This article is the 2nd instalment of a 4-part series on predictive maintenance.

An ideal world would be one where we would need to carry out the least amount of maintenance to maximise asset performance and uptime. But how can we know when it’s time to execute that maintenance?

Predictive maintenance provides an answer. Predictive maintenance isn’t new, but with technologies such as real-time condition monitoring, artificial intelligence (AI), machine learning (ML), analytics, and cloud platforms, there’s a lot more advancement and accuracy in predictions of asset failure and providing recommendations for corrective actions. Predictive maintenance software for asset management has shown outstanding results.

When it comes to verifying the value of a maintenance or asset management program, learning from industry examples is the next best thing to conducting your own proof of value trial. Predictive maintenance can drive big gains in a variety of industry sectors. Companies in every industry are striving to increase reliability at their facilities by testing and investing in novel approaches to optimise their assets. Listed below are five high priority industries that benefit from predictive maintenance, including real-world examples: 

Five Industries that benefit from predictive maintenance

1. Manufacturing

The most prominent industry tied to predictive maintenance is the manufacturing industry. Manufacturing operations almost exclusively rely on heavy assets and machinery, and the scope of malfunctions is enormous. Big manufacturers can lose an average of $22k every minute when operations become paralyzed due to asset failure. 

With the rise of Industrial Internet of Things (IIoT) and other technologies of Industry 4.0, asset maintenance in manufacturing is becoming more predictive and automated. The industry has cut substantial costs by eliminating avoidable reactive maintenance and improving asset performance. 

Predictive maintenance examples in the manufacturing industry:

Using predictive maintenance, Canadian pulp and paper manufacturer Mercer Celgar achieved a striking reduction in equipment failures from 50 per year to 5 per year. In addition, they reduced their pump replacements from 123 in 2007 to 15 in 2018. 

Alumina manufacturer Noranda Alumina LLC, Los Angeles, United States realized a 60% decline in bearing replacements since implementing a predictive maintenance program in 2019. This saved the company approximately $900,000 in bearing purchases and costly downtime.

2. Food & beverage 

The market for food and beverage processing equipment was valued at USD 58.3 billion in 2021, and it’s expected to touch USD 76 billion in 2026. As the demand for healthy functional foods and beverages grows, the industry will require more advanced processing and storage equipment. Food and drink storage facilities also have to tackle stringent regulatory standards and maintenance challenges related to safety and hygiene.  

Enter predictive maintenance technology. With proper monitoring of critical equipment such as refrigeration, air handling and purifying units, it could analyse the temperature and vibration to alert the staff when maintenance would be needed. Any potential issue would be addressed before it caused downtime, lost supplies, or, most critically, a threat to customer health and safety.

Predictive maintenance example in the food and beverage industry:

Food and beverage company Frito-Lay reduced planned downtime to 0.75% and unplanned downtime to 2.88% by introducing a robust program of predictive maintenance technologies. The technology assisted in preventing the failure of a PC combustion blower motor, which could have resulted in the indefinite shutdown of the entire potato chip department.

3. Power & energy

Another industry where predictive maintenance delivers big gains is power and energy. What makes predictive maintenance in this industry so crucial is the fact that its continuous functioning powers entire cities and nations, and any equipment failure can halt economic activity at a very large scale. 

Detecting problems and fixing them ahead of time lowers inspection costs, protects the energy sector from huge expenses on repairing/replacing assets, and strengthens worker safety by improving equipment reliability. 

Predictive maintenance examples in the power and energy industry:

According to GlobalData’s research, Duke Energy, a large power provider in the United States, used predictive maintenance and asset optimization to deal with cost overruns involving wind turbines and other equipment.

European electric utility company E.ON leveraged technology that utilizes artificial intelligence (AI) to notify potential failures prior to their occurrence.

The same research pointed out that predictive maintenance is instrumental in alleviating serious issues such as leading-edge erosion (LEE) of wind turbines that can decrease annual energy production by upto 5%.

4. IT & Digital Infrastructure

Almost every service we use today is dependent on computer hardware, from government agencies and hospitals to data centres that run the financial sector and IT technology that controls navigation and telecommunications. It’s easy to see how a protracted period of service outage or data loss may result in a massive disaster affecting millions of people. Fortunately, predictive maintenance is one of the methods for lowering the chances of this ever occurring.

The financial consequences of data centre outages are enormous. For every hour of downtime, businesses lose an average of $138,000 in revenue. To put this in context, every second Amazon.com goes down, Amazon stands to lose $1,104! 

Predictive maintenance example in the IT industry: 

A project at the Large Hadron Collider (LHC) Grid data centre currently placed at the INFN-CNAF research institute in Bologna, Italy is incorporating predictive maintenance technology to keep computing systems optimal, increase operational efficiency and reduce costs.

5. Buildings

Buildings can benefit greatly from the implementation of predictive maintenance software. Heating, Ventilation and Air Conditioning (HVAC) is an excellent candidate for predictive maintenance inside a building as equipment failure can cause severe problems and costs. Condition-based monitoring of critical components such as compressors, fans and motors in real time can detect anomalies and maintenance can be performed before a problem occurs.

Predictive maintenance examples in the buildings industry: 

Commercial real estate maintenance company Enertiv said predictive maintenance reduced costs by an estimated 25%, with a 50% reduction in major equipment failures and extension of equipment life from 20% to 36%.

According to Knight Frank, a predictive maintenance program was conducted at a 29-storied office building in Australia that incurred routine maintenance costs between $95,000 and $190,000 a year. An extra $50,000 to $120,000 were spent on building repairs. The program involved just the building’s HVAC system, but it resulted in savings of $16,742 in operating costs and $32,300 in repair costs per year.

Read the first article in this series to see why predictive maintenance is gaining popularity among building and facility managers. 

Do you belong to any of the five industries we mentioned above? Have you employed predictive maintenance at your facilities yet? There are many more industries where asset management initiatives like predictive maintenance can drive cost savings for your business. Schedule a call with us to learn more.