Taking Tacit Knowledge into Account by Using Problem Cases as Guidelines in HMI Development
IMPROVE is aiming for developing a more efficient way of providing plant field maintenance in highly complex industrial facilities. Therefore, knowledge based models and devices for data mining and processing are to be created in order to support the facility’s maintenance operators who keep the system running in a good condition. To achieve this goal two kinds of simulation are going to be developed, on the one side a simulation grounded on a model of the plant working without any disruption and under ideal conditions, and on the other side a simulation grounded on the actual empirical data of the production line and its specific environment. Furthermore, these two simulations, or rather the futures these simulations are predicting, are constantly and simultaneously compared so that critical disturbances which are going to happen within the next hours, days, or even longer termed intervals can be detected before breakdown. Hence, a facility supported by such a maintenance system will change the way of remediating generally and thereby raise the economic efficiency significantly
My task in this context contains two challenges. Firstly, I generally observe and analyse the socio-technical development of this new maintenance system ethnographically by using ethnomethodological field observation, document or rather code/model analysis, and potentially also interviews. Thereby, I am going to investigate the organizational, social, cultural, and engineering processes involved in this project. Secondly, I support that part of IMPROVE which is engaged with the development of the HMI (human machine interface). This task requires certain socio-scientific experience and proficiencies respective the alleged use cases, user experiences, and expectable human erroneous behaviors.
Interestingly, the development of the HMI requires models and specific data in advance being conceivable by common human cognition capacities. This is a great opportunity to not only observe ethnographically the discursive production of what good data and models are but also to get the chance to have some especially emic insight. Thus, the HMI development can be constructively reflected without neglecting its afore prerequisites of modeling and simulation so that the HMI design will eventually benefit.
