Establishing Human Performance Improvements and Economic Benefit for a Human-Centered Operator Interface: An Industrial Evaluation
Bibliographic record
Abstract
A controlled comparison of a human-centered operator interface to that of a traditional distributed control system interface was conducted to establish the human performance improvement. Twenty-one professional petrochemical plant operators completed a series of matching process upset scenarios on their respective plants' high-fidelity training simulators. Each scenario contained an equipment or process failure previously experienced in the real plants. The results indicated that operators using the human-centered design completed scenarios an average of 7.5 minutes faster (41% improvement over the traditional interface), successfully dealt with failures in 96% of the cases (a 26% improvement), and recognized the presence of the failure before the first process alarm in 48% of the cases (a 38% improvement). These performance results were then used as input to a Monte Carlo simulation that estimated the economic benefit for the human-centered interface at $1,090,000 CAD per year for a plant of comparable size.
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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 | 0.001 | 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 | 0.001 | 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".