40 Contact: BRIAN KUPTZ brian.kuptz@noricangroup.com and resources, as well as ensuring production targets are met. Pre-empting blade breakage through early detection and planned exchange cost only $1,600 at one of our customers—compared to at least $4,800 if the blade had been left to break. At another customer, ignoring blocked filters cost an extra $8,000 for clean-up and increased wear. In fact, just tracking a blast machine’s operating status over time can reveal a great deal about its own performance and that of the entire process. Supervisors can compare the efficiency of different product runs or shifts, with no need to build spreadsheets or even use paper-based methods. Careful inspection of both live and historical data can reveal issues, not just at the blast machine itself, but upstream and downstream from it. There might be loading and unloading delays, machine faults, unscheduled maintenance, operators taking unauthorized breaks and other issues. MEASURE EFFECTIVENESS Machine effectiveness metrics like performance and availability help translate operating data into more efficient production. Machine performance can be quantified by cycle time or, using a workpiece counter, output volume by hour, shift or other time period. Machine availability shows you when any downtime or production loss occurred and how long it lasted, so you can track and compare the production effectiveness of individual product runs and shifts. Where production stops, you can look at other KPIs to find out why. For example, an in-line CT blast machine is often integrated with a green sand molding line to clean scale from iron castings. If the molding line stops, the blast machine might be working perfectly and the problem lie elsewhere. If parts are not being unloaded from the blast machine’s outfeed – maybe a conveyer belt is failing or there aren’t enough staff available to unload parts – then the whole line will soon have to stop too. If there are no castings coming in via the infeed, then the shot blast machine will be idling. A MANAGEMENT VIEW If blasting stops, a quick glance at the dashboard shows if the machine has a technical fault and its infeed and outfeed status, so you can see if a problem is local, upstream or downstream. If your IIoT system is monitoring an entire foundry line, you can then check on the other machines’ data too. The point is you know immediately (either by constant monitoring or setting an alarm) when there is a problem with the blast machine and can investigate. How did production go this morning? Were volumes as predicted? If not, when did production stop? Often operators don’t pass on information to management. For example, if a failing motor triggers an alarm every two hours and stops the blast machine, the operator should alert maintenance. But if they just press the reset button, then that fault keeps reoccurring, causing more lost production. With digital, managers will see the regular stoppages, investigate and make sure the machine is repaired. It’s about making the process visible. For example, the worst problems might happen on Mondays. Comparing the times of stoppages to the type of product being produced could indicate if it’s a specific product that is causing problems. Or, if operators constantly stop a machine because the outfeed is blocked, managers might assume it is a blast machine problem when it's actually running perfectly and there’s just not enough packing boxes to load the cleaned castings. START MEASURING Informing changes to production strategy is perhaps digital's most powerful benefit. For example, overall equipment effectiveness (OEE) typically combines three metrics – performance, availability and quality – to highlight where you can improve production. Blast machine performance and availability instantly available while manually-generated quality control data can be added in later, letting you display and report on OEE. As you collect extra data and extend it into other applications, your IIoT system can become the “brain” of the company and be the single source of data that everyone trusts. Once you have the infrastructure in place to collect data and people are regularly using the system, there’s really no limit – digitally speaking – on how far you can go with it.
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