Uncertainty Evaluation Framework of Large-Scale Metrology for Precision Manufacturing in Shop Floor Environment

With the rise of Industry 4.0, digital manufacturing and smart measuring technologies are enabling the development of zero-defect manufacturing strategies, which leads to less material waste and lower energy consumption, moving from off-line metrology and dedicated measuring equipment to in-line measurements and automated inspection systems. This is especially important for the production and manufacturing of large-scale parts, because of the high component cost and long delivery cycle. However, establishing traceability for measurement systems is often complicated due to both the measurement technology and the objects being measured. Traceability of measurement in the manufacturing environment is not ensured yet, and uncertainty evaluation for in-process measurement remains a complex and active research challenge. This work introduces a new uncertainty modelling and evaluation framework for traceable measurement of the large-scale components in ‘shop floor’ conditions. The framework is verified using real data obtained from various instruments for in situ measurement of a large artefact. Experimental results demonstrate that uncertainty evaluation for large-scale metrology is crucial for precision manufacturing on the production floor. The methods can be extended to the evaluation of measurement uncertainty of components with a smaller size and off-line inspection.

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Publication Details

Journal
Metrology
Published
2026-06-17
DOI
https://doi.org/10.3390/metrology6020042
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Uncertainty Evaluation Framework of Large-Scale Metrology for Precision Manufacturing in Shop Floor Environment

Simon Cavill, Yongjia Xu, Li Li, Feng Li
Metrology
Industrial Vision Systems and Defect Detection
article

Uncertainty Evaluation Framework of Large-Scale Metrology for Precision Manufacturing in Shop Floor Environment

Simon Cavill, Yongjia Xu, Li Li, Feng Li
article en

Abstract

With the rise of Industry 4.0, digital manufacturing and smart measuring technologies are enabling the development of zero-defect manufacturing strategies, which leads to less material waste and lower energy consumption, moving from off-line metrology and dedicated measuring equipment to in-line measurements and automated inspection systems. This is especially important for the production and manufacturing of large-scale parts, because of the high component cost and long delivery cycle. However, establishing traceability for measurement systems is often complicated due to both the measurement technology and the objects being measured. Traceability of measurement in the manufacturing environment is not ensured yet, and uncertainty evaluation for in-process measurement remains a complex and active research challenge. This work introduces a new uncertainty modelling and evaluation framework for traceable measurement of the large-scale components in ‘shop floor’ conditions. The framework is verified using real data obtained from various instruments for in situ measurement of a large artefact. Experimental results demonstrate that uncertainty evaluation for large-scale metrology is crucial for precision manufacturing on the production floor. The methods can be extended to the evaluation of measurement uncertainty of components with a smaller size and off-line inspection.

MetrologyVol. 6(2)
Engineering and Physical Sciences Research Council (GB), University of Huddersfield (GB), Altex Technologies Corporation (United States) (US), Advanced Manufacturing Research Centre (GB)
Affordable and clean energy
Openalex Percentile: Top 7%
Industrial Vision Systems and Defect Detection
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