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Lessons Learned Practice in a Complex Production Environment
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-7512-4425
2017 (English)In: Book Innovative Quality Improvement in Operations / [ed] Tomas Backström, Anders Fundin, Peter E. Johansson, Springer, 2017, 113-130 p.Chapter in book (Other academic)
Abstract [en]

Lessons learned practice is a well-known method embraced by many companies to enhance continuous learning in their organizational routines and day-to-day work. The extant literature presents a mix of several lessons learned approaches from different disciplines. However, the approaches fail to address the distinct, complex settings that arise in production and operation phases. Thus, there is a need for rethinking of lessons learned practice in a complex production environments. Based on case studies in the aerospace industry, this chapter presents a new method for lessons learned practice, which includes a standard, seven-step representation format, together with guidelines, using videos as an enabling media. The seven-steps are: lesson learned statement, working context, task description, what went wrong or what went well, lesson learned, lesson learned measures, and applicability and delimitations. The method intends to capture a single learning point with specific recommendations, promoting process-based rather than a project-based learning. The chapter presents results from the validation of this new method in industrial setting. The validation shows that the method is beneficial in capturing lessons from skill-oriented activities in narrative form by visually showing and telling defects, problems, or improvements in complex products and associated actions in production or product support phases. The method supports exploration processes at the individual level with the creation of new knowledge with a richer context and so support exploitation processes and activities at the organizational level.

Place, publisher, year, edition, pages
Springer, 2017. 113-130 p.
Series
International Series in Operations Research & Management Science, ISSN 0884-8289
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-35499DOI: 10.1007/978-3-319-55985-8_7Scopus ID: 2-s2.0-85024493040ISBN: 978-3-319-55984-1 OAI: oai:DiVA.org:mdh-35499DiVA: diva2:1106887
Available from: 2017-06-08 Created: 2017-06-08 Last updated: 2017-08-10Bibliographically approved

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Chirumalla, Koteshwar

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf