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This paper aims to describe a new methodology for controlling highly flexible automated manufacturing cells for use in aerospace manufacturing and repair.

The design methodology and rational of the FLEXA control architecture are described along with it implementation and testing.

The trials completed so far show that the level of flexibility required can be achieved both at factory, or enterprise level, and at shop floor level.

This work has significant practical implications through its direct applicability for aerospace and other automated manufacturing processes.

The originality of the paper lies in the truly flexible nature of the control system described and its ability to mimic traditional cell control architectures but be expanded through the use of virtual Programmable Logic Controller to control any number of cells without the need for significant extra hardware.

The purpose of this paper is to describe the integration of a gesture control system for industrial collaborative robot. Human and robot collaborative systems can be a viable manufacturing solution, but efficient control and communication are required for operations to be carried out effectively and safely.

The integrated system consists of facial recognition, static pose recognition and dynamic hand motion tracking. Each sub-system has been tested in isolation before integration and demonstration of a sample task.

It is demonstrated that the combination of multiple gesture control methods can increase its potential applications for industrial robots.

The novelty of the system is the combination of a dual gesture controls method which allows operators to command an industrial robot by posing hand gestures as well as control the robot motion by moving one of their hands in front of the sensor. A facial verification system is integrated to improve the robustness, reliability and security of the control system which also allows assignment of permission levels to different users.