Identification of Platform Candidates Through Production System Classification Coding

Daniel G. H. Sorensen; Hoda A. ElMaraghy; Thomas Ditlev Brunoe; Kjeld Nielsen

doi:10.1007/978-3-030-30000-5_50

Identification of Platform Candidates Through Production System Classification Coding

Daniel G. H. Sorensen^*, Hoda A. ElMaraghy, Thomas Ditlev Brunoe, Kjeld Nielsen

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

1 Citation (Scopus)

Abstract

Changeable and reconfigurable manufacturing appears as a natural response to a need for improved variety management. Such manufacturing systems are complicated to develop, and it can be advantageous to base or build these systems on product and production platforms. Development of platforms is, however, not a trivial task. Currently, identification and selection of candidates for inclusion in a platform is typically subjective relying on experts and tacit knowledge. The objectivity of this process can be strengthened by collecting data on existing production systems in a company and comparing these systems to each other. To do so, a coherent, consistent and preferably digital representation of multiple production systems is needed. In this research, a production system classification coding (PSCC) scheme is employed to classify and structure data for a number of existing production systems, spanning multiple departments and product families. Candidates for a production platform covering the included production systems are identified based on ranking certain platform drivers, processes and enablers.

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
Place of Publication	Cham
Publisher	Springer
Publication date	24 Aug 2019
Pages	400-407
Chapter	50
ISBN (Print)	9783030299996
ISBN (Electronic)	978-3-030-30000-5
DOIs	https://doi.org/10.1007/978-3-030-30000-5_50
Publication status	Published - 24 Aug 2019
Event	IFIP WG 5.7 International Conference, APMS 2019 - Hilton Austin, Texas, Austin, TX, United States Duration: 2 Sept 2019 → 5 Sept 2019 https://www.apms-conference.org

Conference

Conference	IFIP WG 5.7 International Conference, APMS 2019
Location	Hilton Austin, Texas
Country/Territory	United States
City	Austin, TX
Period	02/09/2019 → 05/09/2019
Internet address	https://www.apms-conference.org

Series	IFIP AICT - Advances in Information and Communication technology
Volume	566
ISSN	1571-5736

Keywords

manufacturing system
classification code
platform

Access to Document

10.1007/978-3-030-30000-5_50

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Sorensen, D. G. H., ElMaraghy, H. A., Brunoe, T. D., & Nielsen, K. (2019). Identification of Platform Candidates Through Production System Classification Coding. In F. Ameri, K. E. Stecke, G. von Cieminski, & D. Kiritsis (Eds.), 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 (pp. 400-407). Springer. https://doi.org/10.1007/978-3-030-30000-5_50

Sorensen, Daniel G. H. ; ElMaraghy, Hoda A. ; Brunoe, Thomas Ditlev et al. / Identification of Platform Candidates Through Production System Classification Coding. 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. editor / Farhad Ameri ; Kathryn E. Stecke ; Gregor von Cieminski ; Dimitris Kiritsis. Cham : Springer, 2019. pp. 400-407 (IFIP AICT - Advances in Information and Communication technology, Vol. 566).

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title = "Identification of Platform Candidates Through Production System Classification Coding",

abstract = "Changeable and reconfigurable manufacturing appears as a natural response to a need for improved variety management. Such manufacturing systems are complicated to develop, and it can be advantageous to base or build these systems on product and production platforms. Development of platforms is, however, not a trivial task. Currently, identification and selection of candidates for inclusion in a platform is typically subjective relying on experts and tacit knowledge. The objectivity of this process can be strengthened by collecting data on existing production systems in a company and comparing these systems to each other. To do so, a coherent, consistent and preferably digital representation of multiple production systems is needed. In this research, a production system classification coding (PSCC) scheme is employed to classify and structure data for a number of existing production systems, spanning multiple departments and product families. Candidates for a production platform covering the included production systems are identified based on ranking certain platform drivers, processes and enablers.",

keywords = "manufacturing system, classification code, platform",

author = "Sorensen, {Daniel G. H.} and ElMaraghy, {Hoda A.} and Brunoe, {Thomas Ditlev} and Kjeld Nielsen",

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doi = "10.1007/978-3-030-30000-5_50",

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booktitle = "Advances in Production Management Systems. Production Management for the Factory of the Future",

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Sorensen, DGH, ElMaraghy, HA, Brunoe, TD & Nielsen, K 2019, Identification of Platform Candidates Through Production System Classification Coding. in F Ameri, KE Stecke, G von Cieminski & D Kiritsis (eds), 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. Springer, Cham, IFIP AICT - Advances in Information and Communication technology, vol. 566, pp. 400-407, IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, United States, 02/09/2019. https://doi.org/10.1007/978-3-030-30000-5_50

Identification of Platform Candidates Through Production System Classification Coding. / Sorensen, Daniel G. H.; ElMaraghy, Hoda A.; Brunoe, Thomas Ditlev et al.
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. Cham: Springer, 2019. p. 400-407 (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 - Identification of Platform Candidates Through Production System Classification Coding

AU - Sorensen, Daniel G. H.

AU - ElMaraghy, Hoda A.

AU - Brunoe, Thomas Ditlev

AU - Nielsen, Kjeld

PY - 2019/8/24

Y1 - 2019/8/24

N2 - Changeable and reconfigurable manufacturing appears as a natural response to a need for improved variety management. Such manufacturing systems are complicated to develop, and it can be advantageous to base or build these systems on product and production platforms. Development of platforms is, however, not a trivial task. Currently, identification and selection of candidates for inclusion in a platform is typically subjective relying on experts and tacit knowledge. The objectivity of this process can be strengthened by collecting data on existing production systems in a company and comparing these systems to each other. To do so, a coherent, consistent and preferably digital representation of multiple production systems is needed. In this research, a production system classification coding (PSCC) scheme is employed to classify and structure data for a number of existing production systems, spanning multiple departments and product families. Candidates for a production platform covering the included production systems are identified based on ranking certain platform drivers, processes and enablers.

AB - Changeable and reconfigurable manufacturing appears as a natural response to a need for improved variety management. Such manufacturing systems are complicated to develop, and it can be advantageous to base or build these systems on product and production platforms. Development of platforms is, however, not a trivial task. Currently, identification and selection of candidates for inclusion in a platform is typically subjective relying on experts and tacit knowledge. The objectivity of this process can be strengthened by collecting data on existing production systems in a company and comparing these systems to each other. To do so, a coherent, consistent and preferably digital representation of multiple production systems is needed. In this research, a production system classification coding (PSCC) scheme is employed to classify and structure data for a number of existing production systems, spanning multiple departments and product families. Candidates for a production platform covering the included production systems are identified based on ranking certain platform drivers, processes and enablers.

KW - manufacturing system

KW - classification code

KW - platform

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U2 - 10.1007/978-3-030-30000-5_50

DO - 10.1007/978-3-030-30000-5_50

M3 - Article in proceeding

SN - 9783030299996

T3 - IFIP AICT - Advances in Information and Communication technology

SP - 400

EP - 407

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

CY - Cham

T2 - IFIP WG 5.7 International Conference, APMS 2019

Y2 - 2 September 2019 through 5 September 2019

ER -

Sorensen DGH, ElMaraghy HA, Brunoe TD , Nielsen K. Identification of Platform Candidates Through Production System Classification Coding. In Ameri F, Stecke KE, von Cieminski G, Kiritsis D, editors, 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. Cham: Springer. 2019. p. 400-407. (IFIP AICT - Advances in Information and Communication technology, Vol. 566). doi: 10.1007/978-3-030-30000-5_50

Identification of Platform Candidates Through Production System Classification Coding

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Developing Manufacturing System Platforms