A closer look at the road to Maintenance 4.0

A closer look at the road to Maintenance 4.0

When it comes to Industry 4.0 and Predictive Maintenance, every industrial organization is different. Helping them to see the next steps towards improved uptime, satisfied customers and cost reductions, gives them a sense of where to go and the efforts it will take. What sets our approach apart?

News Industry 4.0 26 August 2020

Central in I-Care’s delivery model is its roadmap for Industry 4.0. Starting with an assessment of the current situation, to identifying opportunities, generate and collect data, analyze and visualize these data and acting on it, it offers customers a complete roadmap to Industry 4.0, wherever they currently are in their journey. In the world of Industry 4.0, factories include augmented machines with wireless connectivity and sensors, connected to a system that can visualize the entire production line, control and make decisions on its own. In essence, it describes the trend towards automation and data exchange.

Predictive Maintenance is an essential part of many industrial companies’ Industry 4.0 strategies. As a method of preventing asset failure by analyzing production and maintenance data, they can identify patterns and predict issues before they occur. However, not every organization has the same maturity level in Predictive Maintenance. Some might still be at the first level, of visual inspections. Others might have already moved on to the second level of using instruments for recurrent examinations. Or they might even have realtime monitoring systems in place (level 3).

Assessing is about more than assets

To reach the Industry 4.0 level of Predictive Maintenance, a company needs to have at least level 3 in place. Level 4 of Predictive Maintenance goes further than the previous levels because it is not just about monitoring live data, but also about online data. The difference is that ‘live’ means realtime data streams, while ‘online’ means you can use both realtime data, IoT sensors and historical data. With an automated and smart solution, you are able to predict previously unpredictable failures.

Our roadmap helps our customers to get a sense of where to go and the efforts this will take. For example, if they aim for Industry 4.0 level of Predictive Maintenance, they will need to have already sensors installed on-site. We also need to know what data they already use and to what ends. This also brings us back to our first step of assessing the current situation. This is not just about assets. For example, is the culture in your facility and industry ready for these next steps? Do you have the budget? Do you have the right competencies and infrastructure in place? And do you have the support of the management?

Move from reactive to predictive

When assessing, we might see that a customer is not ready yet. For example, they might still be in the reactive/corrective mode for maintenance, saying that a line or machine will run until it fails or something breaks. Or they might have a preventive strategy, changing parts of machines periodically to prevent failures. In these cases, we are not going to propose the 4.0 roadmap, but instead, put the customer on the path of digitalization to convert their reactive strategy into a predictive approach. After that, the roadmap to 4.0 appears. So, if you are ready for 4.0 we can move forward. But if not, we can still take another starting point and at least start moving.

The end goals are the same for almost every client: improved uptime, satisfied customers because you can deliver on time, and cost reduction as a result of avoided failures and secondary effects of these failures on other parts of production lines. We think that with an Industry 4.0 approach, we can use data to detect any failure that could occur before a machine goes into failure mode. We also believe that the best way to do this is to concentrate on data and to automate data analytics.

Industry 4.0 since ’04

A focus on customer maturity shows why some companies are successful with Industry 4.0, while others need our help. Big industrial companies might often have teams in place that want to do something with process data such as temperature readings, pressure readings or tank levels. For ourselves, we are more focused on what we call Maintenance 4.0, measuring specific data such as vibrations. We have done this since 2004 and therefore we can add historical data to our live data flows and to our prediction models. Most of the times, even big companies don’t have the teams and competences in place to deal with these data and reach Maintenance 4.0.

This is one of the things that sets us apart in the Industry 4.0 world. For the complete roadmap, you need to have different competencies. It is about much more than knowing assets, industries, programming, databases and how to connect them. We see plenty of companies experimenting with data and AI. But before going to ’AI mode’, you need to generate and collect data. We have done Industry 4.0 since ’04 and add industry knowledge, historical data and competences in leveraging data to the mix. This is why we believe firmly in our Industry/Maintenance 4.0 approach: being able to position our customers on the roadmap, we are helping them to imagine the road to success.





Olivier Dengis, Industry 4.0 Officer and SME at I-Care