Predictive Maintenance: Reducing Costs & Improving Efficiency

What if equipment breakdowns could be decreased by up to 75%? It might sound too good to be true, but predictive maintenance has been found to provide this and many other benefits. In the following blog we will discuss how predictive maintenance and the associated benefits regarding cost and time-savings can be adopted by businesses from all industries.

What is Predictive Maintenance?

Going by its simple definition, performing maintenance means to ensure a piece of equipment is kept in good working order. Traditionally, it was common place for organisations to put a maintenance schedule in place that would determine when equipment would be serviced. Unfortunately, that did not always translate to equipment functioning at best capacity, as issues and failures could occur between scheduled servicing. Equipment failure of this type often requires costly repairs, increases downtime, which in turn reduces service and productivity.   

Predictive maintenance offers a solution. It refers to measuring operational conditions to detect early warning signs of sub-optimal performance which allows any issues to be corrected before they cause serious problems. Operating data gathered from HVAC, refrigeration or lighting equipment can be processed by software that will determine when intervention is required. Responsive actions are taken based on actual operating data rather than on pre-set maintenance schedules. 

Utilising predictive maintenance brings a host of benefits: less machine downtime, decrease in maintenance costs, longer equipment life, and fewer unscheduled service technician call-outs.

The US Department of Energy has conducted a study on the different types of maintenance and has found that the predictive type can produce outstanding cost savings and an increase in productivity in many different areas of the business:

• Return on investment: 10 times
• Reduction in maintenance costs: 25% to 30%
• Elimination of breakdowns: 70% to 75%
• Reduction in downtime: 35% to 45%
• Increase in production: 20% to 25%.

The Internet of Things and Industry 4.0

Predictive maintenance ties in with utilising the Internet of Things (IoT), which describes networks of integrated smart devices which send and receive data through internet connections. The IoT has played a key role in the recent digitalisation of manufacturing and building management worldwide. This phenomenon is often referred to as the fourth industrial revolution, or Industry 4.0. 

Installing connected devices, ideally those based on open protocols, is essential for a business to benefit from the IoT, Industry 4.0 and predictive maintenance. Integrated devices capable of communicating with each other and a central system allows data to be collected and sent to predictive maintenance software for analysis. 

Remote Monitoring & Predictive Maintenance Solutions

In order to gain the full benefits from predictive maintenance, it is essential to select capable solutions. Resource Data Management’s (RDM’s) ActiveFM™, enterprise-level remote monitoring and energy management software is a comprehensive option. Accessible via a web browser, ActiveFM™ dashboards support remote monitoring and predictive maintenance strategies using data received from IoT devices.

It can be set up to predict system failures, automatically handle incidents and provide the insight required to correct issues remotely. Data insights and automated predictive maintenance provide comprehensive asset and facility management. Add-on software options include Kwheb, a cloud-based energy dashboard and Live Maps, a real-time map view of HVAC, refrigeration, and lighting devices across multiple sites.

RDM’s open protocol, IP-based control system head-end, DMTouch is ideal for predictive maintenance of HVAC and refrigeration equipment. The DMTouch aggregates all control devices in a site and provides vital live data that can be used to quickly identify potential issues. 

For refrigeration devices, the Temperature Performance Indicator (TPI) feature uses live data to assign a performance score on a colour-coded scale from 1 to 10. A refrigeration case performing optimally has a score of 1 (green), while a poorly performing case will have a score of 10 (red).  An increasing TPI score can generate alarms and allow users to identify issues early, potentially avoiding costly repairs. The TPI score can be easily accessed by users across a network simply using a web browser on a PC or mobile device.  The TPI feature is inherent to the DMTouch, but ActiveFM utilises this tool on an enterprise level to quickly identify problem sites and devices.