"Big Data Analysis in Smart Manufacturing: A Review"
written by Kevin Nagorny, Pedro Lima-Monteiro, Jose Barata, Armando Walter Colombo,
published by International Journal of Communications, Network and System Sciences, Vol.10 No.3, 2017
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] The Influence of Smart Manufacturing Towards Energy Conservation: A Review
2020
[2] First Time Quality Diagnostics and Improvement through Data Analysis: A Study of a Crankshaft Line
2020
[3] Integration of data analytics with cloud services for safer process systems, application examples and implementation challenges
2020
[4] A Deep Learning-Based Model for the Automated Assessment of the Activity of a Single Worker
2020
[5] A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future
2020
[6] Intelligent Maintenance Systems and Predictive Manufacturing
2020
[7] Human behavior understanding for worker-centered intelligent manufacturing
2020
[8] Recognizing the Necessity for Developing Customer-Oriented New Products for the 4th Industrial Revolution
2020
[9] Discussing Relations Between Dynamic Business Environments and Big Data Analytics
2020
[10] Machine Learning and Data Mining in Manufacturing
2020
[11] A Systematic Review of Big Data Analytics for Oil and Gas Industry 4.0
2020
[12] Requirements for Big Data Adoption for Railway Asset Management
2020
[13] Manufacturing big data ecosystem: A systematic literature review
2020
[14] 4 차 산업혁명 시대를 대비한 고객 중심의 신제품 개발 필요성 인식 제고
2020
[15] Exploring the Specificities and Challenges of Testing Big Data Systems
2019
[16] Recommendation Framework for on-Demand Smart Product Customization.
2019
[17] Investigation of Fusion Features for Apple Classification in Smart Manufacturing
2019
[18] Smart manufacturing systems: state of the art and future trends
2019
[19] An FCM–GABPN Ensemble Approach for Material Feeding Prediction of Printed Circuit Board Template
2019
[20] Cognitive IoT for Smart Environment: A survey on Enabling Technologies, Architectures, Approaches and Research Challenges
International Journal of Electronics Engineering, 2019
[21] Multi-modal recognition of worker activity for human-centered intelligent manufacturing
2019
[22] A framework to help decision makers to be environmentally aware during the maintenance of cyber physical systems
2019
[23] A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: a framework, challenges and future research …
2019
[24] Recommendation Framework for on-Demand Smart Product Customization
2019
[25] State and Trends of Machine Learning Approaches in Business: An Empirical Review
2019
[26] Transformation towards smart factory system: Examining new job profiles and competencies
2019
[27] Smart factory: A methodology for adaptation
2019
[28] Finding The Four Qualities Of Intelligent Industrial Reporting
2019
[29] 驱动制造业从 “互联网+” 走向 “人工智能+” 的大数据之道
2019
[30] Building a Simple Smart Factory
2019
[31] A Process-oriented Backend for Data-driven Production Planning and Control
2018
[32] Comparison of Machine Learning Approaches for Time-series-based Quality Monitoring of Resistance Spot Welding (RSW)
2018
[33] When Smart Gets Smarter: How Big Data Analytics Creates Business Value in Smart Manufacturing
2018
[34] Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production
Journal of Electrical and Computer Engineering, 2018
[35] Big Data: Concept, Potentialities and Vulnerabilities
2018
[36] Semantical support for a CPS data marketplace to prepare Big Data analytics in smart manufacturing environments
2018
[37] Knowledge integration via the fusion of the data models used in automotive production systems
Enterprise Information Systems, 2018
[38] Worker Activity Recognition in Smart Manufacturing Using IMU and sEMG Signals with Convolutional Neural Networks
Procedia Manufacturing, 2018
[39] Innovation and entrepreneurship guidance system based on clustering algorithm
Cluster Computing, 2018
[40] A Survey on the Concepts, Trends, Enabling Technologies, Architectures, Challenges and Open Issues in Cognitive IoT Based Smart Environments
2018
[41] A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry
Applied Sciences, 2018
[42] Tools, Technologies, and Methodologies to Support Data Science: Support Technologies for Data Science