1,721,040 research outputs found
Correction to: Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production
No full textIn the published article “Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production. Prod. Eng. Res. Devel. (2021). https:// doi. org/ 10. 1007/ s11740- 021- 01077-9” the order of author's name is given incorrectly. Erratum: Verna Elisa, Genta Gianfranco, Galetto Maurizio & Franceschini Fiorenzo was the Authors list in the article. Corrige: the correct Authors list should be: Elisa Verna, Gianfranco Genta, Maurizio Galetto & Fiorenzo Franceschini. Erratum: the previous citation of the article was: “Elisa, V., Gianfranco, G., Maurizio, G. et al. Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production. Prod. Eng. Res. Devel. (2021). https:// doi. org/ 10. 1007/ s11740- 021- 01077-9”. Corrige: the article should be cited as “Verna, E., Genta, G., Galetto, M., et al. Performance measurement for offline inspections under variable interactions and inspection errors in low-volume production. Prod. Eng. Res. Devel. (2021). https:// doi. org/ 10. 1007/ s11740- 021- 01077-9”. Original article corrected
Accurate estimation of prediction models for operator-induced defects in assembly manufacturing processes
Full text linkThe presence of defects in industrial manufacturing may compromise the final quality and cost of a product. Among all possible defect causes, human errors have significant effects on the performances of assembly systems. Much research has been conducted in recent years focusing on the problem of defect generation in assembly processes, considering the close connection between assembly complexity and human errors. It was observed that the relationship between the average number of defects introduced during each assembly phase and the related assembly complexity follows a power-law relationship. Accordingly, many authors proposed a data logarithmic transformation in order to linearize the mathematical model. However, as has already been discussed in literature, when the model is retransformed in the original form a significant bias may occur, leading to completely wrong predictions. In this paper, the bias due to the logarithmic transformation of models for predicting defects in assembly is analyzed and discussed. Two alternative methods are proposed and compared to overcome this drawback: the use of a bias correction factor to the retransformed fitted values and a power-law nonlinear regression model. The latter has proved to be the best approach to predict defects with few non-repeated data and affected by high variability, such as in the case under study
Puzzling choices in hard times: Union ideologies of social concertation in the Great Recession
Full text linkUsing the cases of Ireland and Portugal during the post-2008 Great Recession, we argue that unions' ideological formations around social concertation are central in aiding them to navigate their options about whether to engage in concessionary bargaining with government under crisis conditions. Building on Hyman's triangle of union identity, we show how an ideational perspective can complement interest-based accounts of unions' strategies to explain their engagement with policymakers or their opposition in the macro-management of the economy
An artificial intelligence classifier for electron beam powder bed fusion as-built surface topographies
Full text linkA novel quality map for monitoring human well-being and overall defectiveness in product variants manufacturing
Full text linkNowadays, companies are faced with demands for increasingly customised products, shifting from mass production to mass customisation. Thus, operators typically have to produce multiple product variants, often characterised by different complexity levels, while meeting quality standards. Companies, however, cannot only be concerned with production quality, but also with the quality and well-being of workers, as demanded by the human-centred paradigm of Industry 5.0. Therefore, this paper proposes a combined analysis of (i) production quality in terms of overall defects generated during product variants manufacturing and (ii) human well-being in terms of stress response. The combination of the two indicators results in a novel tool called “Quality Map”, which enables the evaluation and monitoring of quality systems during the production of product variants from a broad standpoint. To demonstrate the viability of the method, a collaborative human-robot assembly is used as a case study
Digital Metrology for Nanoindentation: Synthetic Data Generator for Error Identification
Full text linkDigital metrology enables precise, real-time measurement and data analysis using digital tools, which enhances accuracy and efficiency in manufacturing and quality control. Among key enabling technologies, Digital Twins allow continuous control, enabling predictive maintenance, faster error detection, and optimised performance of the measurement system. A current challenge is establishing traceability for the Digital Twins and for the data processing algorithms implemented in digital metrology. Nanoindentation is a challenging measurement technique that may be susceptible to several random and systematic measurement errors. This work presents a parametric synthetic dataset generator for quasi-static, room-temperature nanoindentation that incorporates correlation and covariance among simulated quantities. The method models indentation responses through a power-law formulation fitted via Orthogonal Distance Regression, allowing for traceable and physics-informed datasets. The generator enables the association of uncertainty with simulated results, supporting its use within a metrological framework. Its performance is benchmarked against non-parametric methods such as bootstrapping, showing comparable accuracy with significantly reduced computational cost and improved representativeness. Furthermore, the methodology can simulate main measurement errors for advanced material characterisation and develops a traceable tool based on synthetic data which could be used to train advanced quality control tools for the detection of main measurement errors
Nanoscale topographical characterization of permeability-related features in the production of polymeric films for food packaging
No full textPolymeric films play a vital role in food packaging, offering protective barriers that reserve the quality, safety, and shelf life of food products. Their performance depends on properties such as mechanical strength, thermal stability and permeability. Permeability is particularly important as it regulates the transfer of gases from the environment to food. Thus, permeability affects the shelf life, taste and safety of food products. The interaction between nanoscale surface features and permeability is a critical but under-explored aspect of film design. This study aims to test capability of surface topographical characterization as an alternative quality inspection tool for permeability in commercial polymer films. Advanced techniques such as Atomic Force Microscopy (AFM) are used to characterize surface features including roughness and morphology. The results will provide an alternative route for the permeability quality control in manufacturing processes of state-of-the-art commercial polymer films for food packaging
A value-driven approach to printed circuit board inspection: Strategic use of inspection technologies to reduce waste
No full textElectronic waste is an escalating global challenge that requires innovative and sustainable strategies to mitigate its environmental impact. This paper presents a decision model designed to identify the most effective inspection processes for printed circuit boards (PCBs) to enable their reuse, recycling or remanufacturing. The goal is to maximise the recoverable value of PCBs while minimising waste. By systematically analysing inspection processes, the model provides a structured framework for determining the sequence of measurement technologies that balance cost effectiveness with the potential for value recovery. This methodology improves resource efficiency and minimises environmental impact, in addition to supporting the principles of a circular economy. Through an illustrative case study, the approach shows how targeted inspections can significantly extend the life of electronic boards, improve economic value recovery and promote environmentally friendly manufacturing practices
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