PROJECT TITLE: Deep Machine Learning and Swarm Intelligence-based Optimization Algorithms for Control and Scheduling of Cyber-Physical Systems in Industry 4.0
ACRONYM: MISSION 4.0
PI: Dr Zoran Miljković, full professor, Faculty of Mechanical Engineering, University of Belgrade
SRO’s: Faculty of Mechanical Engineering, University of Belgrade; Faculty of Philosophy, University of Belgrade
The project team will implement novel interdisciplinary approaches in the following scientific research directions: optimization of dynamic integrated process planning and scheduling (DIPPS); intelligent vision-based machine control of mobile robots, as well as deep machine learning of cybersecurity systems during secure communication in Industry 4.0.
The strategic goal of the MISSION4.0 project implies the impact and implementation of the original methodology based on artificial intelligence techniques, along with the development and application of ethical principles in cognitive robotics from a sociological aspect, in production systems which will apply achievable principles of Industry 4.0 in Serbia and influence global development in the domain of 4th industrial revolution (Industry 4.0 ) through project results which will be published and presented to the international public in accordance with the approach oriented towards open science.
Thanks to this project, a large number of scientific papers will be published in the country and abroad, and the results will be announced at prestigious conferences. The MISSION4.0 project aims at achieving adaptable, reconfigurable and intelligent Cyber-Physical Production Systems for Industry 4.0, which is actually a strategically oriented direction of development of production technologies in today’s economy of the Republic of Serbia.
PROJECT OBJECTIVE: The objective is to integrate artificial intelligence techniques for deep machine learning and biologically inspired multicriteria optimizations, in order to achieve cyber-physical production systems.
METHODOLOGY: Algorithms for biologically inspired optimization techniques will be developed, as well as an original method for intelligent navigation of a mobile robot based on stereo vision autonomous machine control.
EXPECTED RESULTS: In addition to scientific papers, technical solutions in the field of cognitive mobile robotics and response to cyber-attacks will be realized, as well as original algorithms for optimal use, planning and scheduling of production resources.
Illustration: Aleksandra Jovanic