State-of-the-Art Intelligent Systems Integration in Engineering

Dear Colleagues,

Engineered systems execute two, function types: cognitive and physical. For thousands of years, humans did both. The first and second Industrial Revolutions (IR) produced new kinds of machines that could perform formerly human-based, physical functions automatically. But it wasn’t the third IR when completely new machines, called computers, began to automate cognitive functions. Automation required physics-based models, software applications to run those models, and digital data that provide the necessary inputs.  

As the third IR was winding down, the models, applications, and inputs became more sophisticated and more complicated. The physical automation machines had more capabilities; and, the available cognitive automation, and other information technologies, exploded on the market.  But the data needed to use them included only numbers and text. That all changed at the beginning the fourth IR, which is based on new types of data and technologies to collect and process that data. Those technologies include image-based sensors, cloud services, cloud computing, data analytics, and artificial intelligence. These technologies are changing the way we design and control engineered systems. They are automating many more of the cognitive functions associated with those systems. And they are interacting across multiple time scales with new, automated, domain-specific, physical technologies, such as Additive Manufacturing.

This special issue focuses on the state-of-the-art, from both the academic and industrial perspectives, in cognitive automation and hybrid modeling, formerly called integration. These are very timely topic for both researchers, who are developing the science behind them; and, users, who are trying to implement and integrate them into their systems. Topics of interest related to cognitive automation include visualization, human roles, V&V, training and trustworthy AI.  Topics in hybrid modeling include verification and validation, data fusion, model composition, and data/model integration, uncertainly propagation, and mathematical foundations for all both.

Dr. Albert T. Jones
Guest Editor

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• cognitive automation
• verification
• validation
• industry 4.0
• physics-based models
• data-driven models
• fusion
• composition
• human operators