Magnesium Alloy Die Casting Process Improvement using the Single Minute Exchange of Dies (SMED) Method and Other Techniques
Bibliographic record
Abstract
In the die casting process, the optimisation of machine capacity utilisation is a key goal in achieving economic throughput. The tooling changeover procedure is widely recognised as a possible area for reducing plant downtime. Following a visit to a sister plant in Canada, the SMED method has been augmented by rationalisation of procedures. Identification of internal and external activities and moving activities off-line wherever appropriate was investigated, along with the elimination of Non-Value-Added Activities wherever possible. There was also a bottleneck in the use of a single crane which may have been otherwise engaged when dies need to be changed. Other operating parameters will need to be investigated, including robotic loading and unloading. There are a number of challenges and opportunities for further downtime reduction, and this study is therefore on-going. The design of a Smart Die and associated condition monitoring systems will be investigated. The business case needs to be addressed and costs/benefits analysed. Changeover times at the UK plant have so far been reduced from 24 hours to an average of 6½ hours.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".