Global Assembly Instruction Strategies (GAIS) 2

Companies are getting more and more global in order to be closer to the end-market. This put great demands in a well-structured information system. Earlier research shows that there are different strategies regarding information and knowledge sharing.

In GAIS 1, both centralization and decentralization strategies were
identified in the manufacturing engineering processes. From previous research it has been argued that multinational companies at a corporate level tend to centralize as such structures are more focused on reducing costs [10]. However, for a multinational company that has a history of an extensive acquisition based growth strategy, it is difficult to handle integration of new entities and take advantage of synergies [11].

GAIS 2 aims to improve information- and knowledge sharing within a global production network. This will be done in two areas with regards to assembly instructions; the engineering manufacturing process and the learning process
of operators.

The aim is divided into four research questions:

  • RQ1: How do different strategies in manufacturing engineering processes affect the flexibility in assembly instructions at a global level?
  • RQ2: What methods and standards are suitable for global information sharing regarding instructions for operators in assembly systems?
  • RQ3: How can technology be utilized to improve learning curve effects, and reduce time-toknowledge, and create flexibility for information and knowledge sharing?
  • RQ4: How can knowledge sharing be improved in order to decrease learning curve for operators?

GAIS 2 aims to achieve models and strategies to be able to decide whether to have a de-centralised or centralized approach within the manufacturing engineering process and the user interface for assembly instruction. Furthermore to have a structured learning process with the most suitable technologies in order to decrease the learning curve and to increase the quality of learning.

GAIS 2 hope to attract younger people by offering flexibility and new technologies for learning and assembling.

Participants

Åsa Fasth Berglund (contact)

Docent at Product and Production Development, Production Systems

Magnus Åkerman

Doktorand at Product and Production Development, Production Systems

Liang Gong

Doktorand at Product and Production Development, Production Systems

Pierre Johansson

at Unknown organization

Dan Li

Doktorand at Product and Production Development, Production Systems

Daniel Linné

Doktorand at Product and Production Development, Production Systems

Dan Paulin

Universitetslektor at Technology Management and Economics, Innovation and R&D Management

Collaborations

Combitech

Linköping, Sweden

Saab Aeronautics

Linköping, Sweden

University West

Trollhättan, Sweden

Volvo Trucks

Gothenburg, Sweden

XMReality

Linköping, Sweden

Funding

VINNOVA

Funding years 2016–2018

Related Areas of Advance and Infrastructure

Production

Area of Advance

More information

Latest update

2017-02-08