Predictive maintenance: fashion trend or real added value?

Predictive maintenance: definition and examples

In 2019, every business leader already questioned the future of these trends, which are Big Data, the Internet of Things (IoT), the predictive maintenance and its younger sister, normative analysis. How do these advancements shape our organizations? Should we wait for others to replace them or should we invest now and get all the benefits possible?

Even if the concept of Big Data still seems vague to you, chances are that you are already familiar with predictive maintenance and that you have observed its impact on your traditional preventive maintenance activities. Likewise, it is difficult to miss these new ranges of affordable sensors, and the possibility of connecting them to your ERP and your equipment. And that's it! You are at the heart of big data. But is it still worth the effort? How can you overcome the fears of your maintenance teams in the face of these changes?

The good news is that there are now more and more affordable solutions that will support you in your transition to Industry 4.0 and help you successfully deploy a predictive maintenance strategy. La Next generation CMMS (computer-aided maintenance management) is one of them. No worries: as soon as your maintenance teams become aware of the proven benefits of digitalization, predictive maintenance will become an essential element of your production strategy.

Big Data, the new El Dorado of industrial maintenance?

The term “Big Data” can cover many realities, from Industry 4.0 to machine learning. For the industrial sector, Big Data primarily refers to the mass data available thanks to ERPs, operations control and systems for monitoring the condition of equipment. In the strict sense of the term, maintenance professionals often associate big data with the use of predictive analytics and rarely with the mass data that the company collects and analyzes.

Sensors have long been used to track equipment. However, in the past, they were linked via proprietary communication protocols. Only a limited number of people were then allowed to consult the data, which could only be analyzed in a limited environment. Today, the Internet of Things allows the networking of these tools using standard Internet protocols (IP) as well as greater accessibility and use of this data. In order to get the most out of these tools, business leaders will need to have certain technological skills.

In this respect, smart CMMS can be of great help. Choosing the right software can avoid a lot of complications, simply by allowing you to automate your entire process. A new generation CMMS allows you to collect, store and analyze all the data extracted when monitoring the condition of your equipment, and to be alerted in the event of an anomaly. Thanks to a CMMS such as Mobility Work, you can even choose the level of confidentiality of your data among the following three:

• Private and only accessible to your factory employees
• Private and accessible to several sites of the same company
• Public and accessible to the entire Mobility Work community

Mobility Work CMMS has a powerful Big Data tool to help you make the best decisions every day.

Predictive maintenance and big data

Industry is one of the sectors that has benefited the most from the benefits of the Internet of Things (IoT). Thanks to the sensors present on the production line, maintenance professionals collect data directly at the foot of the equipment and analyze them using predictive algorithms in order to detect possible warning signs of a failure. Thus, they are in a position to maximize the efficiency of their maintenance operations, improve the availability of their equipment and optimize maintenance costs.

A CMMS software allows you to store your data, to share it with other systems in the organization (ERP, automated systems, cost centers) but also to analyze and compare it to the data in these systems. In short, such solutions represent a real asset in terms of maintenance management, intervention planning, purchasing and spare parts management.

Predictive maintenance is ultimately just the natural evolution of industrial maintenance, in that it offers a global overview of the condition of equipment based on a complex set of data from various sources. While they represent a significant initial investment, predictive maintenance programs pay off in the long term. Maintenance interventions are carried out according to the real condition of the equipment, when it shows concrete signs of deterioration.

Thanks to Mobility Work's next-generation CMMS, easily collect, process and analyze your data, and thus gain a better understanding of the anomalies in your production system.

The key to the success of predictive maintenance

In isolation, a quality CMMS inspired by Industry 4.0 may not be enough to guarantee the success of your predictive maintenance program, but it is nonetheless a key factor in the success of your predictive maintenance routines.

Mobility Work is an intuitive mobile application, available on iOS and Android

As with most IT solutions, the user experience plays a decisive role here. A few clicks are enough to access your data in Mobility Work CMMS and generate performance graphs using our integrated dynamic analysis tool. Thanks to its mobile application, Mobility Work CMMS is always at your fingertips, allowing you to follow trends, identify possible problems and report them to your team. Collect and list all your data easily and in real time at the foot of your equipment using tools such as pressure meters, oil level meters, etc. Our teams support you on all your data integrity and processing issues.

If you still have doubts about deploying a predictive maintenance routine or if the cost seems too high, you can test some key equipment. For assets whose shutdown would cause significant losses of function or a safety risk, the benefits of predictive maintenance will only be more obvious.

Predictive maintenance is a program inspired by the Internet of Things (IoT) allowing you to monitor the performance level of your industrial and manufacturing processes, but also to repair or replace faulty components before they break down. The development of predictive analytics solutions is still in its early stages. At the moment, most organizations are working to control the collection and storage of their data.

The latest solutions on the CMMS market, such as Mobility Work, the first community dedicated to maintenance management, help business leaders reconcile different maintenance performance or product quality strategies. In the future, an increasing number of businesses will turn to predictive maintenance and invest more in developing predictive models to predict downtime more accurately.

Are you interested in maintenance management and want to know more in order to increase your productivity and save money?