Key software considerations for a predictive maintenance future
For decades preventive maintenance has ruled as the most effective way of managing maintenance. It has helped extend the lifespan of critical assets for manufacturers, healthcare companies, educational organisations and more.
However, maintenance management software vendors are now pushing the envelope with predictive maintenance capabilities. When maintenance managers have real-time data about asset conditions, repairs can be more efficiently prioritised to reduce labour and inventory costs – keeping machines running at peak performance longer.
For those seeking a maintenance solution, here are some considerations about features, costs and the future of this technology.
How do preventive and predictive maintenance (PdM) differ?
Most maintenance professionals know how to use preventive maintenance functionality in a computerised maintenance management system. However, describing it alongside predictive maintenance helps illustrate the distinction. Knowing how each method works can give buyers an idea of which is best for the company.
The idea behind preventive maintenance is scheduling work based on historical repair information or original equipment manufacturer recommendations. Armed with information about how (and how often) a particular machine failed or was repaired in the past, managers can make scheduling decisions to minimise downtime.
For example, say an AC motor that powers a conveyor in a manufacturing plant consistently failed every two months due to bearing wear. Knowing this, a manager would create a recurring preventive maintenance task (called a PM) to replace the bearings just before that two-month runtime.
Through this method, the AC motor’s failures are reduced significantly, if not outright eliminated, because the data shows trends about how that machine tends to fail. Users can track this information most effectively using a computerised maintenance management system (CMMS). However, even those using manual methods can track repair data and input it into a software system down the road.
Preventive maintenance uses informed estimates about how and when an asset fails. Predictive maintenance goes a step further, allowing CMMS users to harness real-time, actual information about the condition of each machine to decide when repairs are needed.
This typically involves the use of sensors mounted on machines that measure voltage, pressure, heat, vibration and more. This data can be automatically streamed into a CMMS, where it is compared to pre-established thresholds to indicate a failure before it occurs.
Using the same example of an AC motor: a maintenance department mounts a vibration sensor to the motor and connects it to the software. The data streams into the system, and is displayed in a list or graph to show vibration readings over time. The manager has created an upper threshold for vibration in the system. This way, when sensor readings indicate vibration past that threshold, the CMMS will automatically generate a work order for the machine.
Let’s break down the benefits of PdM:
- Access to actual condition data. With preventive maintenance, historical data can guide your PM scheduling, but many factors that maintenance professionals may never detect can affect the performance of an asset. Getting real condition data from a machine itself removes the guesswork and allows for more informed decision-making.
- Reduced labour and inventory costs. As repairs are only scheduled and performed when sensor readings indicate a potential failure, many recurring calendar-based PMs can be eliminated. This reduces labour hours and the cost of spare parts that may be needed for repairs.
- Minimised downtime. Downtime is a profit killer, and should be reduced as much as possible. With appropriate sensor readings for each type of asset, maintenance professionals can spot potential problems before they occur and prevent downtime.
What should I consider as a potential PdM buyer?
There are some considerations to weigh up before jumping into predictive maintenance. Here are a couple of key questions to think about with your maintenance and executive team:
- What do we want to achieve with PdM? You should have a plan in place that conveys what you want to achieve with predictive maintenance. Do you want to reduce costs or better utilise labour hours? Are you more focused on preventing downtime on a few critical assets? By laying out specific goals for the investment, the company and maintenance department can implement the CMMS in a way that facilitates these goals. For example, a department may focus on implementing the work order system first to optimise that process, before adding other features.
- Can we justify the hardware costs? Many modern pieces of equipment include built-in gauges and meters that can be read when taking spot checks; the data is then entered into the CMMS manually. However, many predictive maintenance software users must purchase sensors to mount on machines, or use hand-held multimeters. While these devices and the software itself are becoming cheaper over time, it is still another cost to factor in. Make sure to determine which and how many assets you want to monitor when estimating investment costs.
What can I expect from PdM in the future?
The Internet of Things (IoT) promises a major boost to connectivity between assets and software so that maintenance personnel can keep an eye on every machine from a central location.
Some companies are already taking advantage of this type of technology with smart buildings, but IoT applications may take some time to be feasible for most companies, as they require highly connected buildings and systems.
Another expected area of improvement is in analytics. Maintenance software offers reporting functionality, which can help users identify trends using historical data and information about vendor and inventory costs. Analytics goes beyond reporting to offer meaningful insights and recommended actions based on current data.
For example, analytical functions, in theory, could factor in a company’s overall costs for inventory management and suggest actions, such as a reduction in stock-on-hand to reduce carrying costs or a change in optimal reorder quantities. This level of analysis exists today and many CMMS and computer aided facility management (CAFM) vendors are working to implement it into their offerings.
In conclusion, predictive maintenance is not likely to completely replace traditional preventive maintenance. However, it can help to minimise downtime and cut costs if used to supplement it. Asset-intensive organisations, such as those in the manufacturing, fleet, facilities management, healthcare or education industries, can reap the most benefits from predictive maintenance.
The author, Taylor Short, joined Software Advice as a CMMS market research associate in 2013. This article also appears in the April/May issue of Facility Management.