Catégorie
Management de la qualité
Publications associées (958)
Optimizing Manufacturing Efficiency: A Six-Sigma DMAIC Approach to Reduce Operational Gaps
Jérôme Chenal, Baraka Jean-Claude Munyaka
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 ...
2024Extensions of Peer Prediction Incentive Mechanisms
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 ...
EPFL2024Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks
Romain Christophe Rémy Fleury, Janez Rus
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 ...
2024Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution
Tobias Kippenberg, Alberto Beccari, Nils Johan Engelsen
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 ...
Berlin2024Stability: a search for structure
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 ...
EPFL2024Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties
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 ...
EPFL2024A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings
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 ...
Pergamon-Elsevier Science Ltd2024Data-driven statistical optimization of a groundwater monitoring network
Andrea Rinaldo, Gianluca Botter
We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...
Elsevier2024Room-temperature quantum optomechanics using an ultralow noise cavity
Tobias Kippenberg, Guanhao Huang, Alberto Beccari, Nils Johan Engelsen
At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...
Berlin2024Mechanically induced correlated errors on superconducting qubits with relaxation times exceeding 0.4 ms
Tobias Kippenberg, Amir Youssefi, Marco Scigliuzzo, Mahdi Chegnizadeh, Shingo Kono, Xuxin Wang
Superconducting qubits are among the most advanced candidates for achieving fault-tolerant quantum computing. Despite recent significant advancements in the qubit lifetimes, the origin of the loss mechanism for state-of-the-art qubits is still subject to i ...
Nature Portfolio2024