Human factors in production and logistics systems of the future
Bibliographic record
Abstract
The way humans work in production and logistics systems is changing. The evolution of technologies, Industry 4.0 applications, and societal changes, such as ageing workforces, are transforming operations processes. This transformation is still a “black-box” for many companies, and there are calls for new management approaches that can help to successfully overcome the future challenges in production and logistics. While Industry 4.0 emerges, companies have started to use advanced control tools enabled by real-time monitoring systems that allow the development of more accurate planning models that enable proactive managerial decision-making. Although we observe an increasing trend in automating human work in almost every industry, human workers are still playing a central role in many production and logistics systems. Many of these planning models developed for managerial decision support, however, do not consider human factors and their impact on system or employee performance, leading to inaccurate planning results and decisions, underperforming systems, and increased health hazards for employees. This paper summarizes the vision, challenges and opportunities in this research field, based on the experience of the authors, members of the Working Group 7 (WG7) “Human factors and ergonomics in industrial and logistic system design and management” of the IFAC Technical Committee (TC) 5.2 “ Manufacturing Modelling for Management and Control ". We also discuss the development of this research stream in light of the contributions presented in invited sessions at related IFAC conferences over the last five years. The TC 5.2 framework is adapted to include a human-centered perspective. Based on this discussion, a research agenda is developed that highlights the potential benefits and future requirements for academia and society in this emerging research field. Promising directions for future research on human factors in production and logistics systems include the consideration of diversity of human workers and an in-depth integration of Industry 4.0 technologies in operations processes to support the development of smart, sustainable, human-centered systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".