NOV-DEC 2018

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AUTOMATION IT INTECH NOVEMBER/DECEMBER 2018 33 N ew real-time, equipment health monitor- ing and prediction (HMP) systems are the first of many exciting AI-based applica- tions that combine embedded human knowl- edge and advanced engineering automation. They help factories to better detect, analyze, pre- dict, and prescribe solutions to complex, every- day manufacturing problems in real time. In today's connected world, manufacturers who do not take advantage of the Industrial Internet of Things (IIoT) will soon find themselves left be- hind. IoT is fueling a wave of new artificial intel- ligence–based, adaptive intelligence applications for smart manufacturing. They offer the potential for massive reductions in manufacturing costs and eliminating machine downtime. How? Manufac- turers are sitting on a wealth of data. Until recently, providing engineers and other stakeholders with access to this data at the right place and at the right time was not possible. Now, however, in the age of IIoT, the cloud, and big data, smart manufactur- ing is making this goal achievable, so employees in engineering, supply chain, and management can make more informed decisions in real time. To meet the demands of the fast-growing smart man- ufacturing sector, equipment HMP technology has AI-based applications that combine embedded human knowledge and advanced engineering au- tomation to help factories solve problems. The equipment health monitoring and predic- tive technology saves manufacturers time and expense by reducing two of the leading losses for the manufacturing industry: equipment failure and downtime. Where there's a sensor there's a way AI-based equipment HMP creates a way to not only take the risk out of manufacturing, but also to reduce risk for all industrial manufacturers, in- cluding those in the electronics, energy, automo- tive, steel, and pharmaceutical sectors. Through the use of sensors for each step of the production process, equipment and outputs are monitored in real time by an adaptive intelligence (AI) that provides a fault detection system, early warning alarms to prevent failure, and remaining useful life (RUL) calculations for all manufacturing equip- ment. Downtime is drastically cut, because main- tenance is only performed as needed and where needed. In addition, of course, the equipment HMP system is highly adaptable to a wide range of industries, enabling smarter manufacturing from the steel and automotive sectors to semiconduc- tors and energy. Manufacturers across all sectors are catching on to this trend. According to a 2017 Gartner Group study, the number of IoT devices installed across the world was 8.4 billion. By 2020, that number will more than double to 20.4 billion IoT devices deployed in the market. AI-based equipment HMP learns the user's unique configurations and processes to identify anomalies. In steel manufacturing, for example, users are seeing an average lead time reduction of 95 percent and cost reductions of 3 percent. In one study, a top-five global steel maker using a real-time HMP system in a cold-rolling steel mill minimized surface quality issues, such as dents, scratches, and impurities, and solved the root causes of coil contraction. This was accom- plished by feeding process data from a plethora of sensors throughout the manufacturing pro- cess to an adaptive intelligence. In addition to the process improvements enabled by HMP, ac- curate predictions of equipment failures avoided costly breakdowns and service disruptions. Predictability in assembly manufacturing Equipment HMP has been helpful with overhead hoist transports, ubiquitous in manufacturing spaces of all types. Users often have hundreds of overhead hoist transports on each assembly line, where they are prone to belt cutting, motor speed reductions, and other errors that lead to failure. More importantly, downtime can cause losses of millions of dollars. Monitoring vibration data al lows the HMP system to send an alarm one full hour before failure, preventing accidents and saving money. Additionally, equipment HMP en- ables the user to easily set gold standard hoists for the entire factory floor. That ensures all trans- ports are operating to that standard after any maintenance, and that the user is notified of any deviation from that standard. The RUL of each individual overhead hoist transport can be moni- tored to maximize maintenance efficiency. Auto industry and equipment HMP In addition to the benefits with overhead hoist transports, the HMP technology has enabled auto industry users to dynamically detect faults in real time. In studies with two top auto makers, sensor data was fed directly into the HMP system, where it was collected, analyzed, and compared to both FAST FORWARD l AI-based equipment health monitoring and prediction systems save time and expense by eliminating equipment failure and downtime. l With IIoT, the cloud, and big data ana lytics, AI-based HMP systems help factories to better detect, analyze, and predict solutions to everyday manufacturing problems. l By using sensors at each step of the production process, adaptive intel- ligence monitors equipment and outputs in real time.

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