Framework Model for Asset Maintenance Management
Bibliographic record
Abstract
This paper presents the development of a generic framework for asset maintenance management. The framework has been presented in the form of an IDEF0 process model. The process model served to illustrate the interaction and dependencies among a diverse set of knowledge areas. In this framework, outputs from one management process become inputs to another in a subsequent hierarchy. The structure of the framework model exhibited the characteristics of flexibility and robustness. Updates in knowledge can be accommodated within the framework through incorporating new management processes and/or activities, as well as establishing new sequencing logic for these processes and/or activities. In a supporting effort to the development of the framework model, the writers have objectively reviewed the general capabilities of three commercially available software applications that are known within the asset management (AM) industry. These three applications, while encompassing a wide selection of capabilities, represent a typical selection of information technology (IT) tools and techniques that are widely used in strategic AM practices. The objective of this review is to study the operational characteristics and functionalities, and to assess the capability of software interoperability, of a representative sample of IT tools known within the AM industry.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".