Realtime reconfiguration using an IEC 61499 operating system
Bibliographic record
Abstract
An emerging technology for distributed process control in the manufacturing industry is the IEC function block architecture (numbered 61499). Widespread deployment of this new technology in Intelligent Manufacturing Systems (IMS) is dependent upon how well the architecture supports reconfiguring tasks while satisfying the associated realtime constraints. However, function blocks without additional realtime facilities may be too limited for many IMS situations, since they do not explicitly represent time during the modification of their autonomous behaviour or when adjusting their cooperative interactions with other system entities. We are developing an operating system geared to the execution and management of function blocks, which supports dynamic reconfiguration in realtime. This operating system is a significantly different approach to other IEC 61499 platforms. An appropriate set of services in the operating system have been designed to facilitate runtime reconfiguration. The paper outlines how these services augment the realtime constraints in the IMS in order to enable the function blocks to perform varying degrees of reconfiguration on the fly. In this paper, we also present a worked example of how realtime reconfiguration can be supported in a suitable IMS scenario using the operating system. A ' proof of concept' prototype of the operating system is currently being developed at the University of Calgary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".