Industry 4.0 and the future of Predictive Maintenance

In its anniversary issue of 9/13/17, EXAME magazine carries a story titled “Disruption is changing the world as we know it.”

It features an interview with Jeffrey Immelt, Chairman of the Board of Directors of General Electric, where he tells how GE went on to invest in a radical change in both structure and strategy.

It talks about the goal of ceasing to be a company that only produces industrial equipment and becoming able to provide data to customers by means of sensors connected to their machines.

By 2020, revenues from GE’s digital business are expected to triple as more equipment is connected to the Internet.

IDENTIFY AVANT-GARDE MOVEMENTS

Among the concepts of Industry 4.0 or the era of its digitalization are the use of sensors to monitor almost everything, logistics by drones, digital content delivery where the menu is chosen by the consumer, the use of 100% renewable energy, autonomous vehicles, blockchain, big data and data analytics, artificial intelligence, and robots performing new tasks, etc.

This is the backdrop of many profound, and in many cases disruptive, changes that humanity is facing and that will not leave the industry unscathed.

The movement for change is accelerating and makes room for simplification, aimed at increasing productivity, and, brings greater tolerance for startup-style experimentation.

The technologies for change are more accessible and at lower cost.

Just take a look at some of the technology centers in the country and observe the national capacity to produce new solutions for existing problems, with a lot of creativity.

IIOT – INDUSTRIAL INTERNET OF THINGS

Industrial Internet of Things (IIoT) is part of the broad concept of the Internet of Things (IoT). The IoT is the network of intelligent computers, devices, and physical objects that collect, store, and share large volumes of data. 

Virtual cloud servers are used to store this data, combine it with other data, which is then worked on and shared in useful formats with users.

The IoT will increase automation in various sectors of daily life, including industries. The application of IoT to manufacturing is called IIoT.

IIoT adoption is growing rapidly. Industries that have adopted it have experienced significant improvements in security, efficiency, and profitability, and this trend will continue as IIoT technologies are adopted on a larger scale.

INNOVATION AS A PRODUCTIVITY DRIVER

Industry 4.0, also known as the Fourth Industrial Revolution, makes use of the innovative concepts of the internet of things (IoT), cloud computing, and data collected by devices such as sensors, to more efficiently do what has to be done.

It is no different for reliability-based industrial maintenance. The same Industry 4.0 technologies are applicable to predictive maintenance. They allow one part of the work – data collection – to be done in an automated and continuous way.

Improving the safety and reducing the risk exposure of employees in charge of inspections and information collection.

Made by autonomous sensors, with communication via Bluetooth or RFID and minimal human interference, the collection of data regarding the situation of the monitored machinery gains speed, accuracy, and frequency of registration with the combination of hardware and software solutions accessed via the internet.

DO MORE WITH LESS ON THE SHOP FLOOR

The use of sensors that monitor the condition of machinery requires careful analysis of what specifically should be monitored and why.

It will not be the use of an exaggerated number of sensors at points on the machinery that will solve the issue. It will be good considerations when choosing the asset to be monitored:

– Identify the machinery and its points that should benefit from continuous monitoring, following criteria of criticality, cost, and maintenance complexity of that asset;

– Define parameters and their threshold data so that the data collected can easily identify where and when a potential problem may be developing;

– Define what to do with the information collected, who will analyze this data, in which situations it should generate an action plan, and what will that action plan be.

It is useless to monitor machinery that by deliberate choice falls under corrective maintenance.

However, machines that have a high availability requirement, are subject to preventive maintenance, have expensive spare parts, or produce large volumes are the best candidates for condition monitoring.

The aim is to increase the availability of this machinery.

Know it like no other, through careful analysis of the monitored data, to the point of being able to predict subsequent behavior.

Sharing the knowledge obtained and continually adjusting best practices is what will raise the standard of industrial maintenance.

This process will be able to reduce costs and improve the quality of the final product.

Meet our IoT solution for industrial maintenance!