Implementing systems engineering and project management processes in a Canadian company – Overview and Results Achieved
Bibliographic record
Abstract
Abstract This article presents a project consisting of implementing project management and systems engineering processes at CSinTrans Inc. (CSiT), a Canadian company founded in 2011. CSiT provides multi‐modal transit information systems as well as information integration to the transit industry worldwide. The Basic profile of the ISO/IEC 29110 for systems engineering has been used as the main reference for the development of these processes. The reasons that prompted CSiT to implement the ISO/IEC 29110 are mentioned. The approach and details on how the standard has been implemented are presented. The lessons learned are described. CSiT developed three process groups to match the attributes of projects such as size and nature. The selection of tools to support the processes is discussed. Third‐party audits, conducted annually since 2016, that led CSiT to become the first systems engineering company successfully audited with ISO/IEC 29110, are presented as well as the benefits obtained. ISO/IEC 29110 has helped raise the maturity of the organization by implementing proven practices and developing consistent work products from one project to another. ISO/IEC 29110 was a good starting point to align processes with specific practices of CMMI® Maturity Levels 2 and 3. ISO/IEC 29110 has also helped CSiT in developing light processes as well as remaining flexible and quick in its ability to respond to its customers. To illustrate the implementation of the Basic profile of ISO/IEC 29110 in other engineering domains, this article briefly presents the implementation in the automotive, agriculture, aeronautic, nuclear and space domains in 6 enterprises of France in 2018.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".