Evaluation of alternative assembly line arrangements with stochastic operation times
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to develop a computer simulation model to evaluate increasing versus decreasing mean operation times assembly line arrangement for normal and exponential distributions and the variances equal to 1 and 16. Design/methodology/approach The model was developed on the basis of a realistic case problem and applied to a six‐station assembly line. The evaluation criteria were: the minimization of the total elapsed time; the maximization of the average percentage of working time; and the minimization of the average time in the system. Findings The increasing mean operation times line arrangement is superior to the decreasing mean operation times line arrangement for the normal and exponential distributions and the variances equal to 1 and 16, in terms of the total elapsed time and the average percentage of the working time evaluation criteria. The decreasing mean operation times lines is marginally superior to the increasing operation times line for the normal distribution for the variances equal to 1 and 16, in terms of the average time in the system evaluation criterion. The above inference can be made for the exponential distribution for the variance 16, but no definitive conclusion can be made for the variance 1. Overall, the increasing mean operation times line arrangement has proven to be superior to the decreasing operation times line arrangement for both the stated distributions and variances, in terms of the important evaluation criteria. Originality/value The paper contributes to the computer simulation approach to solving assembly line problems that deal with the impact of normally and exponentially distributed operation times, with variances equal to 1 and 16, on the increasing and decreasing mean operation times assembly line arrangements.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it