Condition-based Maintenance Maintenance On The Floor Predictive Maintenance Preventive Maintenance Reliability

Aging Equipment Isn’t the Problem

Klaus M. Blache | October 10, 2018

Q: How much does equipment age matter?

A: It depends on your maintenance practices. Costs may go up even if you have a robust maintenance process; it may be difficult to get replacement parts. Costs can increase if you don’t do precision maintenance or don’t follow good lubrication practices. However, if you maintain your machinery and equipment correctly, most old equipment will have minimal impact on reliability and uptime. In several companies, I’ve observed equipment that is more than 100 years old, and it’s still running well.

In a report from the Congressional Budget Office, Washington (,  “The Effects of Aging on the Costs of Operating and Maintaining Military Equipment, 2001,” it was estimated that spending on O&M for aircraft increases by 1% to 3% for every additional year of age, after adjusting for inflation. However, the report also included such things as rising medical costs and new technology. Details were not provided for items such as parts and fuel costs. This information would allow us to analyze equipment-related costs in more detail.

According to the report, “The Office of the Secretary of Defense publishes the Operation and Maintenance Overview each year, which breaks out O&M spending in various ways. However, none of those breakouts can be aggregated to create an estimate of total O&M spending on equipment.” So, the slight repair cost increase each year (if it’s really maintenance) needs to be evaluated against the cost of a replacement.

A key item to monitor is reduction in equipment functionality or downtime. My experiences and data show that, when equipment is properly maintained, age has minimal impact on reliability. Yes, at some point in time, age will become a factor, but it’s usually because other reliability and maintainability principles were violated. That’s why doing life-cycle costing, with R&M principles in mind, is so important.

From RCM II Reliability-Centered Maintenance (John Moubray, 1992 &1997, Industrial Press Inc.) and a Nolan and Heap study conducted in 1978 for the airline industry, we see six failure-pattern curves that show conditional probability (likelihood of an event happening based on the occurrence of a previous event) of failure and operating age for various mechanical and electrical components. These concepts are encompassed in the technical standard “SAE JA1011, Evaluation Criteria for a RCM Process,” which details the minimum criteria that any process should meet before it can be called RCM (reliability-centered maintenance).

This work indicates that less than 20% of failures are age related. The other 80% are random events over time. With most failures being unpredictable, a robust predictive-technology program (where applicable) and more so, condition-based maintenance, makes the most sense. Collect data, do root-cause analysis, and remove failure modes or you will simply be reactive to random failure. You need to eliminate the physical events and human error that cause these random failures. It’s equally important to perform ongoing continuous improvement and share learning to have an impact on future purchases. Maintainability is a designed-in parameter and should be in your purchasing specifications.

Some reasons for machinery and equipment (M&E) failures are:

• Operations runs equipment too hard/long before turning it over to maintenance.

• Maintainers are not properly trained in precision maintenance.

• M&E was not properly designed or installed.

• Too much early maintenance has introduced more “infant mortality.”

• Lower-quality parts were substituted because purchasing buys “as equal” to save money.

• Trying to save money (buying from the internet for low-cost reasons) has introduced counterfeit parts.

• PM optimization was never performed to assure that the best PM tasks are in place.

• Quality historical data was not collected, thus preventing effective improvement decisions.

• Spare parts are not stored properly, which reduces part life.

• Due to large maintenance backlogs and other priorities, PMs are not completed.

• Personnel don’t use good lubrication practices.

• There is no robust predictive technology/condition-based monitoring and root-cause analysis process in place to continually find and fix.

• Without a standardized best-practice maintenance process in place, maintenance is too reactive.

Part of the solution is also fixing the overall maintenance culture. Consider the following statements. From Nick Dagres, shop manager at Hydro Inc., Chicago: “When a new machinist arrives, we stand with him and show him how the machine works and how it operates. We give him the checklist and train him on how to fix problems that may arise. Our goal is to continue maintaining our preventive program so that the machines will run another 30 to 40 years,” (Keeping Old Machines Running Like New,” Efficient Plant, Jan. 2016).

Forty-five percent of Best-in-Class companies have “on-demand asset lifecycle information easily accessible by maintenance and production employees.” The industry average for this was 27% and Laggards were at 22%. Just some of the key differentiators between groups were Best in Class (13% reduction in maintenance cost and 2% unscheduled asset downtime), Industry Average (5% reduction in maintenance cost and 5% unscheduled asset downtime), and Laggards (1% increase in maintenance cost and 7% unscheduled asset downtime). (Aberdeen Group study, “Maintenance, Repair, and Operations (MRO) in Asset Intensive Industries,” Feb. 2013, Nuris Ismail and Reid Paquin).

The management of aging equipment starts with the realization that “aging” is not how old the equipment is. It’s also about how many hours per day and days per year it runs. What environment (heat, dust, wet) is it in? How long will it last if it’s run to failure? What can be expected if we perform proper maintenance? This is part of using tools such as life-cycle costing and reliability growth analysis (Weibull) to help you better understand when to repair, upgrade, or replace. EP




Klaus M. Blache

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