Nov_Dec_AMP_Digital

FEATURE A D V A N C E D M A T E R I A L S & P R O C E S S E S | N O V E M B E R / D E C E M B E R 2 0 1 7 5 4 9 other, leaving valuable data unshared across these different business systems. In many cases, each is providing exactly what is intended, but with gaps in data—gaps that may very well be filled in by a different system with valuable data just waiting to be shared. Field devices provide valuable process data and ma- chine status. The good news about data capture in heat treating is that it has been gathered for years. Process data from field devices comes from microprocessor controllers, programmable logic controllers (PLCs), and discrete instru- ments. Even field devices without communications provide feedback to data collection systems in the form of discrete I/O or 4-20 mA signals. An example of this is a door with a simple limit switch tied to a PLC, providing a count of the number of times the door has been opened; this information is then used to coordinate planned maintenance instead of facing an unexpected outage. There is no right or wrong way to slice through data for decision-making processes. What one operation identifies as beneficial, another may not. In fact, many manufacturing and heat treating operations do not fully utilize the data they already have. Inmany cases, there is simply not enough time to sort through the information. In other cases, the expertise is not available to present data in a format that would enable decision-making. Quick analysis of real-timedata is standard operating procedure when it comes to heat treating. Howev- er, the challenge becomes real-time analysis of process data used for operational analysis that can be acted on . In many cases, a gap exists between the time data is produced and the time it is used for something actionable. INTELLIGENT HEAT TREATING Several years ago, Pete Hushek from Phoenix Heat Treat coined the term “intelligent heat treating.” What Hushek envisionedwas taking full advantage of the data that was available to him to create a predictive process for cycle development and an opportunity to improve operational performance with his SCADA and automated process con- trollers. Keeping operators informed about load status gives them a heads-up on equipment coming available, allowing labor to shift to load preparation to ensure equipment use is maximized. According to Hushek, “We are constantly mining data to look at quality and operational improvements. We have had an opportunity to refine cycle times and adjust ramps, preheats, and soaks that incorporate data from our tem- perature uniformity surveys. This provides our team with visual information related to sufficient load temperature uniformity, meeting industry specifications and customer requirements.” This is just one example of information in heat treating being used to help with quality, cost, and performance. IIoT is bigger than real-timemachine information and plant-wide SCADA. But the definitions of IIoT are really based on how companies put the information to use. Companies like Gen- eral Motors use IIoT as the foundation for their Industry 4.0 initiatives and to achieve zero downtime on their manufac- turing lines. DATA ANALYTICS Because heat treating is an additional treatment per- formed on a manufactured part, it also impacts overall product flow. The significance of delivery time is escalated when the parts being heat treated are a component of a fin- ished good. Transparency of timelines and updates about parts status are what many industrialists benefit from with IIoT, whether dealing with customer service from an outside heat treat service provider or workflow in a captive shop, for example. Gathering data from field devices collectively pro- vides information on equipment status and remaining time, while using historical statistics can predict completion time. Data analytics is the future of automation in manu- facturing. Autonomous machines using established metrics combinedwith real-time and historical information allow for the highest level of productivity by predicting and prevent- ing potential problems in pursuit of a zero-downtime oper- ation. Employees armed with smartphones can quickly de- liver information relevant to their job responsibility. The key is providing relevant content to the end user. If too much in- formation is presented to someone, it becomes background noise and loses its benefit. It is important to have a system that not only captures data efficiently, but also provides the information in an eas- ily digestible format. Visualization often helps, providing a familiar format for quickly reviewing data and an opportu- nity to react swiftly and make well-informed decisions. One of the major hurdles in using this information is making it accessible in a timely and actionable manner. Delivering the right data in a summarized format to the right individual is where benefits start to be realized. IIoT has tremendous potential in so many areas of in- dustry, and the opportunities in heat treating cannot be overlooked. The potential for predictive processes, mainte- nance, and productivity will be fully realized as the heat treat industry combines data from multiple sources and focuses on evaluating—and acting on—both real-time and historical data that is readily available. ~HTPro For more information: Jim Oakes is vice president of busi- ness development, Super Systems Inc., 7205 Edington Dr., Cincinnati, OH 45249, 513.772.0060, joakes@supersystems. com, www.supersystems.com. 10 FE T E