Engineering Leadership and Sustainable Smart Manufacturing: Literature Review with Focus on Contemporary Era (2000-2020)
Bibliographic record
Abstract
This study aims to explore the effective engineering leadership competencies and understanding engineering leaders’ role in achieving sustainable smart manufacturing (SSM) with focus on contemporary era (2000-2020). There will be an attempt to provide better understanding of the definition of engineering leadership and its importance in the future in the light of Industry 4.0. Besides, it intends to explore the main leadership competencies that engineers need to balance and achieve TBL sustainability and explore the common challenges and obstacles. Using the literature review approach, the study is based on a multidisciplinary approach that combines three different disciplines, namely engineering leadership, sustainability leadership and leadership 4.0. The study’s novelty lays in merging all these different leadership approaches together in one study. The study showed that most engineering leadership research focused on entry-level engineers to equip them with essential non-technical skills. in the majority of the engineering leadership studies related to population size, no general agreement of what engineering leadership is, use of different leadership models, and investigation of different leadership levels, sectors, and geographical areas because most of the studies have been conducted in Canada and the USA. The study also showed that sustainability is one of the fundamental goals of Industry 4.0. Although smart SM and Industry 4.0 have drawn the interest of the science community and industry in recent years, attempts to analyse the state of the art of these two emerging paradigms still lack in the literature. The situational, transformational, transactional, and authentic leadership styles appeared more than others in the reviewed studies. Finally, the results of the study will help industry to recruit effective leaders and improve leadership programme development. It will boost the engineering curriculum to prepare future engineers with the required leadership competencies required by the industry to overcome obstacles during the new industrial revolution.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".