Page 20 - MetalForming November 2016

Do You Place a Dollar Value on Downtime?
Machine: Press 15 -- Interval: Week
AVAILABILITY
Interval Period: 7/3/2016 12:00:00 AM To 7/10/2016 12:00:00 AM
PERFORMANCE EFFICIENCY
QUALITY RATE
OEE
Actual Production Rate (Calculated) 1,272 cycles/hr Cycle Time 2.83 seconds
dark without much data to support those critical decisions. And, often those attempts are made after the fact, when productivity already has suffered and the impact is felt throughout the plant.
“We prefer to fine-tune our process- es and react early to prevent big prob- lems late in a run,” says ODM produc- tion manager Brandon Enright.
Enright has overseen the installa- tion of SmartPac 2 controls on four of ODM’s 17 mechanical stamping presses (200- to 1500-ton capacity), and ShopFloorConnect on 10 presses and on its four robotic-welding cells. Compared to its older press controls, the SmartPac 2 units “provide added functionality that helps us get back up and running whenever there’s an issue with a press,” says Enright. “For example, we just don’t learn that a sensor has faulted, now we know how it faulted, which is huge in terms of identifying a root cause of the prob- lem more quickly. Also, new tonnage- monitoring functionality allows us to develop a history of the tonnage over a tool’s lifetime, again helping identify early-on when a tool needs mainte- nance prior to something catastrophic happening.”
A Smart Factory Excels at Continuous Improvement
Asked to identify continuous- improvement projects spurred by its recent data-gathering and analysis efforts, Enright points to a plague com- mon to many metalforming shops: maintenance-related downtime.
“By using the flurry of data we can now collect from the plant floor using ShopFloorConnect,” he shares, “we’ve been able to identify common, recur- ring issues and conduct detailed root- cause analysis in each case. As a result, in many cases we’ve signed service contracts with vendors to perform monthly, quarterly or annual inspec- tions. And, we fine-tuned our preven- tive-maintenance activities—all to ensure that we keep the equipment running at optimum performance lev- els at all times. The improvement in
OEE By Machine (with Primary Ideal Rate)
From: 7/3/2016 12:00:00 AM A. Total Available Time
B. Planned Downtime
C. Net Available Time (A - B) D. Unplanned Downtime
E. Operating Time (C - D)
F. Availability (E / C) x 100
G. T otal Cycles Run
H. Ideal Production Rate
I. Performance Efficiency ((G / E) / (H / 60)) x 100
J. Total Defects (Rework + Scrap)
K. Quality Rate ((G - J) / G) x 100
Overall Equipment Effectiveness (OEE) by Tool (F x I x K ) Equipment Availability x Performance Efficiency x Quality Rate
Report Range
To: 7/10/2016 12:00:00 AM 10,080 min
4,979 min 5,101 min 745 min 4,356 min
85.4 %
92,370 cycles 1098.0 cycles/hr
115.9 %
0 parts 100.0 %
98.9 %
18 MetalForming/November 2016
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OEE reports, by machine, help identify continuous-improvement opportunities, to unearth hidden press time and allow ODM to bring in more work without adding new capital equipment.
OEE has been critical to allowing us to grow—both in new customers, and in the work we’re doing for existing cus- tomers—without adding new presses.”
One more example: tracking cycle time through the robotic-welding cells, and identifying inconsistencies that can be tracked back to flawed procedures.
“By knowing immediately if a cell’s throughput is slipping,” Enright says, “we can troubleshoot before things spi- ral out of control. For example, we’ve identified wear parts on the robots that can inhibit performance, so that we
can replace them in a timely manner. And, we’ve identified processes where the robotic welder works more quickly than the operator tasked with loading and unloading the weld fixtures, caus- ing robot idle time. Again, we assign a dollar value to downtime. In these cases, we might redesign the fixture or provide the operator with special tools to allow him to load/unload more quickly, or look to make his process more ergonomic.
“We’re fine-tuning and reacting,” he summarizes, “rather than fixing big issues late in production runs.” MF