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FEATURE INDUSTRY 4.0 PREDICTING GREAT THINGS – A NEW ERA IN MAINTENANCE


dipped their toes in the water, employing data scientists to monitor a handful of the most critical production assets. But it remains the case that this kind of sophisticated machine analysis, and the proactive approach to maintenance it enables, is no more than an aspiration for the most manufacturers around the world. Until recently, gathering the data


The advent of Industry 4.0, combined with advanced analytics and machine learning tools, will deliver effective predictive maintenance in manufacturing. Dr Simon Kampa, CEO of Senseye, explains...


T


he rapid adoption of technologies designed to drive ever higher levels of


efficiency and productivity has given rise to a new kind of manufacturing environment. Indeed, the move to ‘smart factories’ has reached a point where many modern industrialists and industry observers speak openly of a fourth industrial revolution. What makes a factory truly smart,


however, goes well beyond traditional notions of lean manufacturing designed to minimise wasteful production processes. The smart factory is an intelligent organism where big data, analytics, automation and cloud technologies work together to make production smarter, more efficient, agile and responsive. The advent of Industry 4.0, where production assets are connected to the Industrial Internet of Things (IIoT) and able to communicate with the world around them, combined with advanced analytics and sophisticated machine learning tools creates huge opportunities to advance manufacturing. In a smart factory, customer feedback can be considered and incorporated into products more quickly. Production faults are addressed immediately. The earliest signs of machine failure are spotted automatically and addressed several months before they can affect production. Senseye has seized on the opportunities presented by Industry 4.0 technologies and the smart factory movement to make a big difference in how manufacturers and other industrial organisations approach


14 MARCH 2019 | PROCESS & CONTROL


condition monitoring and predictive maintenance. We provide cloud-based software for predictive maintenance that uses advanced machine learning algorithms to analyse data from machine sensors and cloud platforms such as Siemens MindSphere to diagnose problems, predict failures and assess the remaining useful life of machinery. These algorithms can be used on any


machine from any manufacturer, and help reduce unplanned downtime and increase overall equipment effectiveness.


ACHIEVING ASPIRATIONS Condition monitoring and predictive maintenance are not new. Manufacturers in heavily regulated sectors such as defence and aerospace have practised these concepts for decades. However, the cost and complexity of gathering and analysing sufficient data to drive tangible results have largely limited the use of these proven tools to those sectors. Some manufacturers in other industries have


The growing use of smart sensors and machines that can record their own vital statistics and relay them for analysis over the internet, means that this valuable data can be extracted from thousands of machines at a low cost


required to inform conditioning monitoring activities was a laborious manual process requiring specialist expertise. The growing use of smart sensors and machines that can record their own vital statistics and relay them for analysis over the internet, means that this valuable data can be extracted from thousands of machines at a low cost. Algorithms located in the cloud can then crunch through all of this data, comparing critical readings around things such as machine vibration, pressure, temperature, torque and the amount of electrical current being drawn, against an extensive self-learning database of known faults. Manufacturers can now spot emerging problems automatically and identify if and when a particular component or machine will fail in the future. Using predictive maintenance in smart factory environments delivers significant returns. Senseye customers are typically able to cut their maintenance costs by around 40% using our automated analysis tools, however, their benefits go way beyond these efficiency gains. Unplanned downtime can be a huge


The smart factory is an intelligent organism where big data, analytics, automation and cloud technologies work together to make production smarter, more efficient, agile and responsive


drain for manufacturing environments. For large-scale manufacturers, every minute in which critical machinery is out of order can cost the factory tens of thousands of pounds. Being able to predict if and when a machine will fail, therefore, allows engineers to make repairs well before a predicted failure might affect production. Although we are still in the early days of


Industry 4.0, it is clear that the opportunities on offer from this new era of responsive, interconnected machinery are enormous. We are seeing higher levels of communication, transparency and yield, and many of our customers - which include organisations in automotive, FMCG/CPG and, heavy industry - have halved their levels of machine downtime by using Senseye. While the longer-term potential of Industry 4.0 has yet to be seen, the benefits of smarter factories are already being felt. It is clear that its future impact will be truly transformative.


Senseye www.senseye.io


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