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Case Study - Simulation and Emulation - Labeler Speed Optimization
 

The Problems

Polytron and E²M designed and installed a bottling line for a major food and beverage manufacturer.  The rated speed of the system required labeling speeds of 1200 bottles per minute (bpm).  The team decided to install parallel labelers, each capable of 600 bpm in order to meet the required speed and ensure a higher line efficiency.

As the customer ramped up production, their operations staff noticed some problems in the labeling area they could not figure out.  The labelers seemed to be operating inefficiently causing downtime, quality and equipment problems.  The E²M/Polytron team elected to use our PolySimsm  emulation modeling methodology to recreate the scenario off-line through emulation, isolate the problem and develop and test the remedy.  

The Solutions

While running the model of the system, we found a pattern characterized by fluctuating machine speeds, eventually resulting in downtime.  This was difficult to recognize during normal production because the problem did not recur except under special circumstances. Using the PolySimsm process, we adjusted the control logic to balance the system.  Changing the timers of two photo-eyes stabilized single filer B.  However, now both labelers were running worse.  Analyzing speed graphs from the emulation model, we found that the sensors used to initiate low speed on the machines needed to be relocated as well.

The problem scenarios were recreated using our PolySim emulation model and confirmed by all operators and technicians.  The solutions were then tested on the model and all were in agreement with the proposed solution.  The logic revisions were sent to an engineer on site and implemented within a matter of minutes.

The Results

Upon restarting the labelers and testing the new logic with normal production scenarios, all stakeholders agreed that the problem had been resolved.  Our PolySimsm methodology allowed the team to discuss the issue, isolate the root cause, develop potential remedies and then test the remedies, all off-line, without distracting production personnel or causing any unnecessary downtime.

 
 
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