liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
A pattern-based decision framework in the era of Industry 4.0
Sungkyunkwan Univ, South Korea.
Sungkyunkwan Univ, South Korea.
Linköping University, Department of Management and Engineering, Logistics & Quality Management. Linköping University, Faculty of Science & Engineering.
2019 (English)In: Total quality management and business excellence (Online), ISSN 1478-3363, E-ISSN 1478-3371Article in journal (Refereed) Epub ahead of print
Abstract [en]

The primary purpose of this paper is to identify human decision-making patterns that can be transformed into machine decision-making in the era of Industry 4.0. We first isolated 40 key decision attributes and 6 decision patterns based on a literature review. Subsequently, we conducted a survey study of a group of 550 respondents from 11 different industrial types to find out the importance of both the attributes and the decision patterns. The six different human decision patterns (emotion, vision, principle, information, prevention, creation) were analysed for decision problems in both the daily lives and the operational stages of a business. The principle-based decision pattern is preferred for people who work in either Industry 1.0 or 2.0, while the information-based pattern is preferred for Industry 3.0. In the era of Industry 4.0, it seems that creation- and prevention-based patterns are also considered important in addition to principle- and information-based patterns. The decision patterns proposed in this study may be applied to design machines decision-making as a way to represent human decision makers.

Place, publisher, year, edition, pages
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD , 2019.
Keywords [en]
decision pattern; decision quality; Industry 4; 0; machine decision-making
National Category
Reliability and Maintenance
Identifiers
URN: urn:nbn:se:liu:diva-161142DOI: 10.1080/14783363.2019.1665840ISI: 000486867100001OAI: oai:DiVA.org:liu-161142DiVA, id: diva2:1365789
Note

Funding Agencies|National Research Foundation of Korea (NRF) - Korea government (MSIT) [2017R1A2B4012882]

Available from: 2019-10-25 Created: 2019-10-25 Last updated: 2019-10-25

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Dahlgaard, Jens Jörn
By organisation
Logistics & Quality ManagementFaculty of Science & Engineering
In the same journal
Total quality management and business excellence (Online)
Reliability and Maintenance

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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