Predictive maintenance & condition monitoring


Achieving peak condition with smart technologies


Even though data-optimised smart machines are appearing increasingly on the factory floor, many companies are still struggling to integrate these new technologies with their legacy systems. A good place to start, writes SKF’s Phil Burge, Marketing and Communications manager, is to enable the collection of data from ‘dumb’ machines, so that their condition can be monitored


W


e are living through the fourth industrial revolution. Through this revolution, machinery is


being outfitted with smart sensors that collect extensive data on performance, and artificial intelligence is increasing production efficiency and enabling seamless quality assurance. Blockchain transactions are improving the transparency and security of any number of transactions, while the impending implementation of 5G mobile internet will allow for ever-larger volumes of data to be processed and sent from anywhere with a connection. Advances in connectivity, big data and the


expansion of the Internet of Things (IoT) are enabling the implementation of such intelligent manufacturing technology, which is creating a sea change in how companies are organised and run. In the past, responsibility for the


management of industrial technology in manufacturing has been divided between the IT and operational technology (OT) departments. Where IT provided top-down support for company management and back


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office operations, OT was built from the ground up to monitor and control machinery, equipment, tools and assets. In this legacy role, OT exists in something of a bubble, where machines, controlled by human inputs, are programmed to perform highly specific tasks. However, the new breed of intelligent manufacturing technology is impacting both IT and OT. Data is no longer the exclusive realm of


the IT department; from supply chain management to the operations floor, data is now ubiquitous across the organisation. As a result, IT and OT can no longer operate independently and are therefore converging. This convergence creates opportunities that have not existed before. Through the integration of IT and OT


data, business leaders can get access to live dashboards that provide up-to-date information on all parts of the organisation. Connected systems can communicate to detect unbalanced workflows and automatically make corrections to prevent outages. Intelligent machines can identify faulty parts and select new assets to restore


production. Furthermore, through the integration of controls, production management and supply chain management systems that are integrated with other IT assets can intelligently route orders and automate work streams. This is all well and good, but it begs a


question; where does one begin in implementing this technology? After all, significant capital investments will have already been made on the production floor. To tear this machinery out and replace it wholesale would be prohibitively expensive. Thankfully, the migration to intelligent


manufacturing does not necessarily mean starting with a blank slate, but rather effectively integrating new technology into the existing manufacturing environment. Further, as new technology transforms manufacturing into a highly connected, intelligent and ultimately more productive industry, businesses must also find a way to enhance their legacy systems to keep up with emerging, increasingly sophisticated technologies. Integrating “dumb” machines with “smart” technology starts with enabling data


October 2019 Instrumentation Monthly


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