Supporting the learning at work of automation engineers in the adoption of new technologies
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Automation engineering is an engineering discipline the objective of which is to design and implement automated functioning of industrial processes and machines. The output of automation engineering is an autonomously performing system that is controlled by an automation system. Making production processes more flexible and safe is a current trend in the industry. This increases the complexity of the processes and machines, and requires adaptability from the automation systems. Thus, also new kinds of competences, knowledge as well as work practices are expected from automation engineers who design automation systems. The focus in this thesis is on automation engineers’ learning at work and how this learning process can be supported with computer-assisted technologies. Engineers’ learning process is based on the knowledge of the automation engineers’ core task which is investigated with the help of the Core-Task Analysis method (Norros 2004). The core task of automation engineering work is refined with the ideas of the process model of learning at work introduced by Järvinen and Poikela (Järvinen & Poikela 2001). The model combines three well-known learning theories: individual’s experiential learning introduced by Kolb (Kolb 1984), the theory of the knowledge creating company introduced by Nonaka and Takeuchi (Nonaka & Takeuchi 1995), and finally the 4I organizational learning framework introduced by Crossan, Lane, and White (Crossan et al. 1999). In this study the focus is on the levels of individuals’ and teams’ learning at work. Research material was collected with two methods: semi-structured theme interviews and workshops. All together 18 automation engineers were interviewed. There were both inexperienced and experienced engineers and both from the domains of process automation and machine automation. The interview themes were constructed based on the Core-Task Analysis method and the Järvinen’s and Poikela’s learning at work process model. As a result the automation engineer’s core task and learning at work process were defined. Workshops were utilized when defining the concept of work support and training tool. Based on this knowledge the concept of Autaki tool was defined and a prototype was developed. The purpose of Autaki is to assist engineers in their daily work and to support them in learning at work. According to the concept definition, Autaki is a databank of knowledge which can flexibly be extended and updated with new information. Autaki supports learning at work by providing tools for both independent and collaborative learning. There is a need for Autaki kind of tool in automation engineering work as well as in many other design work disciplines. The high requirements of performing work fast and effectively in addition to the aging and retirement of the engineers are threats for engineering companies if they do not prepare themselves into this change in an appropriate way. Essential domain specific tacit knowledge have to be transferred from the experienced engineers to the inexperienced ones. This study offers one way to support this complicated and challenging task.