A review of methodologies for integrating human factors and ergonomics in engineering 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
The requirements of Human Factors and Ergonomics (HF/E) in engineering design must be satisfied, including usability, safety, reliability, and operability in the workplace and work environment. This study presents a review of the methodologies for integrating HF/E information in engineering design. The primary purpose of this review is to identify and summarise the current research in this field, thereby giving the recommendations of future research. The focus is on the interaction design between the system (product) and its user (human), including the design of a complex machine, equipment, system, and simple product. Publications in this field between 1982 and 2017 were reviewed from two aspects: (1) the stage of HF/E information integration in engineering design, including conceptual design, embodiment, and detailed design, and (2) the category of the HF/E, including physical ergonomics, cognitive ergonomics, and organisational ergonomics. The benefits and limitations of the reviewed design methodologies were stated in their respective sections. A critical analysis of the research topics from these two aspects was performed with comparison summarising the applicability of these methodologies for researchers and designers. The suggestions for future research were also offered according to the main findings.
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.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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