Predictive Maintenance

As a business owner in 2019 you have definitely asked yourself where are all these trends as Big Data, the Internet of Things (IoT), predictive and even now prescriptive analytics are taking us. How are these developments impacting organizations? Should you just wait until they pass and the next buzz invention emerge or should you take them seriously and reap off the possible benefits?

And if Big Data still appears to you as something vague, you have most probably already encountered predictive maintenance and maybe started experiencing its impact on traditional preventive maintenance activities. It is almost impossible to ignore the current possibility of purchasing sensors at favourable prices and connecting them to your ERP and machines. And there you are! In the middle of Big Data! But is it worth continuing the investment? And how to convince your so resistant to change maintenance employees?

The good news is that currently there are more and more cost efficient solutions that can guide you through the jungle of industry 4.0 and help you get used to and adopt successfully predictive maintenance. Next-gen CMMS (computerized maintenance management system) solutions are one of them. And don’t worry, as soon as your maintenance team starts seeing and benefiting from the proven benefits of digitalization, predictive maintenance will become indispensable for your production.

What Is Big Data and Why Should You Know It?

Big Data can be a quite vast expression for everything from industry 4.0 to machine learning. For industrial organizations, Big Data is rather describing the large amounts of data that are available from ERPs, process control and condition-monitoring system. In the narrow sense, Big Data is associated among maintenance professionals with the use of predictive analytics and rarely refers to big datasets that have been stored and analyzed.

Condition-monitoring programs through sensors is nothing new. The only difference is that in the past these sensors have been connected via proprietary communication protocols. The information was available only to a limited number of people and analyzed in a limited context. Nowadays the Internet of Things (for good or for bad) gathers all these devices using standard Internet communication protocols, which makes the data used for many other things and seen by many other users. All this advancement requires of business owners a certain level of technology knowledge.

Smart CMMS software can be a great help in cases like these. Choosing the right solution can save you a lot of headaches, by simply making the whole process running by itself. A next-gen CMMS can collect, store and analyze all data available from the condition monitoring equipment and send notifications. With a solution as Mobility Work you can even decide if you want to make your data public or not. You can easily choose between the 3 following privacy levels:

  • private and only accessible within your plant
  • private and only accessible within your multisite company
  • public and accessible from the entire Mobility Work community

Mobility Work CMMS provides a powerful Big Data tool to help you daily in your decision-making process

Mobility Work CMMS provides a powerful Big Data tool to help you daily in your decision-making process

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Predictive Maintenance as a Part of Big Data

Manufacturing is one of the sectors that has benefited the most from IoT. By mounting sensors on machines, professionals collect data, which can be analyzed through predictive algorithms and discover signs of potential failures before they occur. By doing so, they are able to increase maintenance efficiency, improve availability and optimize maintenance costs.

A CMMS can store the data, share it between various internal systems (ERPs, automation systems, cost centers) but also analyze it in the context of all the data coming from these systems. This brings major benefits for maintenance management, planning, operations, purchasing and spare parts management.

Predictive takes simply maintenance one step further by providing a complete picture on assets’ health, based on a complex set of data drawn from a variety of sources. Even though expensive at the beginning, predictive maintenance programs are turning into a cost efficient solution in the long term. Maintenance interventions are performed only when the equipment itself is showing some deterioration signs, based on an assessment of equipment condition.

The next-gen CMMS Mobility Work can help you leverage data collection, processing and analysis and in the same time provide you with a better understanding of production system’s abnormal behavior.

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How Can You Make Predictive Maintenance Work?

A quality and industry 4.0 induced CMMS might not be all you need to ensure the success of your predictive maintenance program but without this component it is 100% sure that your predictive maintenance routine won’t work.

Mobility Work CMMS provides a user-friendly mobile app, available on iOS and Android.

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As with most of the IT products, UX remains of crucial importance. Mobility Work requires just a few clicks to connect to your data and generate powerful dashboards through a powerful integrated analytics tool. Mobility Work CMMS mobile application can be easily accessed anytime and anywhere, from any device), and enables you to monitor trends, identify potential problems and notify your team. You can easily collect and index any machine data in real-time thanks to the counters value as pressure, oil level, etc. Our team is happy to support you on data integrity and data handling security issues.

If you are still in doubt about the deployment of predictive maintenance and/or your budget is not enough, you can try to apply it only on prioritized critical equipment. These are asset whose failure will cause severe function loss and safety risk.

Predictive maintenance is a program based on the Internet of things (IoT) to monitor the performance of industrial, mostly manufacturing processes, and to repair or replace deteriorating components before they fail. Today, the creation of predictive analytics is still in its infancy. For now, most of the organizations are trying to master the collection and storing of data. Sophisticated CMMS such as Mobility Work, the first maintenance management platform, are already available at the market to support business owners in establishing correlations between different ways of maintenance performance and product quality. In the future is expected that more and more businesses will appreciate the benefits of predictive maintenance and start investing more in the creation of sophisticated predictive models that more accurately predict failure.