A Thousand Parts a Shift and You Remember the Failures, Not the Throughput
Every production manager knows the "good" days—the shifts where the machines hum, the scrap rate is near zero, and the target quantity is met two hours early. But the shifts that actually define the profitability of a shop are the "bad" ones. The shifts where a single broken tap or a misalignment in Operation 4 burns through three hours of "overclocked" time while the technician tries to diagnose the issue.
If those failures aren't documented immediately, they become anecdotes. "I think we had a problem with that job last month," becomes the only piece of data you have for the next planning cycle. This template turns those anecdotes into a structured post-mortem that identifies exactly why your production targets were missed.
The Gap Between Required and Reality
The "Quantity Required" vs. "Quantity Made" fields are the two most important numbers in the database. That delta—the missing parts—represents your scrap rate and your lost margin. But the "Quantity Made" field only tells you that you failed. The "Op No." (Operation Number) field tells you where.
In a complex manufacturing flow, a part might pass five operations before failing at the sixth. If you're consistently losing parts at Op 30, the issue isn't with the material or the operator—it's with the tool path or the fixture for that specific stage. By logging the "Date Of Opperation" against the specific Op No., you can correlate failures with environmental factors: Is Op 30 failing more often on humid afternoons when the coolant temperature spikes?
Overclocked Time: Tracking the Production Bleed
"Reason For Overclocked Time" is the field that exposes the hidden costs of production. In manufacturing, "overclocked" isn't about computer speed—it's about the time spent beyond the standard labor estimate for the job.
Is the machine sitting idle because of "Tooling Issues"? Was the "Reason" a delay in material delivery from the warehouse? Or was it a "Job No." that was misquoted, requiring 20% more time than the estimate allowed? By forcing a specific reason for every minute of overclocked time, you move from "we're running behind" to "we spent 14 hours this week waiting for Inspection to sign off on Drawing No. 104."
Dual-Image Evidence for Root Cause Analysis
"Image 1" and "Image 2" provide the visual proof that notes can't capture. When a part fails quality control, a photo of the defect in the machine fixture ("Image 1") vs. the part on the inspection table ("Image 2") can reveal a vibration issue or a tool-wear pattern.
These images serve as a bridge between the shop floor and the engineering office. When the engineer pulls up "Drawing No." and "Iss No.", they see the actual photo of the failure. They don't have to walk down to the floor and dig a part out of the scrap bin. They see the visual evidence of the "Problem Log" and can adjust the "Iss No." revision to fix the root cause before the next "Job No." is released to the floor.