Operationalizing Mass Customization in Manufacturing SMEs—A Systematic Literature Review
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
With the emergence of the fourth industrial revolution, market globalization, and growing customer demands, companies are being forced to rethink their ways of doing business to remain competitive. Small and medium-sized enterprises (SMEs) in the manufacturing sector must also adapt to personalized customer demands. This context forces companies to migrate towards mass customization. The literature proposes several strategies for adapting to this new paradigm but does not offer an implementation sequence for successfully operationalizing mass customization within an SME. Based on a systematic review of the themes surrounding Industry 4.0 and mass customization in the literature, this article aims to highlight the different strategies and factors to be put in place to successfully implement mass customization. This research reveals the lack of a prioritization of factors that favour the operationalization of mass customization. Lastly, the literature does not detail the tools and their levels of maturity resulting from the factors to be implemented. This article highlights the gaps in the literature related to mass customization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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