Micromanufacturing processes are complex physical processes which are continuously changing in a dynamic environment. In this context the main objective is the development of computational technologies and algorithms in order to enable faster, self-organized, self-optimized behavior of micromanufacturing processes by means of intelligent control systems.
This work is supported by the national research project DPI2012-35504: Artificial Cognitive Control System for Micromanufacturing Processes. Method and Application (CONMICRO) led by Prof. Rodolfo Haber. This project will provide the necessary umbrella to carry out the required tasks during this period.
Accordingly to our framework this work is focused on the four main pillars of the CONMICRO project. Obviously, for the sake of time constraints, it will focus on three of them. Thereby, the general objectives of this work are:
- To design an artificial cognitive architecture for controlling physical processes based on the results of the COGNETCON project. This architecture will be based on the shared circuits model of sociocognitive capacities. It is important to notice this architecture will be designed regarding the principles of simplicity and scalability.
- To implement the designed artificial cognitive architecture for controlling physical processes. This implementation will be done in Java. The implementation has also to take into account simplicity and scalability principles as its main issue.
- To validate the design and implementation of the artificial cognitive architecture in both simulation and a real scenario. Due to the importance of the machine in the real scenario it is essential that the application matches perfectly with the simulation study.
- To acquire new knowledge and developing skills in different fields and topics of the real world mainly: working with proprietary software and programming languages, for instance Labview; using middleware for enable communication between different machines such ZeroC Ice; the design and implementation of the artificial cognitive architecture, to learn about modeling and control in real time of physical process.
DPI2012-35504