Journal Information
Engineering Applications of Artificial Intelligence
Impact Factor:

Call For Papers
Artificial Intelligence (AI) techniques are now being used by the practicing engineer to solve a whole range of hitherto intractable problems. This journal provides an international forum for rapid publication of work describing the practical application of AI methods in all branches of engineering.

Focal points of the journal include, but are not limited to innovative applications of:

• Real-time intelligent automation, and their associated supporting methodologies and techniques, including control theory and industrial informatics,
• Architectures, algorithms and techniques for distributed AI systems, including multi-agent based control and holonic control,
• Decision-support systems,
• Aspects of reasoning: abductive, case-based, model-based, non-monotonic, incomplete, progressive and approximate reasoning,
• Applications of chaos theory and fractals,
• Metaheuristics and their applications in intelligent automation: Genetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, etc.,
• Knowledge processing, knowledge elicitation and acquisition, knowledge representation, knowledge compaction, knowledge bases, expert systems,
• Neural networks, fuzzy systems, neuro-fuzzy systems,
• Perception, e.g. image processing, pattern recognition, vision systems, tactile systems, speech recognition and synthesis,
• Aspects of software engineering, e.g. intelligent programming environments, verification and validation of AI-based software, software and hardware architectures for the real-time use of AI techniques, safety and reliability,
• Intelligent fault detection, fault analysis, diagnostics and monitoring,
• Self-organizing, emerging or bio-inspired system,
• Industrial experiences in the application of the above techniques, e.g. case studies or benchmarking exercises.

Engineering Applications of Artificial Intelligence publishes:
• Survey papers/tutorials.
• Contributed papers — detailed expositions of new research or applications.
• Case studies or software reviews — evaluative and descriptive reviews of existing available AI software systems, discussing the experience gained and lessons learnt from using or developing AI systems for engineering applications.
• IFAC EAAI Forum — problems arising from engineering practice, needing to be solved by somebody; solutions to problems discussed in this forum or elsewhere; critiques of a position or claim found in the literature. 
Last updated by Xin Yao in 2017-08-21
Special Issues
Special Issue on Industry 4.0
Submission Date: 2017-09-10

Industry 4.0 or the fourth industrial revolution, is a collective term embracing some contemporary automation, data exchange, and manufacturing technologies. Industry 4.0 is also referred as Industrial Internet, Smart Factory, Cyber-Physical Production Systems (CPPS) or Advanced Manufacturing, but the meaning is mostly the same. It is defined as a collective term for technologies and concepts of value chain organizations which bring together Cyber-Physical Systems, the Internet of Services and the Internet of Things. Respect the unlimited possibilities of having billions of people connected by mobile devices, giving rise to novel processing power, storage capacities, and knowledge access. Alternatively, think about the staggering confluence of emerging technology breakthroughs, covering wide-ranging fields such as artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3D printing, nanotechnology, materials science and energy storage, to name a few. Many of these innovations are in their infancy, but they are already approaching an inflection point in their development as they build on and augment each other in a fusion of technologies across the physical, digital and biological worlds. This special issue emphasizes on Industry 4.0 and its real world applications. Some of the topics covered are listed below: 1. Big Data and Analytics Analytics based on large data sets has appeared in the manufacturing world, where it optimizes production quality, saves energy, and improves equipment service. In an Industry 4.0 context, the collection and comprehensive evaluation of data from many different sources production equipment and systems as well as an enterprise and customer management systems. 2. Autonomous Robots Companies in many industries have long used robots to launch complex tasks, but robots are evolving for even greater utility. They are becoming more autonomous, flexible, and cooperative. Eventually, they interact with one another and work safely side by side with humans and learn from them. 3. Simulation In the engineering phase, 3-D simulations of products, materials, and production processes are already used, but in the future, simulations will be used more extensively in plant operations as well. These simulations will leverage real-time data to mirror the physical world in a virtual model, which can include machines, products, and humans. This allows operators to test and optimize the machine settings for the next product in line in the virtual world before the physical changeover, thereby driving down machine setup times and increasing quality. 4. Internet of Things The Internet of Things and the Internet of Services in the manufacturing process has initiated Industry 4.0. However, with the industrial Internet of Things, more devices are enriched with embedded computing and connected using standard technologies. This allows field devices to communicate and interact both with one another and with more centralized controllers, as necessary. It also decentralizes analytics and decision making, enabling real-time responses. 5. Cybersecurity The raised connectivity and use of standard communications protocols that come with Industry 4.0, the need to protect critical industrial systems and manufacturing lines from cybersecurity threats increase dramatically. As a result, secure, reliable communications, as well as sophisticated identity and access management of machines and users, are essential. 6. Additive Manufacturing Additive manufacturing as the industrial version of 3-D printing is already used to make some niche items, such as medical implants, and to produce plastic prototypes for engineers and designers. With Industry 4.0, these additive manufacturing methods will be widely used to produce small batches of customized products that offer construction advantages, such as complex, lightweight designs. High-performance, decentralized additive manufacturing systems will reduce transport distances and stock on hand. 7. Assistance Systems Technologies that support employees at work and help them focus on their core tasks e.g. smartphone, tablet, smart glasses. These systems are currently in their infancy, but in the future, companies will make much broader use of augmented reality to provide workers with real-time information to improve decision making and work procedures.
Last updated by Dou Sun in 2017-08-05
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