a piece of equipment is out for servicing, your takeoff system should be aware. Knowing this information can help you set a better timeline for the project or recommend alternative equipment options. 

Even if you are currently happy with your technology systems, evaluate your tools regularly — at least annually. There might be better options out there that improve your workflow. 

Streamline Communication Methods

Finally, boost your communication best practices to improve your predictive maintenance processes. Create channels for your staff to report on the health of certain pieces of equipment and report issues that should be serviced. This can help you collect historical data on your assets and better understand their maintenance needs. Even if a piece of equipment is fine, the team members who use it should still submit status reports on them. 

Predictive maintenance is a multi-faceted process. Everyone needs to work together to keep up with servicing assets and reporting potential problems before they put your equipment out of commission. Use these steps to better manage your construction business.

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