Optimal Allocation of Worker Hours to Competing Design Projects to Meet Value Growth Targets
Bibliographic record
Abstract
Value creation is the motivating principle of lean product development processes. Set-based concurrent engineering has been proposed to improve product development efficiency and stimulate innovation. However, this approach can lead to inefficient resource utilization because it promotes the development of competitive designs, and effective worker time allocation is a real need in complex design projects. This paper looks at one aspect of resource allocation: optimally assigning limited manpower to competing design projects using a project value growth model that characterizes the translation of work-hours into developed value. While resource allocation methodologies have been proposed before, this paper adds to these efforts by including the lean principle of value together with worker capability when delivering project work and formulates the solution as a predictive control problem. The optimized allocation solution can give guidance to project managers if it is necessary to add overtime or change scheduled completion dates if target value growth is missed because of scarce resources.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".