Tag: predictive maintenance

Is your approach to facility management largely focused on planning, scheduling, and assigning maintenance tasks at regular, fixed intervals? This approach, called planned preventive maintenance, is still widely used at most facilities. However, in order to further maximise equipment uptime and utilisation rates, many facilities are switching to a newer, more data-driven style of maintenance – predictive maintenance (PdM).

To put things in perspective, the global market for predictive maintenance was valued at $9.15 billion in 2023. The market is now set to grow at a CAGR of 24.2% from 2023 to 2033 and is expected to reach a whopping $79.9 billion by 2033!

The first in a series of four, this article covers:

• the basics of predictive maintenance, 
• how it differs from its more traditional counterpart (preventive maintenance),
• some scenarios where it is becoming popular among facilities today, 
• how it improves the bottom line for businesses, and
• some questions for you to decide if it’s right for your facility

What is Predictive Maintenance?

As the name suggests, predictive maintenance is a “forward-looking” maintenance strategy designed to predict when an asset needs to be fixed, replaced or when any corrective action needs to be taken to optimise asset performance. Also known as condition-based maintenance, it involves the use of sensors, Internet of Things (IoT), data analytics and other smart building technologies to monitor the condition of assets during day-to-day operations and schedule maintenance before the asset breaks down. 

Predictive maintenance has been around in the industrial world since the early 1990s, but its implementation is still fairly low in comparison to more traditional methods like preventive and reactive maintenance. When utilised timely and correctly, PdM can help facilities increase efficiency and productivity, while allowing asset lifespan to be maximised and maintenance costs to reduce over time. 

Preventive vs. Predictive Maintenance – What’s the Difference?

Predictive maintenance and preventive maintenance are both proactive approaches, but work toward the same goal of keeping facility assets in best working condition in different ways.

Preventive maintenance is maintenance that takes place on a regular basis irrespective of asset conditions. On the other hand, predictive maintenance is carried out only when it’s needed, depending on asset conditions.

Preventive maintenance is primarily performed on the basis of time-sensitive triggers (i.e. weekly, monthly, or annually), or on the basis of usage (i.e. after every 100 times used).

A downfall of preventive maintenance is that it may lead to doing too much maintenance on an equipment. It relies on the assumption that consistent checking will uncover any faults and give you enough time to correct them before they cause failure. Alternatively, predictive maintenance allows maintenance frequency to be much lower, and at the most convenient and most cost-efficient moment, before the equipment has been compromised. 

3 scenarios where predictive maintenance (PdM) is gaining popularity

1. Facilities are spread across different geographical locations

Consider a provider of commercial refrigeration storage units to food retailers across the country. Under a preventive maintenance program, workers would be dispatched on a regular basis to inspect the units. This method ignores the potential of anything going wrong in between scheduled visits. In this case, the costs could be high, with emergency repairs, food waste, and lost revenue during downtime bearing heavily on the business .

Under a predictive maintenance program, all units would be fitted with IoT sensors to measure various aspects of their operation, including humidity levels, compressor vibrations, temperature, etc. With real time data analytics indicating when a component is likely to malfunction, a maintenance technician can be dispatched to rectify the problem before it even occurs.

2. Facilities have pieces of equipment that are critical in nature or belong to a high-risk industry

Not all pieces of equipment and systems are equally critical to a facility’s operations. Highly critical assets often impact organisational safety, compliance with regulation, cost, or regular business functionality. Failure of these assets can result in major setbacks.

An offshore oil platform, for example, is a high-risk facility that has a number of critical production assets such as heat exchangers, pumps, and compressors. If a problem emerges with any of these assets between routine preventative maintenance inspections, output could be halted permanently, or worker safety could be compromised. Predictive maintenance, on the other hand, allows you to detect any anomalies in the performance of these critical assets and instantly alerts you to an impending failure. 

3. Asset owners want a more cost-effective approach to maintenance

Early detection of equipment faults provides a number of advantages. These include reducing downtime, preventing last-minute emergency repairs, and prolonging the usable life of your equipment. So, for asset owners looking to save money for the company, PdM is a better option than preventive maintenance. 

Predictive maintenance can also increase productivity, and eliminate as much as 30% of all time-based preventive maintenance tasks. Preventive maintenance can sometimes accelerate failure of asset components, since disassembling and/or reassembling can potentially increase the probability of a future breakdown. This becomes especially critical in situations where downtime can be disastrous, product/service delivery quality is at stake, and machinery replacement costs are extremely high.

Does predictive maintenance really pay off?

According to Gartner, decision automation in the form of predictive maintenance will offer the most business value for heavy asset enterprises.

A report by Deloitte confirms that, on average, predictive maintenance improves productivity by 25%, and slashes maintenance planning time by 20-50%. It also reduces equipment breakdowns by 70% and increases equipment uptime by 10-20%. 

Further, research from the US Department of Energy shows that a successful predictive maintenance program can result in a 10 times increase in ROI, a 25-30% reduction in maintenance costs, and a 35-45% reduction in downtime.

Is predictive maintenance the right choice for your facility?

Predictive maintenance requires significant investment in terms of capital, technology, and personnel training. While these investments may appear intimidating to a company, the ROI on PdM typically transcends any initial costs. To decide if it is the right choice for you, ask yourself the following questions:

• What is the estimated value of my facility assets or equipment?
• Are the assets critical to business operations and continuity?
• What do past records reflect in terms of downtime, faults, losses, and potential safety hazards?
• Is my company currently able to afford or invest in predictive maintenance technologies or experts?

If your answers to these questions match the three scenarios we discussed in this article, you should focus on implementing a predictive maintenance software for asset management at your facility.

Want to read more on predictive maintenance? Head over to the next article in this series!

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.