Development of a cognitive supporting operator training environment
Paper in proceeding, 2014

In aggregate production and mining the operators are responsible for controlling and monitoring the process to maintain high plant throughput and safe operation. Operators have to make different decisions to control the process due to changed demand on the operation from both management and conditions of the process. The quality of the response and the time it takes for an operator to respond to altered demand relies on what information is available and the experience of the operator. In this work a dynamic simulation platform has been developed to be used for operator training. Models for representing production units and process control for plant simulations have been developed and implemented in MATLAB/SIMULINK to simulate time-dependent plant behavior. Stochastic and scheduled events are included using the discrete events simulation toolbox SimEvents. The human-machine interface was developed using the human-machine interface software ICONICS. The operators’ cognitive process, in interpreting the plants semantic, has been studied by observations and with informal interviews with operators. This was done to get information about the daily operation and the problems that occur in the process. By interacting with operators that experience different physical interactions with the process; more qualitative e-learning software for supporting operator training in a dynamic operator environment could be developed. The quality of the operator training environment was evaluated with a usability study that was performed with operators and others within the production.


Gauti Asbjörnsson

Chalmers, Product and Production Development, Product Development

Erik Hulthén

Chalmers, Product and Production Development, Product Development

Magnus Evertsson

Chalmers, Product and Production Development, Product Development

27th International Mineral Processing Congress, IMPC 2014, Santiago, Chile, 20-24 October 2014

Subject Categories

Production Engineering, Human Work Science and Ergonomics

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