Zhiqiang Wang

Zhiqiang Wang
Leonardo da Vinci Engineering School | ESILV · Faculty of Mechanical Engineering

Doctor of Engineering
Associate professor in Ecole Supérieur d'Ingénieur Léonard De-Vinci. Domaine: Smart manufacturing, Industrie 4.0

About

14
Publications
3,008
Reads
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200
Citations
Introduction
Zhiqiang Wang currently works at Ecole Supérieur d'Ingénieurs Léonard de Vinci as an associate professor. His research domain are Smart manufacturing, Machine Learning, Deep learning, Digital twin and Machining.
Education
September 2017 - December 2020
Nantes Université
Field of study
  • Decision-aid in machining based on business rules and unsupervised machine learning
September 2009 - March 2012
École nationale supérieure d'arts et métiers
Field of study
  • Mechanical Engineering, Machining, Fluid mechanics
September 2005 - July 2009
Shanghai Jiao Tong University
Field of study
  • Mechanical Engineering

Publications

Publications (14)
Article
Full-text available
Fault analysis (FA) is the process of collecting and analyzing data to determine the cause of a failure. It plays an important role in ensuring the quality in manufacturing process. Traditional FA techniques are time-consuming and labor-intensive, relying heavily on human expertise and the availability of failure inspection equipment. In semiconduc...
Conference Paper
Full-text available
In the context of Industry 4.0, large volumes of manufacturing data are available on instrumented machine-tool. The critical point is the exploitation of this digital content. Data contextualization is important for efficient and robust data mining, particularly for industrial production. For this purpose, a classification method of the operational...
Conference Paper
Full-text available
In the semiconductor industry, Failure Analysis (FA) is an investigation to determine the root causes of a failure. It also involves an intermediate analysis to build the steps of the failure analysis in order to mitigate future failures and to facilitate the future FA. In the framework of the FA 4.0 project, the reporting system records three item...
Conference Paper
Full-text available
Les machines-outils intelligentes gérèrent de nombreuses données et l'exploration de ces données peut faciliter la prise de décision en matière de gestion opérationnelle. Une sélection fine des données pertinentes, basée sur le contexte d'usinage, est nécessaire pour un calcul précis des indicateurs clés de performance (KPIs). Il s'agit d'une étape...
Thesis
Full-text available
In the general context of Industry 4.0, large volumes of manufacturing data are available on instrumented machine-tools. They are interesting to exploit not only to improve machine-tool performances but also to support the decision making for the operational management. This thesis aims at proposing a decision-aid system for intelligent and connect...
Article
Full-text available
This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the DS to enable the...
Article
Full-text available
Intelligent machine-tools generate a large amount of digital data. Data mining can support decision making for operational management. The first step in a data mining approach is the selection of relevant data. Raw data must, therefore, be classified into different groups of contexts. This paper proposes a contextual classification pro- cedure in m...
Conference Paper
Full-text available
Dans le contexte général de l'Industrie 4.0, une entreprise de fabrication moderne dispose de nombreuses données numériques qui pourraient être utilisées pour rendre les machines-outils plus intelligentes et faciliter la prise de décision en matière de gestion opérationnelle. L'une des premières étapes de l'approche d'exploration de données est la...
Conference Paper
Full-text available
Dans le contexte général de l'Industrie 4.0, une entreprise de fabrication moderne dispose de nombreuses données numériques qui pourraient être utilisées pour rendre les machines-outils plus intelligentes et faciliter la prise de décision en matière de gestion opérationnelle. L'une des premières étapes de l'approche d'exploration de données est la...
Article
Full-text available
High speed machining (HSM) is widely used for the manufacturing of aircraft structures, turbine blades, etc. It greatly increases the efficiency and automation for the machining. However, in HSM, operators cannot detect incidents when they manage several machines of a production cell. Robust monitoring systems are required to protect the machine to...
Conference Paper
Full-text available
High speed machining (HSM) is widely used for the manufacturing of aircraft structures, turbine blades, etc. It greatly increases the efficiency and automation for the machining. However, in HSM, operators cannot detect incidents when they manage several machines of a production cell. Robust monitoring systems are required to protect the machine to...
Article
Full-text available
Reproducible operation at high performances of superconducting cavities is required for linear accelerators. High beta elliptical cavities are thus of concern and, to achieve required performances for such resonators, surface preparation including electropolishing is recommended. We have designed and operate a setup for electropolishing in the vert...

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