Many industries benefit from predictive maintenance. Implementing smart devices and sensors for condition monitoring is a strategic business decision to optimize productivity while minimizing cost. Since the initial capital cost of condition monitoring technology can be expensive, it is important to evaluate the pros and cons of predictive maintenance to ensure you reap the most benefit for your business.
Pros of Predictive Maintenance
The decision to use predictive maintenance for your business comes with several benefits.
Minimize costs of unnecessary inspections and repairs
Predictive maintenance allows you to take the guesswork out of maintenance and only tend to inspections and repairs when necessary. Without predictive maintenance, your business relies either on a set schedule of maintenance or waiting until a malfunction occurs – both of which are costly to business productivity and revenue.
By following a set schedule, it leads to inspections and repairs when they are not needed, thus leading to inefficient use of resources, such as time, labor – and potentially downtime on machines. By using predictive maintenance, cloud-computing software and strategically placed sensors allow you to detect abnormalities and analyze data that suggest steps to evaluate - before severe damage or equipment downtime occurs. It ensures that you can tend the machines that need tending to when they need tending to – thus creating a more efficient and productive maintenance schedule.
Maximized equipment lifespan due to necessary repairs and upkeep
Predictive maintenance helps prevent any real equipment damage from occurring, so you can have peace of mind about the functionality of your assets. Additionally, by consistently monitoring your machinery, data can indicate abnormalities that need repair before they affect other parts of the machine or process. This allows you to maximize the total lifespan of your equipment through necessary repairs when detected through condition monitoring.
Predictive maintenance, while it may be costly upfront, can prove to be significant cost savings for your business overall. By protecting your most valuable equipment, you can not only expand the lifespan of the entire machine or process but make necessary adjustments or repairs when abnormalities are detected through condition monitoring. Additionally, predictive maintenance has proven to decrease downtime in business. Rather than having to make a costly – and timely – repair when a machine malfunctions, phased approaches to maintenance allow for little, to no, downtime. Having a constant flow of productivity, and the reassurance there is an unlikely chance of the machinery being out of commission, are benefits businesses experience after using predictive maintenance in their workplace.
Cons of Predictive Maintenance
While there are many benefits to predictive maintenance, there are also some disadvantages of which businesses need to be aware. A few of them are:
Cost of implementation
There is no getting around the fact that predictive maintenance can be an expensive capital investment. Depending on the type of condition monitoring technology, there will also be sensors, printed electronics, cloud-based data gathering, and a data dashboard that at a minimum will need to be implemented. At this point, one would question if another necessary cost would be hiring a professional with specialized credentials to read and interpret the data. Brewer Science’s Printed Electronics and Smart Devices Foundry specialize in providing actionable data. Your current maintenance team would be able to understand the information and take actions accordingly – without the need for highly specialized training. However, this is not the case for all companies who provide predictive maintenance technologies, since their platforms could require more lengthy training, thus making another “con” for them to be downtime of their personnel as they learn the new programs. Brewer Science’s approach to the data interpretation is easily understandable, and we take a specialized approach to understand our customers' needs and expectations of the project.
It is not perfect (but pretty close)
When making the transition to condition monitoring and predictive maintenance, some customers might have the pretense that the future of their processes will be completely automated or that maintenance will only be needed whenever the program tells you to, and it will always be 100% accurate. Unfortunately, that’s not always the reality. Technology can fail to take essential factors into account when analyzing an asset, such as the age of equipment and weather. There is also the potential of misunderstanding readings or not calibrating sensors properly. However, through the specialized approach of assisting each customer with a customized approach to their unique business needs, we have found that Brewer Science’s Printed Electronics and Smart Device Foundry provides customers with the most satisfying results in the industry.
Predictive Maintenance might not be right for your business
Not all assets that have failures are costly. For those assets, other maintenance strategies such as preventive maintenance or reactive maintenance may be more suited for your business. It just all depends on the industry you are in, and the machinery that is used. Ask yourself, Is predictive maintenance right for my business?
Brewer Science leverages 40 years of diverse experience to bring innovative solutions to customers' unique business needs. No matter the industry or the application, a talented team of engineers brings together material expertise and innovative creativity to help you achieve your business objective. Monitoring machinery functions, industrial functions, temperatures of machines or the environment, the moisture or water content, or even valve performance can ensure you do not miss important productivity concerns and lose productivity due to downtime. To learn more about Brewer Science’s Flexible Hybrid Electronics Foundry and how you can use it to implement predictive maintenance in your business, talk to an expert today.