Page 30 - MetalForming April 2017

Innovation
the development of new solutions to quicken response times and improve machine diagnostics, as well as the increased use of remote troubleshoot- ing. In the end, all of this leads to more efficient service.
One example: Integrated sensors within the slat cleaner of a laser-cutting machine. Here, this special power tool designed to clean the machine’s slats communicates with an online system
to notify users when maintenance is required. Although the monitoring tech- nology is fairly straightforward, fabri- cators can realize substantial benefits.
Further, in laser cutting new tech- nologies such as smart-nozzle automa- tion can ensure process reliability in addition to alerting the user when maintenance is required. A camera sys- tem with integrated sensors automat- ically inspects the cutting lens and noz-
zle during machine operation. Using this information, the user can contin- ually monitor consumable status and schedule cleaning or replacement.
Innovations such as these con- tribute to lean-manufacturing initia- tives by increasing efficiency through- out the shop. By this point, most fabricators have embraced lean man- ufacturing as a worthwhile endeavor and recognize its role in increasing effi- ciency and productivity for lower oper- ating costs and greater flexibility.
Preventive and Predictive Maintenance
Applying lean principles to service offerings has led to increased use of pre- ventive maintenance (PM), seeking to avoid unplanned downtime through regular performance and maintenance sessions. A recent survey of fabricators finds that machines covered by PM plans, compared to those not covered, require 20 to 30 percent fewer spare parts and repairs; will run with higher uptime; and will have a higher resale value. The real value of PM is realized, however, when the technician can apply experience and training to identify potential problems before they arise, and then schedule the least-disruptive fix to minimize machine downtime.
Soon, service concepts will take PM to the next level, allowing fabricators to identify concerns without relying on the keen eye of a service technician during a scheduled plant visit. It already is possible to predict potential failures by using machine data gathered by sensors, software and other tech- nologies. But as machine connectivity continues to increase, manufacturers will be able to derive even more data from a larger pool of machines.
With this data comes statistical rel- evance that can be used to identify sig- nals of impending problems. And, with these types of predictive-maintenance solutions in place, a metal fabricator no longer will have to request emer- gency support when faced with a downed machine. Instead, a service technician will proactively contact the user if, for example, a machine part is
28 MetalForming/April 2017
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