Calculating the Impact of Predictive Maintenance on Productivity

In previous articles, we have discussed the benefits of predictive maintenance in general and condition monitoring in particular when compared with less effective strategies including preventive maintenance and reactive (also referred to as breakdown or run-to-fail) maintenance. In this article we answer a question that is typically asked from financial justification perspective: how much does predictive maintenance impact the productivity of a workplace?

A number of scientific studies have been performed around the world by various universities, companies and organizations, each producing similar results. Said results are as follows: a successfully implemented predictive maintenance strategy, though it may involve up-front costs both financial and temporal in nature, ultimately will significantly improve the overall productivity of a workshop. How this occurs, and how such improvements can be calculated and quantified, are discussed in greater detail below.

Defining “Productivity”

In order to properly address this topic, another question must first be asked: what is productivity, and what factors affect it? The standard definition of productivity commonly used in the manufacturing world is: the effectiveness of a productive effort, specifically focusing on the rate of units of output per unit of input.  Typically, productivity in industry is measured both by the sheer amount of product produced and by the monetary profits which this amount of product provides for the company.

A typical productivity calculation involves three key factors:

  • Quantity:   How much of the product is being generated? How long is one complete cycle, i.e. the amount of time required to produce one unit? Are the machines involved in the production process working at their full speed at all times? Does the machine require stopping for upkeep tasks such as cleaning or oil replacement? Is there any unplanned downtime due to machine failure or operator error?
  • Quality:   How much of the product is of a sufficient quality to be usable and/or sellable? Are products being created which are damaged or defective in any way? How much time is required to dispose of these products or to recycle or repurpose their component materials and return them to the production process? How much of the input resources are being wasted in the accidental generation of defective products?
  • Cost:   How much money does it take to produce one unit of product? How many raw materials are required? Does it require utilities – water, electricity, gas, steam or any other – to produce? Does it result in any emissions or environmental waste which may be subject to taxes or other additional fees? How many employees are required to operate each machine or otherwise participate in the production process? What are the salaries of each of these employees? Do they require any specialized training which incurs an additional cost? Has the machine caused safety or health problems which require further financial resources to solve, such as the payments of workers’ compensation to an injured employee or employee turnover/replacement? 

A workplace is therefore at its most productive when it is outputting a high quantity of products with a low cost per unit and all of the products are usable with none being damaged or defective in any way. A productive workplace is also usually one which makes a very high monetary profit, as production costs are low, employees work efficiently and are properly trained, and money is not wasted on throwing out the resources used in the accidental creation of damaged products.

The Role of Maintenance in the Productive Workplace

What role, then, does maintenance play in helping a workplace achieve its maximum potential productivity? Do inefficient, improperly implemented, or totally absent maintenance strategies have any negative impacts on overall productivity?  Maintenance plays a large role and allows for significant improvements in productivity, while a lack of maintenance or inefficient, outdated methods can often cause significant decreases in overall productivity values.

In order to understand the effects of maintenance on productivity, both positive and negative, it is best to look at the ways in which it impacts each of the three elements discussed in the previous section.

The effects of maintenance on overall quantity are probably the easiest to list and identify. A well-maintained machine experiences fewer unplanned shutdowns due to mechanical, electrical or operational failure. In addition, strategies such as predictive maintenance and especially condition monitoring are able to identify degradation or decline in speed and efficiency well in advance of the occurrence of total failure. This allows employees to perform the necessary upkeep or repair tasks at the earliest possible opportunity, keeping the machines running at full speed and capacity and allowing them to produce the maximum number of units possible. Condition monitoring comes with the additional benefit of being able to collect performance data while the machine is still running, further decreasing both the necessity of planned downtime and the risk of unplanned downtime.

Regular upkeep tasks, such as cleaning and oil replacement, have also been shown to significantly increase product quality, as they decrease the risk of producing defective units. In addition, the ability to detect degradation in advance further decreases that risk, as failures in rotating parts, motors, electrical power supplies and more can be rapidly repaired before they have the ability to negatively affect the quality of the final product.

The majority of condition monitoring devices collect large amounts of performance data on a regular, often 24/7, basis. This data can be shared with the manufacturers of the machine in order to produce upgrades or updated versions which are even more productive, in terms of both quantity and quality, than before. Condition monitoring, more than any other maintenance strategy, allows for long-term quality and quantity improvements in all areas of the workplace, including the design and manufacturing of the machine itself.

Lastly, the implementation of predictive maintenance has also proven to result in significantly decreased production costs over time. First and foremost, it is significantly cheaper to replace individual parts or perform regular upkeep tasks than it is to replace the entire machine after too much degradation or total failure has been allowed to occur. Secondly, the increased lifespan of machines provided by successful implementation of predictive maintenance technologies further decreases costs by making even necessary part replacements occur less frequently.

Machines monitored via predictive maintenance are also significantly less likely to pose health or safety risks to employees than those which are maintained in other ways or not maintained at all. The core tenet of predictive maintenance is the ability to detect and repair potential problems well in advance of catastrophic failure. This increased knowledge of the machine’s overall health means that ‘spontaneous’ failures, including potentially dangerous ones such as sparking, fire, combustion or rotating parts moving in unnatural ways, will not affect employees. While the decrease in cost associated with safer machines may not be as immediately obvious, it usually means that companies will not have to expend money no risk employee-moral on potentially lengthy, cost-heavy incidents such as the injury of an employee by a machine.

The positive effects of predictive maintenance on overall production costs may not be obvious because most condition monitoring devices are perceived as 1) requiring a significant up-front cost and 2) requiring extensive and often expensive employee training in order to properly operate the hardware and interpret the data which it provides. However, recent innovations in the development of condition monitoring devices have significantly minimized these problems; as a result, implementing a condition monitoring program even for small manufacturing plants or less than critical equipment can offer a significant decrease in production costs in the long term.

For example, the Tactix™ device, developed by Proaxion©, is capable of performing a number of condition monitoring tasks, including vibration and temperature analysis continuously, 24/7. In addition, it is “plug and play”, does not require integration with the plant IT systems and can be installed and providing data within an hour. The software component organizes the data in a readable, easy-to-understand format, and does not require employees to be extensively trained in order to understand key information about the machines’ health and performance.  The system comes at an affordable price, well below typical capital expenditure limits.

In conclusion, predictive maintenance and especially condition monitoring can improve the overall productivity of a workplace by targeting all three of the key areas, quantity, quality and cost. Any upfront costs necessary to implement the program and educate employees are outweighed by long-term improvements to all parts of the manufacturing process. A workplace successfully utilizing predictive maintenance will possess safe, efficiently functioning machines and employees with a better understanding of the inner workings of the equipment which they operate. Over time, a significant increase in profits is observed with plants that enable predictive maintenance and condition monitoring.

If you have any questions or are interested in evaluating the Proaxion© Tactix™ system for a condition monitoring plan in your workplace, please contact us.