System of System Based Sociotechnical Complexity Challenges in Product and Process Design
Bibliographic record
Abstract
Unique characteristic of system of system based product life cycle challenges evolves different level of systems. This means the product design system and process level system consideration are very important besides the system level issues for product and process development which are part of systems of system. These core issues include the physical elements, assembly process and its related cognitive elements of component to that particular assembly and its process at Sub system level which are fundamental of System of system in holistic perspective of new product and process design. Any system level change or variety affects the next adjacent system in the same product as a member of same family of a system of system. In this paper the aspect of Hybrid electric car battery has been explored to reduce the system of system level sociotecnical complexity in product design. In this context, the affect of changeability in the assembly system level has been explored and DFA analysis and the complexity Index of the product at physical structure, assembly process and cognitive system level been discussed to draw analogy for making an understanding of similar nature of the system in platform based product and process family development.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".