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JAN-FEB 2018

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INTECH JANUARY/FEBRUARY 2018 19 FACTORY AUTOMATION T he MTConnect standard enables manu- facturing equipment to provide data for predictive analytics—which is a hot topic for good reason. The vision of anticipating break - downs before they happen is decades old, but the computing power, available data, and level of statistics and forecasting expertise in industry today puts this vision closer to reality than ever before. Production line shutdowns are excep - tionally costly, and manufacturing executives are understandably enthusiastic about moving from a preventative to a predictive paradigm. In the Industrial Analytics 2016/2017 survey and report from the Digital Analytics Association Germany and IoT Analytics, machine predictive/ prescriptive maintenance was the top industrial data analytics application. Similarly, in the 2016 Global Manufacturing Competitiveness Index by Deloitte and the U.S. Council on Competitive- ness, top manufacturing executives ranked pre- dictive analytics as the most important future advanced manufacturing technology. With the MTConnect standard, manufactur- ing equipment provides data in structured XML, rather than in proprietary formats. Uniform data opens up a world of new applications for indus - try. MTConnect data sources include production equipment, sensor packages, and other hardware. Applications using MTConnect data have more efficient operations, improved production opti - mization, and increased productivity. Within the MTConnect community, the rise of analytics has been watched closely. The MT - Connect standard drastically reduces the cost of translating between different brands or types of equipment and devices. A factory outfitted with MTConnect is an appealing target for an analytics project, because data is already homogenized and uniformly defined. The MTConnect standard de - fines a semantic vocabulary or dictionary of terms, as well as a structure of how terms relate to one another. The dictionary specifies units, exact word - ings and spellings, and definitions. For example, "spindle speed" is normalized to "RotaryVelocity" and expressed in units of revolutions per minute. The structure or data schema specifies that Rota ry- Velocity is nested under a set of one or more rotary axes (for a single- or multispindle machine), and that rotary axes are in turn nested under a set of all axes, including rotary and linear. MTConnect for monitoring Machine monitoring was the first widely com- mercialized application using MTConnect data, and the standard has become closely associated with shop floor monitoring software and the companies writing and selling it. Those applications have long been used to visualize data like utilization and overall equip - ment effectiveness, although these days most software pack - ages have expanded to include additional data views, calcula - tions, or functions, such as downtime classi- fication or data breakdowns by shift, process, or operator. Many of these features relied on MTConnect data, either by adding calculation across multiple existing MTConnect data items or by adding new data items into the standard. Despite the close association between MTCon - nect and shop floor monitoring companies, MTConnect is not application specific. The role of the MTConnect standard is to expose device data using a consistent dictionary of terms (data items) and predefined structure, but once that data is formatted and exposed it could be used for anything. Predictive analytics for the factory Building on the foundation already in place for monitoring and status reporting, predictive ana- lytics is the most talked-about upcoming appli- cation area for MTConnect. Predictive analytics, which broadly means using data and statistical modeling to anticipate future events or condi- tions, has been talked about for decades in man- ufacturing. It may not have always gone by the name predictive analytics, but forecasting and er- ror prediction have long played a big role in miti- gating production risks. Predictive analytics in manufacturing starts with crosscutting predictive models that apply to many different industries. It is a discipline unto itself, and the best practices, modeling, software tools, techniques, and computer processing pow - er serving the discipline are always improving. As data science has become a full-fledged indus - try and a lucrative career path, many in the field have set their sights on manufacturing. Mean - while, data connectivity in factories has become FAST FORWARD l Manufacturing executives rank predictive analytics as the most important advanced manufacturing technology of the future. l The decades-old vision of anticipating breakdowns before they happen can now be achieved. l Factory connectivity coupled with the MTConnect standard is the underlying infrastructure of both predictive analytics and process improvement. Building on the foundation already in place for monitoring and status reporting, predictive analytics is the most talked-about upcoming application area for MTConnect.

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