The Impact of Complexity during Product Design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ever increasing product complexity is an obstacle to effective product development. This paper introduces an agent-based model to study the impact of complexity during product design. Product was modeled as a set of functions that require knowledge, design effort and integration, and designers were modeled as agents who applied knowledge to function development tasks and communicated with each other. Simulation experiments were conducted to study the impact of variables, such as: designers’ knowledge level, designers’ experience, coordination efficiency and organizational structure under different levels of product complexity. The results suggest that an increase in complexity increases effort and span time exponentially. Thus, for the development of complex products, more effective coordination mechanisms should be applied when a project has very high levels of complexity and innovation. Having more knowledgeable and experienced designers also helps to lessen design effort and shorten span time. No assertion could be made as to whether a team or matrix organizational structure was superior.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it