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This paper introduces a simulation-based approach to enhance quality defect detection in a prominent French textile company's manufacturing process. The production workflow is initially simulated and analyzed to identify key parameters influencing defect creation and detection. After assessing the existing control process using performance metrics, a novel Inspection Quality Plan (IQP) is formulated. To validate the effectiveness of the proposed IQP, a simulation model is developed and calibrated to mirror real-world conditions. This model, initially validated against the current solution, acts as a benchmark for evaluating predefined scenarios and determining optimal configurations. The implemented scenario, tested in the workshop under authentic conditions, results in a remarkable 42% improvement in defect detection within the knitting process. The positive outcomes are meticulously examined and discussed. This study, employing a holistic approach that integrates simulation modeling, performance evaluation, and real-world deployment, establishes an optimized strategy for enhancing defect detection in the textile industry. It underscores the effectiveness of the proposed IQP, showcasing significant improvements observed in practical settings based on a simulation model. [ABSTRACT FROM AUTHOR]

Freeform surfaces find potential applications in optics but pose new challenges for manufacturing and functional testing. A basic description of such surfaces is observed in terms of surface spatial frequencies which have been altered as a result of evolution in the fabrication of optics. While mid-spatial-frequency (MSF) errors arising from manufacturing and metrology processes are well documented, our investigation reveals that such errors originate not only during these stages but also during the surface construction at the design phase, particularly for high-order XY polynomial optical surfaces. The presence of MSF errors can significantly affect the performance of high-performance optical systems across various applications. The study discussed in this paper focuses on the relationship between the resolution of the design dataset of freeform surfaces with high-order polynomials and the subsequent surface imperfections in the production of precision optics. The main contributions of this investigation are the identification of MSF errors at surface construction of the design phase and the control over the MSF errors in design dataset using the 2nd-order Gaussian filtration which will bridge the gap between freeform optics design and ultra-precision manufacturing. [ABSTRACT FROM AUTHOR]

This work presents a measurement for the identification of translational quasi-static stiffness of machine tool using Stiffness Workspace System (SWS). The novelty of this work is a significant modification of the SWS. The changes in measurement procedure and data analysis as well as new technical solutions are described in detail. A methodology for generalised translational static stiffness determination is presented. The major purpose of this paper is to provide the information about quasi-static stiffness values that characterise a typical machine tool. The measurement procedure is implemented in a case study on a 5-axis machining centre. Measurement results were used to determine the generalised translational stiffness indicators of points in the workspace. Then, the static stiffness distribution on the XY plane over machining space was estimated. The obtained results confirm the importance of analyses of static stiffness distribution as they point out areas where some possible changes occur. In the conclusion of the paper the utility value of the information of translational static stiffness is emphasised. [ABSTRACT FROM AUTHOR]

Today, additive manufacturing (AM) is being utilized in a plethora of fields and applications. This study investigates two of the most commonly used AM technologies, fused filament fabrication (FFF) and stereolithography (SLA), under different part complexities and their effects to finished part quality. The process parameters investigated are infill density (ID), infill pattern (IP), and layer height (LH). The output variables observed are power consumption (PC), surface roughness (SR), and mass. Statistical analysis of experimental data indicates that LH is the most influential parameter for all output variables except mass. A validation study is later performed using three specimens with more diversely complex geometries. The model complexity is then evaluated and analyzed using three different ratios. Normalizing PC with respect to volume indicates a lower PC per unit volume for FFF. Experimental data also indicates SLA has a better surface finish and uses less power. This paper reports the state-of-the-art FFF and SLA process knowledge blocks created through this research study. [ABSTRACT FROM AUTHOR]

Industrial systems resources are capable of producing large amount of data. These data are often in heterogeneous formats and distributed, yet they provide means to mine the information which can allow the deployment of intelligent management tools for production activities. For this purpose, it is necessary to be able to implement knowledge extraction and prediction processes using Artificial Intelligence (AI) models, but the selection and configuration of intended AI models tend to be increasingly complex for a non-expert user. In this paper, we present an approach and a software platform that may allow industrial actors, who are usually not familiar with AI, to select and configure algorithms optimally adapted to their needs. Hence, the approach is essentially based on automated machine learning. The resulting platform effectively enables a better choice among the combination of AI algorithms and hyper-parameters configurations. It also makes it possible to provide features of explainability of the resulting algorithms and models, thus increasing the acceptability of these models in practicing community of the users. The proposed approach has been applied in the field of predictive maintenance. Current tests are based on the analysis of more than 360 databases from the subjected field. [ABSTRACT FROM AUTHOR]