Case study
Solving a Critical Heating
Challenge during Ramp-Up
Summary
Launching a new mass production line always comes with risks. In this case, a large-scale inverter ramp-up was stopped almost immediately after start because of a critical yield collapse. The problem appeared simple, parts were failing pre-bake due to unstable temperature, but multiple engineers and managers spent days investigating without progress.
As an external problem-solving expert, I joined the team with one goal: quickly identify the root cause, validate it with data, and restore production. Within a short time, we went from a crisis-level 17% FPY to a stable 97% FPY, enabling the plant to enter volume production.
The Problem
The production line for a new inverter product was expected to ramp smoothly, but FPY dropped to just 17% at pre-bake.
Temperature instability was observed at the part level — many products were falling below the lower specification limit.
Production was halted, as continuing would have created massive scrap costs and reliability risks.
A cross-functional team was assembled, including the manufacturing manager, R&D leader, and several engineers. Despite multiple root cause analysis attempts, no clear factor explained the failures.
This combination of high visibility, halted output, and mounting pressure made the situation extremely urgent.
The Investigation
To understand the problem, I began by separating machine conditions from product behavior:
Product data review: I analyzed thermal profiles across different runs. The trend confirmed that parts consistently failed to reach stable target temperature.
Machine sensor analysis: I compared the internal heating block sensor readings with the product’s actual measured temperature. A mismatch indicated poor thermal transfer.
Hypothesis testing: Initial adjustments of heating profiles and setpoints were attempted, but no sustainable improvement was seen.
At this point, the issue remained hidden. Standard DOE and parameter shifts did not reveal the underlying cause.
The Investigation
To understand the problem, I began by separating machine conditions from product behavior:
Product data review: I analyzed thermal profiles across different runs. The trend confirmed that parts consistently failed to reach stable target temperature.
Machine sensor analysis: I compared the internal heating block sensor readings with the product’s actual measured temperature. A mismatch indicated poor thermal transfer.
Hypothesis testing: Initial adjustments of heating profiles and setpoints were attempted, but no sustainable improvement was seen.
At this point, the issue remained hidden. Standard DOE and parameter shifts did not reveal the underlying cause.
The Breakthrough
I proposed a simple but unconventional test: swap the heating blocks between two different machines of the same process type.
After the swap, the yield performance followed the block — not the machine.
This suggested the problem was hardware-specific, not machine-wide or software-related.
Upon closer inspection, I noticed the supplier had not provided official surface roughness verification for the heating blocks. My hypothesis: poor surface finish reduced the physical contact between block and part, causing insufficient heat transfer.
I escalated this to the supplier and requested new heating blocks, this time verified with lab-certified surface roughness measurements.
The Result
The new heating blocks were installed.
On the very first run, FPY jumped from 17% → 97%.
Production was immediately restarted, and the ramp-up continued without further major issues.
This rapid turnaround avoided weeks of lost production and significant financial losses. More importantly, it built confidence in the production line and prevented potential customer delays.
Lessons Learned
This case demonstrated that:
Yield collapses often hide in small overlooked details (in this case, surface finish).
A structured yet flexible root cause approach can uncover issues that traditional parameter tweaking will miss.
Involving suppliers early and challenging assumptions (like “the hardware is within spec”) is critical.
Conclusion
A ramp-up crisis that had stalled production was resolved through a combination of structured analysis, practical experimentation, and supplier engagement. By validating the true root cause and implementing a simple hardware change, the line was restored from 17% to 97% FPY.
Facing a critical Yield / Quality issue?
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