Innovations for Interpretability, Flexibility, and Sustainability in Intelligent Machinery and Industry 4.0-Reference-Cited by-同舟云学术

Innovations for Interpretability, Flexibility, and Sustainability in Intelligent Machinery and Industry 4.0

Published:2023-04-23 Issue:9 Volume:13 Page:5257
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Trappey Amy J. C.¹^ORCID,Lee Ching-Hung²^ORCID,Mo John P. T.³^ORCID

Affiliation:

1. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 300044, Taiwan

2. School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China

3. School of Engineering, RMIT University, Melbourne, VIC 3000, Australia

Abstract

Three levels, namely the device level, the connection level, and the systems management level, are frequently used to conceptualize intelligent machinery and Industry 4 [...]

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

https://www.mdpi.com/2076-3417/13/9/5257/pdf

Reference11 articles.

1. Chiang, T., Che, Z., Lee, C., and Liang, W. (2021). Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules. Appl. Sci., 11.

2. Yiu, C., Ng, K., Lee, C., Chow, C., Chan, T., Li, K., and Wong, K. (2021). A Digital Twin-Based Platform towards Intelligent Automation with Virtual Counterparts of Flight and Air Traffic Control Operations. Appl. Sci., 11.

3. De Paepe, D., Vanden Hautte, S., Steenwinckel, B., Moens, P., Vaneessen, J., Vandekerckhove, S., Volckaert, B., Ongenae, F., and Van Hoecke, S. (2021). A Complete Software Stack for IoT Time-Series Analysis that Combines Semantics and Machine Learning—Lessons Learned from the Dyversify Project. Appl. Sci., 11.

4. Lee, T., Chang, L., and Chan, Y. (2022). An Intelligent Handover Mechanism Based on MOS Predictions for Real-Time Video Conference Services in Mobile Networks. Appl. Sci., 12.

5. Varna, D., and Abromavičius, V. (2022). A System for a Real-Time Electronic Component Detection and Classification on a Conveyor Belt. Appl. Sci., 12.

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