Bikash Koli Dey,Hyesung Seok
Bikash Koli Dey
The manufacturer's service to the customer is one of the critical factors in maximizing profit. This study proposes the innovative (Q, r) inventory policy integrated with autonomated inspection and service strategy for service-dependent dem...
Foreign objects detection using deep learning techniques for graphic card assembly line [0.03%]
基于深度学习的图形卡装配线 foreign object debris 检测方法研究
R J Kuo,Faisal Fuad Nursyahid
R J Kuo
An assembly is a process in which operators and machines manufacture products from semi-finished components into finished goods. It is important to conduct quality control at the end of the assembly line and ensure that no foreign object is...
Digital Twin and web services for robotic deburring in intelligent manufacturing [0.03%]
智能製造中的數字孪生與網格服務在機器人去毛刺中應用
Liliana Stan,Adrian Florin Nicolescu,Cristina Pupăză et al.
Liliana Stan et al.
The development of modern manufacturing requires key solutions to enhance the intelligence of manufacturing such as digitalization, real-time monitoring, or simulation techniques. For smart robotic manufacturing, the modern approach regardi...
A novel disassembly process of end-of-life lithium-ion batteries enhanced by online sensing and machine learning techniques [0.03%]
基于在线监测与机器学习的废旧锂离子电池新型拆解方法研究
Yingqi Lu,Maede Maftouni,Tairan Yang et al.
Yingqi Lu et al.
An effective lithium-ion battery (LIB) recycling infrastructure is of great importance to alleviate the concerns over the disposal of waste LIBs and the sustainability of critical elements for producing LIB components. The End-of-life (EOL)...
Multi-objective optimisation of ultrasonically welded dissimilar joints through machine learning [0.03%]
基于机器学习的超声焊接异种接头多目标优化
Patrick G Mongan,Vedant Modi,John W McLaughlin et al.
Patrick G Mongan et al.
The use of composite materials is increasing in industry sectors such as renewable energy generation and storage, transport (including automotive, aerospace and agri-machinery) and construction. This is a result of the various advantages of...
Machine learning to determine the main factors affecting creep rates in laser powder bed fusion [0.03%]
用于确定激光粉末床熔融中影响蠕变率的主要因素的机器学习方法
Salomé Sanchez,Divish Rengasamy,Christopher J Hyde et al.
Salomé Sanchez et al.
There is an increasing need for the use of additive manufacturing (AM) to produce improved critical application engineering components. However, the materials manufactured using AM perform well below their traditionally manufactured counter...
Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective [0.03%]
网络制造建模与分析的挑战：从机器学习和计算的角度看综述研究
SungKu Kang,Ran Jin,Xinwei Deng et al.
SungKu Kang et al.
In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing, founded upon advanced communication, computation, and control infrastructure. Cybermanufacturing will unleash the potential of multi-modal manufacturing data...
Slim Zidi,Nadia Hamani,Lyes Kermad
Slim Zidi
The COVID 19 pandemic, fluctuating demand, market uncertainty and the emergence of new technologies explain the need for a more flexible and agile supply chain. In fact, several important factors should be taken into account in the process ...
Human-centred design in industry 4.0: case study review and opportunities for future research [0.03%]
以人为中心的设计在工业4.0中的应用：案例研究与未来研究机会
Hien Nguyen Ngoc,Ganix Lasa,Ion Iriarte
Hien Nguyen Ngoc
The transition to industry 4.0 has impacted factories, but it also affects the entire value chain. In this sense, human-centred factors play a core role in transitioning to sustainable manufacturing processes and consumption. The awareness ...
Reza Vatankhah Barenji
Reza Vatankhah Barenji
Cloud manufacturing (CM) is a new networked manufacturing model that delivers various on-demand manufacturing capabilities to the consumers from the providers. In this model, the provider and consumer never meet each other, thus "trust" is ...