Using Predictive Analytics to Improve Your CMMS

This post was written by Lisa Dunn from Technology Advice. 

The statistics are illuminating: According to a 2017 report, poor maintenance strategies can lower a facility’s productive capacity up to 20 percent. Another study revealed last year that unplanned downtime could cost industrial manufacturers approximately $50 billion per year.

There is no question that today’s businesses and facilities depend on their equipment. In the world of manufacturing, for example, high-tech machines produce products to sell. In the healthcare space, countless pieces of cutting-edge equipment save lives. No matter the industry, machines end up being the focal point – and any downtime can significantly damage operations.

Fortunately, there are numerous Computerized Maintenance Management Systems (CMMS) on the market available to help facility managers and enterprises simplify tasks such as managing maintenance, scheduling repair, tracking spare parts, and monitoring machine lifecycles.

In fact, by introducing CMMS software to your company, you can eventually replace the outdated combination of logbooks, paper records, spreadsheets, and emails –  traditional methods that can make it challenging to track maintenance schedules, view repair histories, maintain spare parts inventories and stay on top of overall spending.  

With predictive analytics and preventive maintenance technology, you can place a sensor device on your machines’ motors to stream data about each piece of equipment’s condition directly into the CMMS. Then, a work order can be automatically generated when the data reveals that a problem may arise.

How Does It Work?

With a predictive analytics strategy, you mount sensors on your equipment that send a stream of data directly to your CMMS. You can opt for hand-held devices or mounted sensors. You can enter and present this data in your CMMS in a list format, allowing team members to view the asset name, the type of meter reading, the date of the reading and the value.

As a result, those specific team members responsible for maintenance can gather data rapidly from the connected machines, enabling them to identify causes that may have previously gone unnoticed.

Predictive Analytics: Gaining Insights

The most important aspect of predictive maintenance and analytics technology is what your CMMS can do with the information once it has been gathered. In fact, the true power of the technology is not in the hardware itself, but in the software where you store the data.

There are several advantages of incorporating predictive analytics into your facility’s maintenance strategy:

  • Provides facility managers with information that can enhance machine reliability, including scheduled maintenance. It also can facilitate a system for improving production by keeping all equipment in peak working condition and minimizing breakdowns, errors and accidents.
  • Reduces overall spending on repairs, which can typically cost more than planned maintenance. Analytics software can help provide a longer lifespan for all assets because planned maintenance fixes problems before they get out of control.
  • Can help reduce on-hand inventory waiting for repairs. This includes both replacement parts and broken down machines waiting for repair.
  • Improves asset retirement processes. It is better to sell a working machine than be stuck with a broken one that needs immediate and expensive replacement. Predictive analytics can identify when an asset nears replacement, giving the team time to sell the used (but still working) machine, lowering overall replacement costs.
  • Allows for continuous data capture on the status of any maintenance work, equipment performance and spending. You can also generate real-time reports reflecting company spending, and produce enhanced forecasts regarding future spending. By integrating your CMMS with HR software like employee time tracking, scheduling, and budgeting tools, you can build on demand dashboards that show a complete picture of human, asset, and budgetary capital.
  • Acts as a central repository, allowing for easier access to documents, files, manuals, equipment logs, permits and other critical information. This approach can also help you create a profile history for each company asset, including records of any machine troubleshooting.
  • By automating your work requests, your maintenance operations become more efficient – versus implementing a system where requests come via email, phone or written documents. This method enables better prioritization of jobs, as well as reduces the risk of a work request getting overlooked.
  • Allows for better management of your spare parts inventory and helps control inventory expenses. Rather than use human perception to determine what you need, create a strategic method that can adequately manage the flow and storage of your inventory. CMMS software can track and update inventory levels and can ease the coordinating with parts suppliers, revealing vital information about how much needs to be on hand at a time, and helping to reduce over-ordering.
  • Lends itself to lower energy consumption thanks to well-maintained equipment that operates more efficiently.
  • Boosts productivity for maintenance staff because they have optimal, more complete information about their jobs. Rather than reacting to changing circumstances which causes a hurry up and wait mentality with employees, technicians can schedule maintenance evenly.

 

Focus On The Right Elements

Predictive analytics software, such as a CMMS, can enhance your facility’s performance and efficiency when employed correctly. The key is to focus on tracking the right elements for a seamless, efficient maintenance approach.

This transforming technology can extend your assets’ lifecycles, increase your team’s productivity, and save your company both time and money. And the best part: users can schedule maintenance tasks and avert emergency breakdowns, proactively repairing equipment before it actually breaks down.

 

Lisa C. Dunn is a writer for TechnologyAdvice and a freelance writer, copywriter and ghostwriter who develops high-quality content for businesses and non-profit organizations. For over 20 years, she has worked with numerous PR and digital marketing agencies, and her work has been featured in well-known publications including Forbes, VentureBeat, Mashable, Huffington Post, Wired, B2C, USA Today, among others.