Theory of Technical Systems – Relationships to Engineering Sciences
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
Products (process or tangible systems) are defined with reference to standard ISO9000:2005. Designing products with a substantial engineering content, technical systems (TS), means to fully describe them ready for manufacture – in detail and assembly drawings, parts lists, adjustment instructions, customer instructions, etc. Designing must take into account all recognized requirements, especially implied and stated requirements for the designing-manufacturing-distributing organization, the intended transformation process (TrfP), and all other phases of the TS-life cycle, including societal norms, economic considerations, etc. The theory of technical systems (TTS) and its associated engineering design science (EDS) provides a framework for design considerations about engineering products, including the technology, TS-life cycle, properties, and other aspects of artificial transformations and their operators. The triad ‘theory - subject - method’ suggests that a systematic enginee-ring design method can be derived from TTS and EDS, to augment the usual intuitive design procedure, especially where the design problem is not routine. Engineering sciences are essential in this design process, (a) for analysis of existing systems and/or proposals for synthesis of designed systems, and (b) to assist as heuristics during design synthesis. Design synthesis is the more difficult operation, it requires iterative working. Several case examples have been published to demonstrate the application of the recommended systematic design method. Some of the relationships between engineering sciences and systematic design processes are explored to show their interdependence, and the need to provide a wider context in this area.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it