Blar i NTNU Open på forfatter "Wang, Kesheng"
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A data-driven method based on deep belief networks for backlash error prediction in machining centers
Li, Zhe; Wang, Yi; Wang, Kesheng (Journal article; Peer reviewed, 2017)Backlash error occurs in a machining center may lead to a series of changes in the geometry of the components and subsequently deteriorate the overall performance of the equipment. Due to the uncertainty of mechanical wear ... -
A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment
Li, Zhe; Li, Jingyue; Wang, Yi; Wang, Kesheng (Journal article; Peer reviewed, 2019)Anomaly in mechanical systems may cause equipment to break down with serious safety, environment, and economic impact. Since many mechanical equipment usually operates under tough working environments, which makes them ... -
An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many-Objective Optimization
Wang, Chen; Wang, Yi; Wang, Kesheng; Dong, Yao; Yang, Yang (Journal article; Peer reviewed, 2017)It is extremely important to maintain balance between convergence and diversity for many-objective evolutionary algorithms. Usually, original BBO algorithm can guarantee convergence to the optimal solution given enough ... -
Application of Machine Learning Methods to Improve Dimensional Accuracy in Additive Manufacturing
Baturynska, Ivanna; Semeniuta, Oleksandr; Wang, Kesheng (Chapter, 2019)Adoption of additive manufacturing for producing end-use products faces a range of limitations. For instance, quality of AM-fabricated parts varies from run to run and from machine to machine. There is also a lack of ... -
Automatic detection of false positive RFID readings using machine learning algorithms
Ma, Haishu; Wang, Yi; Wang, Kesheng (Peer reviewed; Journal article, 2018)Radio frequency identification (RFID) has been widely used for the automatic identification, tracking and tracing of goods throughout the supply chain from the manufacturer to the customer. However, one technological problem ... -
Collaborative Fault Diagnosis Decision Fusion Algorithm Based on Improved DS Evidence Theory
Gao, Xiue; Chen, Bo; Chen, Shifeng; Wang, Kesheng; Wang, Yi; Xie, Wenxue; Yuan, Jin; Martinsen, Kristian; Ghosh, Tamal (Chapter, 2020)DS evidence theory has in obtaining a correct diagnosis when confronted with highly conflicting evidence, a collaborative fault diagnosis decision fusion algorithm based on an improved version of DS evidence theory is ... -
Data Mining for Intelligent Green Monitoring of Machine Centers - Backlash Error Analysis for Condition Monitoring
Braaten, Jørgen (Master thesis, 2015)The European Union has pledged to limit climate change by reducing energy consumption and the manufacturing industry is among the biggest energy consumer in Europe. A project named Intelligent Green Monitoring (IGM) is ... -
Deep Learning Driven Approaches for Predictive Maintenance: A Framework of Intelligent Fault Diagnosis and Prognosis in the Industry 4.0 Era
Li, Zhe (Doctoral theses at NTNU;2018:132, Doctoral thesis, 2018) -
A design approach to integrated intelligent systems in a manufacturing environment
Paramsothy, Jeyakumar (Doktor ingeniøravhandling 1995:112, Doctoral thesis, 1995) -
Framework for Discussing Sustainability Improvement in Container Ports – a Nordic Case Study
Hakam, Moulay Hicham (Doctoral thesis at NTNU;2016:178, Doctoral thesis, 2016)This PhD research project proposes a five-construct framework for discussing how to improve the sustainability performance in Nordic container ports (NCPs). The port of Narvik is used as a representative case study whenever ... -
Functionally Graded Materials for Highly Stressed Components
Huo, Jingming (Doctoral theses at NTNU;2017:188, Doctoral thesis, 2017)The present work deals with representation, design, analysis and fabrication of Functionally Graded Materials (FGMs). First, a general overview on FGMs is described. A new and precious definition has been made. Structures, ... -
HDPS-BPSO Based Predictive Maintenance Scheduling for Backlash Error Compensation in a Machining Center
Li, Zhe; Wang, Yi; Wang, Kesheng; Li, Jingyue (LNEE;volume 484, Journal article; Peer reviewed, 2018)This paper presents a novel HDPS-BPSO maintenance scheduling strategy for backlash error compensation in a machining center through binary particle swarm optimization (BPSO) and data-driven regression methods. During the ... -
Industry 4.0 - Potentials for Predictive Maintenance
Li, Zhe; Wang, Kesheng; He, Yafei (Advances in Economics, Business and Management Research;, Chapter, 2016)Abstract: Industry 4.0 represents the coming fourth industrial revolution on the way to combine modern industries with Cyber-Physical Systems, Internet of Things and Internet of Services. In an Industry 4.0 factory, machines ... -
Intelligent predictive maintenance for fault diagnosis and prognosis in machine centers: Industry 4.0 scenario
Li, Zhe; Wang, Yi; Wang, Kesheng (Journal article; Peer reviewed, 2017)Fault diagnosis and prognosis in mechanical systems have been researched and developed in the last few decades at a very rapid rate. However, owing to the high complexity of machine centers, research on improving the ... -
Interpretation and compensation of backlash error data in machine centers for intelligent predictive maintenance using ANNs
Wang, Kesheng; Li, Zhe; Braaten, Jørgen; Yu, Quan (Journal article; Peer reviewed, 2015)It is especially significant for a manufacturing company to select a proper maintenance policy because maintenance impacts not only on economy, reliability and availability but also on personnel safety. This article reports ... -
Logistics 4.0 Technologies Driven Approaches for Warehouse Operations: A Framework of Resource Management System
Ma, Haishu (Doctoral theses at NTNU;2017:267, Doctoral thesis, 2017)The last several years have seen the evolution of warehouse from stockpiling of inventory to high-velocity operations, allowing facilities to handle as many goods as they typically deal with, but at lower costs. Warehouses ... -
Models for lifetime estimation: an overview with focus on applications to wind turbines
Welte, Thomas Michael; Wang, Kesheng (Journal article; Peer reviewed, 2014)This paper provides an overview of models and methods for estimation of lifetime of technical components. Although the focus in this paper is on wind turbine applications, the major content of the paper is of general nature. ... -
A New Fault Identification Method Based on Combined Reconstruction Contribution Plot and Structured Residual
Chen, Bo; Wang, Kesheng; Gao, Xiue; Wang, Yi; Chen, Shifeng; Zhang, Tianshu; Martinsen, Kristian; Ghosh, Tamal (Chapter, 2020)The existing contribution plot-based reconstruction fault identification methods suffer from low identification accuracy and serious trailing effect. In this paper, a new fault identification method is proposed based on a ... -
A Surrogate-Assisted Optimization Approach for Multi-Response End Milling of Aluminium Alloy AA3105
Ghosh, Tamal; Yi, Wang; Martinsen, Kristian; Wang, Kesheng (Peer reviewed; Journal article, 2020)Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are ... -
The Challenges of Logistics 4.0 for the Supply Chain Management and the Information Technology
Domingo Galindo, Laura (Master thesis, 2016)Internet has changed our life. It has brought a new way of communication, transferring information and making businesses. The term already known as Internet of things , provides the idea of the digital connection between ...