Identification and weighting factors influencing the establishment of a single minute exchange of dies in plastic injection industry using VIKOR and Shannon Entropy
Bibliographic record
Abstract
Single minute exchange of dies (SMED) is one of the most important tools to achieve lean production system. The main idea of this system is to provide methods and to use creative and innovative solutions for continuous improvement. Due to the importance of this issue and its effect on reducing waste during the production process, this study presents a method to identify and to weight factors in the establishment of a single minute exchange of dies in 14 plastic injection factories. In this study, fourteen factories in injection industry were chosen and the factors influencing the implementation of single minute exchange of dies were identified. Following data collection, decision matrix was formed and the weight of each factor was determined by using Shannon Entropy. Then, in order to determine the readiness of factories, VIKOR method was used to rank companies. The results indicate priorities of the following factors in establishing SMED that include: Senior management support, technical capabilities, technical knowledge of staff and consultants, knowledge of mold design, manufacturing infrastructure, team work, combination of the project team work, benchmarking, training, clear understanding of project objectives, rewards and motivation, proper management expectation, project management, teamwork and organizational culture. Practical implications: Due to the factors, Top manager can make the best decision for implementing of SMED technique. This study develops factors influencing on SMED implementation based on Shannon and VIKOR methods for ranking parameters and plants.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".