Details
| Original language | English |
|---|---|
| Title of host publication | Towards Sustainable Customization |
| Subtitle of host publication | Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 |
| Editors | Ann-Louise Andersen, Rasmus Andersen, Thomas Ditlev Brunoe, Maria Stoettrup Schioenning Larsen, Kjeld Nielsen, Alessia Napoleone, Stefan Kjeldgaard |
| Place of Publication | Cham |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 603-611 |
| Number of pages | 9 |
| ISBN (print) | 9783030906993 |
| Publication status | Published - 2022 |
| Event | 8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021 - Aalborg, Denmark Duration: 1 Nov 2021 → 2 Nov 2021 |
Publication series
| Name | Lecture Notes in Mechanical Engineering |
|---|---|
| ISSN (Print) | 2195-4356 |
| ISSN (electronic) | 2195-4364 |
Abstract
Contract manufacturing companies have to calculate offer prices for individualized products in cost-driven markets with experience-based estimations on limited data. Especially, the estimation of processing and set-up times is time-consuming and challenging. Algorithms providing suitable and transparent estimations with low configuration effort and licence costs for several machining processes are currently not available. Therefore, a method is developed to provide automated estimates for machining and set-up times from production data based on similarity metrics. This method is evaluated using feedback data from turned, milled and whirled workpieces. Experiments show that, compared to experience-based methods, an accuracy increase of 7.8% is achievable for process time estimation of turned parts and 21.2% for set-up operations.
Keywords
- Cost estimation, Decision support, Process time estimation, Set-up time estimation, Smart services
ASJC Scopus subject areas
- Engineering(all)
- Automotive Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Chemical Engineering(all)
- Fluid Flow and Transfer Processes
Cite this
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Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021. ed. / Ann-Louise Andersen; Rasmus Andersen; Thomas Ditlev Brunoe; Maria Stoettrup Schioenning Larsen; Kjeld Nielsen; Alessia Napoleone; Stefan Kjeldgaard. Cham: Springer Science and Business Media Deutschland GmbH, 2022. p. 603-611 (Lecture Notes in Mechanical Engineering).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Similarity-Based Process and Set-Up Time Estimation
AU - Denkena, B.
AU - Dittrich, M. A.
AU - Settnik, S. J.
N1 - Funding Information: The project ?JobTRADE? is funded by the European Fund for Regional Development for Regional Development (EFRE) and the State of Lower Saxony, program area more developed region (SER) under the grant number ZW 3-85035663.
PY - 2022
Y1 - 2022
N2 - Contract manufacturing companies have to calculate offer prices for individualized products in cost-driven markets with experience-based estimations on limited data. Especially, the estimation of processing and set-up times is time-consuming and challenging. Algorithms providing suitable and transparent estimations with low configuration effort and licence costs for several machining processes are currently not available. Therefore, a method is developed to provide automated estimates for machining and set-up times from production data based on similarity metrics. This method is evaluated using feedback data from turned, milled and whirled workpieces. Experiments show that, compared to experience-based methods, an accuracy increase of 7.8% is achievable for process time estimation of turned parts and 21.2% for set-up operations.
AB - Contract manufacturing companies have to calculate offer prices for individualized products in cost-driven markets with experience-based estimations on limited data. Especially, the estimation of processing and set-up times is time-consuming and challenging. Algorithms providing suitable and transparent estimations with low configuration effort and licence costs for several machining processes are currently not available. Therefore, a method is developed to provide automated estimates for machining and set-up times from production data based on similarity metrics. This method is evaluated using feedback data from turned, milled and whirled workpieces. Experiments show that, compared to experience-based methods, an accuracy increase of 7.8% is achievable for process time estimation of turned parts and 21.2% for set-up operations.
KW - Cost estimation
KW - Decision support
KW - Process time estimation
KW - Set-up time estimation
KW - Smart services
UR - http://www.scopus.com/inward/record.url?scp=85119401100&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-90700-6_68
DO - 10.1007/978-3-030-90700-6_68
M3 - Conference contribution
AN - SCOPUS:85119401100
SN - 9783030906993
T3 - Lecture Notes in Mechanical Engineering
SP - 603
EP - 611
BT - Towards Sustainable Customization
A2 - Andersen, Ann-Louise
A2 - Andersen, Rasmus
A2 - Brunoe, Thomas Ditlev
A2 - Larsen, Maria Stoettrup Schioenning
A2 - Nielsen, Kjeld
A2 - Napoleone, Alessia
A2 - Kjeldgaard, Stefan
PB - Springer Science and Business Media Deutschland GmbH
CY - Cham
T2 - 8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021
Y2 - 1 November 2021 through 2 November 2021
ER -