Vers la maîtrise de la qualité des assemblages de précision

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The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

The construction industry plays a major role in the high levels of greenhouse gas emissions, resource consumption, and waste generation observed nowadays. Key to the circular economy, structural component reuse arises as a promising solution to divert cons ...

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

In droplet microfluidic devices with suction-based flow control, the microchannel geometry and suction pressure at the outlet govern the dynamic properties of the two phases that influence the droplet generation. Therefore, it is critical to understand the ...

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...

We study the problem of group testing with non-identical, independent priors. So far, the pooling strategies that have been proposed in the literature take the following approach: a hand-crafted test design along with a decoding strategy is proposed, and g ...

Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

This study applies Six-Sigma DMAIC methodology to enhance the efficiency of a manufacturing production line, specifically targeting the "gaps" between planned and actual working time. Key findings reveal that meetings, scanning, follow-up activities, walki ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

A significant project such as the FCC-ee (with 91.17 km circumference) entails numerous challenges to ensure the stability and performance of the machine. In the pursuit of contributing to the improvement of energy consumption during its operation, the exp ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

This book has been designed for instructors in higher education or adult training who wish to develop a new course or revise an existing one. It adopts a practical, visual, and modular approach based on the principle of constructive alignment. At its heart ...

Vers la maîtrise de la qualité des assemblages de précision

Chat with Graph Search

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

Extensions of Peer Prediction Incentive Mechanisms

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

RE:SLAB — a load bearing system for open-ended component reuse in building structures

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Modified capillary number to standardize droplet generation in suction-driven microfluidics

Oligolithic Cross-task Optimizations across Isolated Workloads

Dynamical simulation via quantum machine learning with provable generalization

Improving Group Testing via Gradient Descent

Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Optimizing Manufacturing Efficiency: A Six-Sigma DMAIC Approach to Reduce Operational Gaps

On distributional autoregression and iterated transportation

FIRST COMPARISON STUDIES IN DYNAMIC APERTURE FOR NESTED MAGNETS AND BASELINE LATTICE IN THE FCC-ee

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Stability: a search for structure

Course Design - A Visual and Modular Approach