Decanter Brand Selection Using Multi-Criteria Decision Making
Bibliographic record
Abstract
Decanters play a crucial role in Palm Oil Mills by separating the oil phase from the sludge underflow in continuous settling tanks during the clarification process. Given the significance of decanters and the multitude of manufacturers, this study focuses on a comprehensive evaluation of three-phase decanter brands selection. Utilizing the analytic hierarchy process, the research explores the nuanced criteria of economics, technical aspects, and service quality for brand selection. Sub-criteria include operational cost, price, overhaul cost, emulsion content, oil losses, capacity, distance to buffer tank, electricity consumption, service scheme, guarantee, spare part availability, and workshop location. The alternatives considered are common decanter brands in Indonesia: Alfa Laval, IHI, Flottweg, and Westfalia. Using Expert Choice®, the analysis identifies Flottweg as the optimal decanter brand based on performance, particularly excelling in service criteria with a priority weight of 0.336. Sensitivity analysis indicates that for IHI to be considered the first option, technical and economic criteria must be prioritized above 56.5% and 50.0%, respectively. This study also concluded that technical and service aspects are equally important in decision-making for the decanter brand in POM A, surpassing economic ones, with service aspects as the critical factor in decanter brand decision-making.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".