Maintenance Statistics: Predictive & Preventive, Labor & Costs

Maintenance planning requires solid data, much of which you’ll obtain by collecting information on your own operations. It also helps to know what’s happening in the industry as a whole—that way, your own metrics are compared within a larger context. This ultimately helps you gauge where your own maintenance management processes are. You’ll get an idea of where you’re doing well and where you might need to make improvements in terms of maintenance management.

In addition, these statistics show just how important modern technologies are in terms of improving operational reliability, no matter how well you’re doing in comparison with the industry overall.

Maintenance costs, budgeting and spend

Maintenance costs are estimated to range between 15% and 40% of total production costs (Dunn, 1987; Lofsten, 2000).
Exterior building maintenance costs about $0.03 per square foot for industrial buildings (BOMA, 2018).
Running a piece of equipment to the point of failure could cost up to 10 times as much as a regular maintenance program would (Buildings.com, 2018).
Every $1 worth of maintenance deferred could quadruple to $4 in capital renewal costs later on (Biedenweg).
Predictive maintenance is highly cost effective, saving roughly 8% to 12% over preventive maintenance, and up to 40% over reactive maintenance (according to the U.S. Department of Energy).
Between 2004 and 2008, the U.S. spent about 57% of its transportation infrastructure budget on new construction projects. The 43% leftover was spent on maintaining the 98.7% of roads remaining.
The U.S. has over 47,000 bridges that are considered to be in urgent need of repairs, while 38% of all America’s bridges need some form of repair work. It would take about 80 years to complete it all.
The global market for enterprise asset management software is valued at $4 billion, and it’s expected to grow at a CAGR of 11% per year. At that rate, its value will have doubled to $8 billion by 2022.
As of 2018, about 53% of facilities use a CMMS to monitor their maintenance. Additionally, 55% use spreadsheets and schedules, and 44% still use paper.

CMMS and Software Adoption

In 2017, 78% of companies who used a CMMS to manage their assets reported seeing improvements in equipment life.
Up to 80% of all attempted CMMS implementations fail.
Perhaps coincidentally, about 80% of all CMMS users don’t use all the functions offered by the software.
For one company in 2017, data visualization software reduced production hours by 320 hours while also increasing production by 15%.

Types of maintenance

According to Plant Engineering’s 2018 maintenance survey, preventive maintenance is favored by 80% of maintenance personnel.
In the same survey, it was shown that usage of predictive maintenance had risen from 47% to 51%, and that running equipment to the point of failure had dropped from 61% to 57%.

Predictive Maintenance

The overall use of predictive maintenance rose from 47% in 2017 to 51% in 2018, though preventive maintenance is still preferred by 80% of maintenance personnel.
80% of manufacturing plants use preventive maintenance, and over half use predictive maintenance with analytical tools.
In 2012, the U.S. Bureau of Labor Statistics estimated that the nation would be short 10 million workers over the course of the following six years.
Roughly 10% (and maybe even less) of industrial equipment ever actually wears out, meaning a very large portion of mechanical failures are avoidable.
Predictive analytics yields a tenfold return on investment, and it results in a savings of 30% to 40%.
As of 2018, the most common challenge facilities face is lack of resources, including human, technical, and strategic resources. The number of facilities who considered this a challenge was li 49%.
Historically, total productive maintenance has been shown to increase plant capacity by over 10% and productivity by 50%, but over half of all attempts to implement TPM result in failure.
79% of businesses see predictive maintenance as the main application of industrial data analytics.

Maintenance personnel

The median salary of an industrial maintenance technician came out to $50,440 in 2017 (Bureau of Labor Statistics).
The motor vehicle manufacturing industry pays the highest salary for maintenance technicians at $69,830 in 2017 (Bureau of Labor Statistics).
Maintenance technicians are most widely employed by the plastics manufacturing industry at 3,830 employees. The next runner up was motor vehicle parts manufacturing with 2,750 workers (Bureau of Labor Statistics).
First line supervisors of maintenance workers tend to earn more, averaging at $68,120 per year (Bureau of Labor Statistics).

Time management

Out of an average working day, only 24.5% of the average maintenance worker’s time is spent performing productive tasks (Plant Services, 2003).
Doing the math for an average maintenance technician based on average salary, the total time spent on unproductive tasks comes out to about $38,082 in labor costs per personnel per year.
An estimated 20.9% of wasted time results from travelling to different areas in the facility, with an additional 19.8% resulting from waiting for instructions (Plant Services, 2003).
Poor maintenance strategies can reduce a company’s production capacity by as much as 20% (Wollenhaupt, 2017).

Production downtimes

Roughly 82% of companies experienced at least one instance of unplanned downtime in the last three years (ServiceMax).
A 2005 survey published by Thomas Industry Update found that the average cost of unplanned downtimes in the automotive industry amounted to $22,000 per minute.
The average age of industrial assets in the United States is about 20 years, according to the Bureau of Economic Analysis. The number has grown significantly since 1990.
Aging equipment is the leading cause of unplanned downtimes at 50%, with lack of time coming in at 14%, according to a 2016 survey by Plant Engineering.
About 44% of all unscheduled equipment downtimes result from aging equipment, making it the leading cause of unscheduled downtime.
Unplanned downtimes cost an estimated $50 billion every year.
Overall, downtime costs most factories somewhere between 5% and 20% of their productive capacity.

Safety

Poor compliance with lockout/tagout standards ranked number five in OSHA’s most frequently cited violations in 2018.
Up to 30% of all manufacturing deaths are related to a maintenance activity.
Companies can save between 12% and 18% by using preventive maintenance over reactive, and each dollar spent on PM saves an average of $5 later on.
Factories throughout the U.S. are estimated to be using about $40 billion worth of outdated equipment.

Internet of Things (IoT)

As of 2017, about 53% of companies adopted big data analytics, which includes predictive maintenance and IIoT technologies.
By 2024, IIoT technologies are predicted to help create nearly $800 billion in economic value.
Roughly 30% of all manufacturers have difficulty understanding IoT.
Even so, as of 2018 nearly half of all manufacturers are placing greater emphasis on IIoT technologies.
Worldwide spending on IoT technology is estimated to reach $1.2 trillion in 2022 with a CAGR of 13.6%.
The number of connected devices in use worldwide is estimated to be over 17 billion, with 7 billion IoT devices.

Maintenance Career Outlook

The U.S. employs a total of over 80,000 machinery maintenance workers.
The nation also has over 131,000 aircraft service technicians and mechanics.
About 1.3 million people currently work as general maintenance workers, with 302,000 working in the real estate sector.
The job outlook for maintenance professionals is projected to grow at about 8% over the next ten years.
The average salary for a maintenance technician in 2019 is just under $39,000 per year.
The top paying industry for machinery maintenance workers is the Federal executive branch at $72,350 per year as of 2019, followed closely by motor vehicle manufacturing at $71,330.

How to use the data

By comparing your own metrics to the data listed above, you can get a clearer idea of where your facility stands in terms of maintenance effectiveness.

For example, if your maintenance costs seem a little high compared to those listed above, there may be something amiss in your processes. You may be deferring maintenance too often, thereby allowing assets to age too much without regular upkeep, or you may have some inefficiency in personnel management.

It’s also important to note that a general trend may not necessarily apply to your situation. For instance, running equipment to the point of failure without regular maintenance can get expensive from a cost-effectiveness standpoint. However, if you already have aged assets at your site, you’ll need to compare the cost of replacement to that of maintenance. In some cases, an equipment upgrade could make more sense than performing additional repair work.

Ultimately, industrial data can help you make important decisions regarding your maintenance strategies, especially when combined with a thorough understanding of your own metrics.