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Computer Support for Preparatory Training in Automotive Assembly

Lennart Malmsköld (Institutionen för produkt- och produktionsutveckling, Produktionssystem)
Göteborg : Chalmers University of Technology, 2009.
[Licentiatavhandling]

The automotive industry is facing new challenges constantly. Reduction of waste and time-to-market, the ability to offer the customer a unique combination of options and high product quality are examples of issues that have been in focus during the last decade and are still considered very important. Shorter product life cycles and the fact that completely different vehicles are often produced on the same assembly line are, together with the aforementioned issues, factors that influence the way new vehicles are launched and produced. The assembly operators constitute a central part of the production system and their skills and ability to produce high quality are issues that will always be in focus. Cost reduction and a change towards more computer based product development methods provide a potential to reduce prototype vehicles to a minimum or even completely. The latter change has affected the training of operators’ prior vehicle launches in a dramatic way since the traditional way to utilize components from prototype vehicles for training purposes has become quite limited. Consequently the new conditions have created a strong need for alternative training methods.

The starting point for the work has been to find methods that are based on already generated engineering information and use them on ordinary desktop computers for the training of experienced assembly operators. The work has been carried out as case studies, all performed in an assembly plant with experienced assembly operators as subjects. The research has been concentrated on understanding this specific area and how this type of training should be organized to best support the operators during a launch of new vehicles.

The result shows that computer based training is an effective tool and preparatory training of assembly operators can be performed in an efficient way by using the defined and explored expert based learning model. The model provides training that supports all operators, including the leaders of the operator teams and it connects the training environment and the real assembly situation on the assembly line in a positive way. A defined framework with four operator knowledge phases named: Product, Process, Assembly sequence and Finesse are presented. The results from the case studies, combined with the defined framework constitute the base for a proposed concept for computer based preparatory training. The concept includes two major training activities and one of them –- is the focus of this work.

The aim of this work has been to develop an understanding for how computers can be used in the training of operators, especially to prepare and support learning in launch training. With the accomplished studies an important step towards deeper understanding has been achieved. However, additional research is needed in order to verify and further develop the proposed concept.

Nyckelord: Virtual Assembly Training, Automotive Operator Training, Lean Production, Job Instruction Training



Denna post skapades 2009-04-23.
CPL Pubid: 92873

 

Institutioner (Chalmers)

Institutionen för produkt- och produktionsutveckling, Produktionssystem (2005-2017)

Ämnesområden

Övrig informationsteknik
Arbetsvetenskap och ergonomi
Teknik och social förändring

Chalmers infrastruktur

Relaterade publikationer

Inkluderade delarbeten:


Instructor based training versus computer based training - A comparative study


Preparatory Virtual Training of Assembly Operators – an Explorative Study of Different Learning Models


Virtual Training – Towards a Design Framework


Examination

Datum: 2009-05-20
Tid: 10:00
Lokal: Gamma-Delta, Hörsalsvägen 7, Chalmers tekniska högskola, Göteborg
Opponent: Phd Peter Nordell, SKF

Ingår i serie

Research series from Chalmers University of Technology, Department of Product and Production Development: report 43