Improving Efficiency with Condition-Based Maintenance

Welcome to the Net Zero Club News Network where we bring you the latest updates on sustainable solutions and innovations in the FM industry. Today, we delve into the challenges faced by the industry and the groundbreaking solutions that are transforming the way we approach maintenance and energy efficiency.

Traditionally, the FM industry has operated on a ‘We have always done it this way’ mindset, but times are changing. Innovative solutions such as data-driven maintenance are revolutionising the sector by utilising live asset performance data to make informed decisions and drive efficiencies.

Let’s first take a look at the traditional methods in the FM industry. Planned Preventative Maintenance (PPM) has been the go-to approach for asset maintenance, using industry standards like SFG20 to schedule maintenance tasks based on pre-determined frequencies. While PPM has been effective in ensuring compliance and reducing breakdown risks, it lacks the ability to consider the actual condition of assets when not on-site, leading to inefficiencies and reactive maintenance.

On the other hand, data-driven approaches offer a more proactive and efficient solution. By tapping into existing building data or implementing IoT sensors, FM teams can access real-time asset performance analytics. This enables them to identify assets showing signs of inefficiency or potential breakdown, allowing for targeted maintenance and elimination of unexpected asset failures. Not only does this save costs, but it also lightens the workload of engineering teams.

When it comes to asset breakdowns, adopting a condition-based maintenance strategy can streamline the callout process and improve overall efficiency. By analysing data for off-site diagnosis, FM teams can pinpoint likely causes of issues and assign the right engineer with the necessary tools and materials for a first-time fix, reducing building downtime and callout costs.

Another key challenge in the FM industry is predicting asset end-of-life and maximising asset value. Traditional methods rely on generic guidelines like CIBSE Guide M, which may not accurately reflect the usage patterns of specific assets. By leveraging data, FM teams can tailor end-of-life predictions based on actual asset usage, leading to more accurate and cost-effective asset management.

As the industry continues to evolve, embracing innovative solutions like data-driven maintenance is essential for overcoming challenges, improving efficiency, and reducing energy wastage. Stay tuned to the Net Zero Club News Network for more updates on sustainable practices shaping the future of FM.