Unplanned downtime has a major impact on the budget of every company causing colossal losses every year. The only way to prevent it is to establish a more efficient equipment maintenance strategy. Industry 4.0 offers a greater opportunity to maximize equipment utilization, operational cost and teams’ productivity through machine data. Predictive maintenance deploys condition-monitoring practices and advanced analytics to predict machine failures.
Predictive Maintenance Essentials
In general, predictive maintenance helps maintenance professionals to predict future outcomes using past data. More high-quality data is fed into the model, the better its accuracy. Predictive maintenance has 2 main objectives:
To predict when equipment failure might occur through a reliable condition-based maintenance technique as vibration analysis, oil analysis, thermal imaging and equipment observation.
To prevent the occurrence of the failure by performing quality maintenance interventions only when required.
The shift from conventional maintenance techniques as reactive and preventive maintenance programs and even sometimes Excel-based data management to the establishment of predictive maintenance strategy is a huge leap. And even though many business owners are convinced that this would bring them a considerable competitive advantage, the adoption of a predictive maintenance strategy remains challenging. Asking the right questions and understanding the essentials of the program is a crucial step.
Question 1: How Does Predictive Maintenance Differ From Other Maintenance Programs?
Should you give up on your current maintenance techniques and if yes, why? Can predictive maintenance co-exists with your established maintenance program or should you totally restructure your strategy? The answers of these and many other questions are summarized in the following 3 most important considerations that you should make before opting for a predictive maintenance program.
Predictive Maintenance vs. Reactive Maintenance
The benefits of reactive maintenance are dubious. On the one hand, if you are dealing with new equipment, you can expect a minimum of failure incidents and if your maintenance program is purely responsive, you won’t spend any money on additional resources until something happens. Since there aren’t any associated maintenance costs, you could consider this period as an economy.
On the other hand, while waiting for the equipment to break down, you are basically shortening the life of the equipment, which finally results in more frequent replacements and interventions. Furthermore, in cases like these, the labor costs associated with the repairs will likely be higher than normal, as the failure will most likely require more extensive repairs than it would have been necessary if the piece of equipment had not completely failed. And last but not least, if you have planned to operate the equipment to failure, you will need a large inventory of spare parts. This and all other mentioned costs could be easily minimized with the predictive maintenance approach.
Preventive Maintenance vs. Predictive Maintenance
Compared to predictive maintenance, preventive maintenance is based on timely scheduled periods, defined by manufacturers’ instructions or asset’s specific behavior. The preventive interventions are performed, no matter if the machines show any deteriorations signs or not. Predictive maintenance on the contrary is based on the actual state of the machine. It follows the data of the mounted on the equipment sensors and as soon as any sensor shows a deviation from the norm (for example: different vibration reading), an intervention is performed.
For example, following the preventive maintenance requirements, lubricant change is a timely based routine without any concern given to the current status and performance capability of the oil. In predictive maintenance, the lubricant would be analyzed periodically to determine its actual condition and changed as soon as it starts performing differently.
Predictive Maintenance vs. Reliability-Based Maintenance
According to reliability-based maintenance, or RCM, not all equipment has the same importance and some assets will have a higher probability of experiencing failures. Therefore certain assets but as well financial and human resources should be prioritized and optimized. In general, the RCM approach is evaluating all equipment and resources in order to obtain the highest possible reliability and profitability levels.
In this context, RCM is not a substitute for predictive maintenance. Both collaborate and rely on each other to enable a plant to better tailor resources to needs while improving reliability and reducing costs.
Question 2: Is Predictive Maintenance Expensive?
This is a difficult question to answer depending a lot on the objectives and size of a factory. If you have a small or a middle-sized business, the installation of predictive maintenance routines might not be cheap since you will need to acquire additional equipment, to train your current staff and hire new professionals.
But if your budget allows it and you are ready to invest in innovative approaches in order to gain competitive advantage, then the obtained benefits of a predictive maintenance adoption will far outweigh the costs.
By the end of the day, a successful predictive maintenance program will significantly reduce energy costs, maintenance costs and downtimes and increase the reliability of the installation.
Question 3: How Can I be Sure That I Run a Successful Predictive Maintenance Program?
Turning the idea of predictive maintenance into an actual deployment can be complex, however there are several steps to follow in order to ensure that you are going into the right direction.
Having a reliable, next-gen CMMS is of crucial importance. Solutions as Mobility Work, the next-gen maintenance management platform, can easily collaborate with your sensors and support you collecting, storing and analyzing your data.
Read more on Predictive Maintenance and CMMS:
Other important recommendations include carefully determining the objectives of your business, checking your database, exploring your data for insights and developing, testing and deploying machine-learning models.
If properly deployed, predictive maintenance offers numerous benefits. First of all, it can completely eliminate catastrophic equipment failures and minimize inventory and order parts as needed to meet downstream maintenance requirements. Assets are shut down right before imminent failure, which reduces the total time, and cost spent maintaining equipment.
But how well equipped and ready a business is for predictive maintenance adoption, depends on many factors. Compared to preventive maintenance, the initial investment needed for condition monitoring equipment and skilled professionals is often high.
Mobility Work is a SaaS computerized maintenance management system, easing predictive maintenance adoption and helping business owners to get the best out of it.