A GROWING global population coupled with rapidly advancing technologies are propelling an ever-increasing demand for essentially anything that consumers require, from infrastructure to food, which is placing mounting pressure on mines and manufacturing plants to produce more, faster and more economically.
“In order to achieve maximum production and overall plant optimisation, operators are demanding more from their heavy industrial machines and equipment, which are expected to run ultra-reliably and perform better and more efficiently for longer, while paying close attention to safety and environmental compliance,” says John Storm, SKF Connected technologies manager. “Given that machines and equipment typically operate in stringent environments, condition monitoring and regular maintenance go hand in glove in achieving the trio of high performance, availability and reliability. Manual monitoring by technicians using portable devices is time-consuming and counter-productive, sapping resources and compromising worker safety.”
By switching from a manual to an automated machine monitoring system and data collection process, Storm says that operators will increase the availability of their rotating equipment and subsequently optimise their operations.
SKF Enlight Collect IMx-1 vibration and temperature sensors automatically monitor the condition of rotating parts, enabling operators to collect critical data on the health of their machines and equipment more often from previously inaccessible locations, requiring fewer technicians and creating a safer environment. More frequent data collection, i.e. hourly or daily instead of weekly or even monthly, leads to early problem detection and machine failure prediction. Operators are subsequently able to proactively carry out preventative maintenance, reducing costly unplanned downtime and maintenance costs, increasing machine life cycles and optimising asset reliability.
The fully automated process sends large volumes of collected data to a host computer network for uploading to the SKF Cloud that is connected to SKF Rotating Equipment Performance Centres where the data is analysed by SKF application specialists. Automated data interpretation and expert fault verification systems allow operators to interpret large volumes of machine data, gaining invaluable insights into the performance of their rotating equipment.
The IMx-1 system relies on a ‘mesh network’ which allows sensors to relay data between each other, enabling data to be routed around radio obstacles such as pipework. As the ‘mesh network’ is self-forming, the system is quicker and easier to deploy compared to other wireless systems such as Wi-Fi or Bluetooth. In addition, the innovative way in which the system handles bandwidth and the sensors’ power consumption, leads to a long battery life.
The compact, battery-powered, easy-to-install SKF Enlight Collect IMx-1 enables operators to build an automated machine monitoring system powered by Cloud-based IoT solutions and AI-driven analytics. Mounted to a bearing housing, the IMx-1 sensor forms a scalable network, wirelessly detecting and processing a raft of common/critical health data from the rotating assets including unbalance, misalignment, high temperatures, looseness, electrically-induced vibration and early stage damage to bearings and gears.
The tough ingress protection rating of IP69K ensures that the robust SKF Enlight Collect IMx-1 will deliver reliable operation in highly taxing conditions typically found in industrial environments including high exposure to dust, dirt, oil, grease, contaminants, flying debris, temperature changes, wind, rain, high-pressure hot water wash-downs and more.
With increased visibility across their entire asset network, operators will achieve their goals of high machine availability, increased productivity, improved safety and a reduced environmental impact for a sustainable, efficient and profitable plant.
SKF Enlight Collect IMx-1 is available on a fee-based contract to assist operators to seamlessly transform from a manual to a fully automated system.
