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Exploring the possibilities of using image recognition technology to create a hybrid lean system for pulse methodology

Kaya, Onur, 1987 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Catic, Amer, 1982 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Bergsjö, Dag Henrik, 1980 (author)
Chalmers tekniska högskola,Chalmers University of Technology
 (creator_code:org_t)
Elsevier BV, 2014
2014
English.
In: Procedia Computer Science. - : Elsevier BV. - 1877-0509. ; 28, s. 275-284
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Processes in product development are becoming more and more complex. A multitude of engineering disciplines are involved in the development of new products. New lean and agile methods arise. Pulse methodology is a lean deviation management methodology introduced by Scania in 2003, and since then many Swedish companies adapted it. It is based on synchronizing the company by frequently having short meetings (aka. pulse meetings) and visualizing the deviations using traffic coded magnets on whiteboards (aka. pulse boards). Even though the whiteboards lack providing efficient communication between distributed teams, still the users appreciate the simplicity of them. In this research, we presented a new methodology called hybrid pulse methodology, which solves the communication issues exist in the baseline methodology. We tested the methodology at the workshops we held in the companies, in simulated global meeting settings, using the demonstrator we developed for the methodology. This research contributes to the lean literature with a new methodology that ensures the synchronization of global organizations by providing efficient communication between distributed teams without damaging the baseline methodology.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

Hybrid systems
Deviation management
Visual management
Distributed teams

Publication and Content Type

kon (subject category)
ref (subject category)

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