Virtual Training - Preparatory Training in Automotive Assembly

Doctoral thesis, 2012

The automotive industry is constantly facing new challenges. Reduction of waste and time-to-market, ability to offer the customer a unique combination of options as well as high product quality are examples of issues that have been in focus during the past decade and still considered extremely important. Together with the aforementioned issues, other factors that influence the way in which new vehicles are launched and produced are shorter product life cycles and the fact that completely different vehicles are often manufactured on the same assembly line. Assembly operators constitute a central part of the production system and their skills and ability to ensure high quality will always be in focus. Cost reduction and a shift towards more virtual product development methods provide the potential to reduce prototype vehicles to a minimum or even completely. This has dramatically affected the training of experienced assembly operators prior to the launch of a new vehicle since the traditional way of utilizing prototype vehicle components for training purposes is more or less non-existent. Consequently, the new conditions have created a strong need for alternative training methods. The starting point for the present work was to identify methods based on previously generated engineering information and use them on ordinary desktop computers for the training of experienced assembly operators. The work was carried out as case studies, all performed in an assembly plant with experienced assembly operators as subjects. The research mainly concentrated on understanding this specific area and how such training should be organized to best support the operators during a new vehicle launch. The results demonstrated that virtual training is an effective tool for preparatory training of assembly operators as well as training in the later stages when detailed assembly sequences and quality related issues (finesse) are in focus. Preparatory training can be performed in an efficient way by using the defined and explored expert based learning model. On the other hand, assembly sequence and finesse training is appropriate for the defined system learning model. The design of the studies was based on a defined framework with four operator knowledge phases: Product, Process, Assembly sequence and Finesse. The results of the case studies combined with the above-mentioned framework constituted the basis for a proposed virtual preparatory training concept. This concept included two major virtual training activities where the first two knowledge phases formed the base for the first activity and the two final phases the foundation for the second. The aim was to develop an understanding of how computers can be used in the training of operator s, especially in the preparation and support of launch training. As a result of our studies, an important step towards a deeper understanding has been achieved.