Abstract
The initial issue of complexity management in companies is the identification of the drivers of complexity. However, current literature lacks methods for assisting practitioners in the initial identification of such drivers. This paper, therefore, presents a novel framework for assisting practitioners with identifying complexity drivers in manufacturing companies. The framework uses a generic value chain and a generic product structure as its two dimensions. Multiple workshops are then conducted with company representatives across different value chain fields focusing on two main parts: First, surveys are used to assign complexity ratings to different generic product structure elements. Secondly, the complexity ratings are elaborated on by workshop participants. The process provides valuable insights into the perceived complexity drivers. The framework is then verified through a case study in the process industry. Based on the case study, multiple complexity drivers were identified across both value chain fields and product structure elements. The case study findings show that the framework facilitates practitioners in identifying organization-wide perceived complexity drivers. The framework contributes to both industry and research by addressing a neglected aspect of complexity management. It achieves this by providing a comprehensive and structured approach for the initial identification of complexity drivers across product elements and value chain fields.
| Original language | English |
|---|---|
| Title of host publication | Advances in Production Management Systems. Production Management for the Factory of the Future : IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1–5, 2019, Proceedings, Part I |
| Editors | Farhad Ameri, Kathryn E. Stecke, Gregor von Cieminski, Dimitris Kiritsis |
| Number of pages | 8 |
| Publisher | Springer |
| Publication date | 2019 |
| Pages | 392-399 |
| ISBN (Print) | 978-3-030-29999-6 |
| ISBN (Electronic) | 978-3-030-30000-5 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | IFIP WG 5.7 International Conference, APMS 2019 - Hilton Austin, Texas, Austin, TX, United States Duration: 2 Sep 2019 → 5 Sep 2019 https://www.apms-conference.org |
Conference
| Conference | IFIP WG 5.7 International Conference, APMS 2019 |
|---|---|
| Location | Hilton Austin, Texas |
| Country | United States |
| City | Austin, TX |
| Period | 02/09/2019 → 05/09/2019 |
| Internet address |
| Series | IFIP AICT - Advances in Information and Communication technology |
|---|---|
| Volume | 566 |
| ISSN | 1571-5736 |
Fingerprint
Keywords
- Complexity driver
- Complexity management
- Framework
- Identification
- Manufacturing
Cite this
}
A Framework for Identification of Complexity Drivers in Manufacturing Companies. / Andersen, Rasmus; Brunø, Thomas Ditlev; Nielsen, Kjeld.
Advances in Production Management Systems. Production Management for the Factory of the Future: IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1–5, 2019, Proceedings, Part I. ed. / Farhad Ameri; Kathryn E. Stecke; Gregor von Cieminski; Dimitris Kiritsis. Springer, 2019. p. 392-399 (IFIP AICT - Advances in Information and Communication technology, Vol. 566).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
TY - GEN
T1 - A Framework for Identification of Complexity Drivers in Manufacturing Companies
AU - Andersen, Rasmus
AU - Brunø, Thomas Ditlev
AU - Nielsen, Kjeld
PY - 2019
Y1 - 2019
N2 - The initial issue of complexity management in companies is the identification of the drivers of complexity. However, current literature lacks methods for assisting practitioners in the initial identification of such drivers. This paper, therefore, presents a novel framework for assisting practitioners with identifying complexity drivers in manufacturing companies. The framework uses a generic value chain and a generic product structure as its two dimensions. Multiple workshops are then conducted with company representatives across different value chain fields focusing on two main parts: First, surveys are used to assign complexity ratings to different generic product structure elements. Secondly, the complexity ratings are elaborated on by workshop participants. The process provides valuable insights into the perceived complexity drivers. The framework is then verified through a case study in the process industry. Based on the case study, multiple complexity drivers were identified across both value chain fields and product structure elements. The case study findings show that the framework facilitates practitioners in identifying organization-wide perceived complexity drivers. The framework contributes to both industry and research by addressing a neglected aspect of complexity management. It achieves this by providing a comprehensive and structured approach for the initial identification of complexity drivers across product elements and value chain fields.
AB - The initial issue of complexity management in companies is the identification of the drivers of complexity. However, current literature lacks methods for assisting practitioners in the initial identification of such drivers. This paper, therefore, presents a novel framework for assisting practitioners with identifying complexity drivers in manufacturing companies. The framework uses a generic value chain and a generic product structure as its two dimensions. Multiple workshops are then conducted with company representatives across different value chain fields focusing on two main parts: First, surveys are used to assign complexity ratings to different generic product structure elements. Secondly, the complexity ratings are elaborated on by workshop participants. The process provides valuable insights into the perceived complexity drivers. The framework is then verified through a case study in the process industry. Based on the case study, multiple complexity drivers were identified across both value chain fields and product structure elements. The case study findings show that the framework facilitates practitioners in identifying organization-wide perceived complexity drivers. The framework contributes to both industry and research by addressing a neglected aspect of complexity management. It achieves this by providing a comprehensive and structured approach for the initial identification of complexity drivers across product elements and value chain fields.
KW - Complexity driver
KW - Complexity management
KW - Framework
KW - Identification
KW - Manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85072965964&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-30000-5_49
DO - 10.1007/978-3-030-30000-5_49
M3 - Article in proceeding
SN - 978-3-030-29999-6
T3 - IFIP AICT - Advances in Information and Communication technology
SP - 392
EP - 399
BT - Advances in Production Management Systems. Production Management for the Factory of the Future
A2 - Ameri, Farhad
A2 - Stecke, Kathryn E.
A2 - von Cieminski, Gregor
A2 - Kiritsis, Dimitris
PB - Springer
ER -