Special Issue on Data-Driven Collaborative Engineering (EVISE Article Type: “Data-Driven Collab Eng”)
摘要截稿:
全文截稿: 2019-10-31
影响因子: 3.879
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 计算机:人工智能 - 2区
• 小类 : 工程:综合 - 1区
Overview
Collaborative Engineering (CE) involves the research and development of collaboration technologies and their applications to the design of processes, products, systems, and services in industries and societies with objectives for better product quality, shorter lead-time, more competitive cost and higher customer satisfaction. Collaboration technologies include theories, methods, mechanisms, protocols, software tools, platforms, and services that support communication, coordination and collaboration among people, software and hardware systems. New generation of ICT technologies, including Cloud/Fog/Edge computing, Internet of Things (IoT), Big Data and Artificial Intelligence/Deep Learning, can substantially expand the frontiers of what is possible in the CE area.
Data is the new oil. In the real-world, the pervasive sensing ability of IoT systems gives rise to the generation of huge and diverse volumes of data, which can be utilized to assist optimal decision-making for collaboration technologies and their applications. The data sets are still growing rapidly because the density of sensing and actuation coverage is still at early stages of development and much more IoT devices will be deployed. Cloud/Fog/Edge computing provides different but complementary paradigms for data storage, integration and processing. Big Data and Artificial Intelligence/Deep Learning enable the efficient data analytics for useful information, insights and knowledge. With the help of ICT, physical objects are virtualized and represented as twin models (Avatars) seamlessly and closely integrated in both the physical and cyber spaces. The simulation systems which comprise twin models and other digital models will operate as an essential part of the corresponding physical system to assist decision-making, training, etc. As a result, what has been described as a data-driven revolution has reshaped both CE and scientific landscapes.
Specific topics of interest include, but are not limited to the following:
Collaboration theory, ontology and methodology
Architecture, interoperability and standard for CE
Emerging sensing technologies of IoT for CE
IoT-enabled collaborative process monitoring and control
Resource composition and reliable networked application
Cloud based collaborative Big Data and Artificial Intelligence
Human-centered pervasive CE environment
Augmented reality and wearable computing for CE
Collective design and social manufacturing in CE
Cybersecurity and privacy for CE systems
Cyber physical production systems and industry 4.0