Implementing Critical Control Management in a Mature Processing Plant
Bibliographic record
Abstract
This paper describes how Process Safety Management (PSM) was improved at a mature asset following a significant process safety event. An unconventional approach was adopted to enable rapid improvements drawing on the Critical Control Approach documented in Energy Safety Canada's A Barrier Focused Approach (similar to the International Council of Mining and Metals (ICMM) publication, Critical Control Management; Implementation Guide) as well as high reliability organisational (HRO) principles.The successful approach owes its intellectual origins to the concept of Safety Critical Elements (SCEs) first enunciated by the UK Health and Safety Executive following the Piper Alpha disaster. The history of the critical control approach is briefly discussed and how the original SCE idea has been enhanced. In particular, the paper will describe how the critical controls (or barriers) have been made more visible to those charged with implementing and managing them.The paper will describe the successes and difficulties of this approach including the shift in thinking required on the part of process safety experts as well as changes to organisational structure. The paper will also illustrate how the existing documentation of the critical controls was substantially reduced and rationalised to make the PSM problem (as perceived by senior managers) more manageable and sustainable. Finally, the paper will consider the extent to which well-known international PSM frameworks enhance or inhibit the adoption of this approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".