A case study in productivity-cost trade-off in the design of paced parallel production systems
Bibliographic record
Abstract
This paper examines the investment and operational cost differences between high-volume serial CNC-based machining lines and parallel CNC-based machining lines. With the progress of CNC technology and their descending cost, more CNC machines have been used in high-volume production systems. CNC machines increase the flexibility and machining capability of production lines, greatly increasing the number of line configurations. Parallel configurations improve system throughput and have the same effect as adding buffers to a pure serial line but without additional work-in-process inventory. This analysis is performed through a case study of a CNC-based automotive cylinder head machining line. Examining machine reliability, line balance, configuration throughput, and cost yields insight into the cost-benefit tradeoff of implementing parallelism. It is found that even with large increases in investment in automated material handling, parallel configurations can yield significant annual cost savings over pure serial lines through reductions in capital investment, especially in CNC machines, and improvements in efficiency, and on a per unit capacity basis, parallel configurations are the least expensive.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".