Organizing the fragmented landscape of multidisciplinary product development: a mapping of approaches, processes, methods and tools from the scientific literature
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
Abstract The fourth industrial revolution is shaping a new industrial landscape. A variety of technologies related to software, information and communication technologies embody a ubiquitous digital and connectivity era. These technologies enable the creation of new products with the integration of connectivity, data collection and processing capacities which require combining engineering disciplines. Increasing product multidisciplinarity compels companies to adapt their product development practices. The scientific literature offers a variety of concepts and techniques to support multidisciplinary product development. This paper seeks to organize the landscape of concepts and techniques available for multidisciplinary product development. An extensive literature review was conducted, and 236 concepts and techniques were identified. Multidisciplinary products of interest deal with both software and hardware development and can be encountered through the denominations of cyber-physical systems, mechatronics and smart products and systems. An in-depth analysis led to the classification and mapping, for each product denomination, of the concepts and techniques available to support their development. The classification relies on a four-level model paired with a decision tree to thoroughly sort the variety of concepts and techniques into the approach, process, method, and tool levels. The mapping between the sorted concepts and techniques enabled the generation of graphical representations called cartographies. These cartographies serve to support companies’ transformation towards the fourth industrial revolution from the product development perspective by giving a general overview of the related literature, and guiding them in the identification of the most suitable approaches, processes, methods and tools.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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