Relating additive and subtractive processes in a teleological and modular approach
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
Purpose The purpose of this paper is to relate additive manufacturing (AM) and machining (CNC) synergistically in a modular approach in the design and manufacturing domains, to generate value for end‐users and manufacturers (a teleological system). Design/methodology/approach The research methodology decomposes a part into modules, by employing a teleological systems theory approach paired with principles of modular design. Modules are manufactured with either additive manufacturing (fused deposition modeling, FDM) or machining (CNC). Process selection is determined by a decision‐making framework that quantifies strength and weakness comparisons of FDM and CNC machining processes, accomplished using the analytic hierarchy process (AHP). Findings The developed methodology and decision‐making framework is successfully applied to the design and manufacturing of a large, complex V6 engine section sand casting pattern. This case study highlights the merits of the research. Research limitations/implications The research assumes that the processes being considered are capable of meeting the product functional requirements. The proposed methodology can be extended to evaluate additional processes. Practical implications Value is assessed in this research relative to: time and cost opportunities, managing knowledge limitations of a process by leveraging hybrid options, and aligning design and manufacturing to create a product that accomplishes the goals of the end‐user (teleological effectiveness). Originality/value Utilizing the AHP process and a teleological perspective are new, and proven effective, approaches in relating additive and subtractive processes in a hybrid approach with end‐user perspectives. The research demonstrates a systematic methodology to quantify additive and subtractive process selection.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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