Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

Lei Shi; Linda B Newnes; Steve Cully; James A Gopsill; Chris Snider

doi:10.1007/978-3-319-33111-9_27

Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

Lei Shi, Linda B Newnes, Steve Cully, James A Gopsill, Chris Snider

Department of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

293 Downloads (Pure)

Abstract

Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.

Original language	English
Title of host publication	Product Lifecycle Management in the Era of Internet of Things
Subtitle of host publication	12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers
Editors	Abdelaziz Bouras, Benoit Eynard, Sebti Foufou, Klaus-Dieter Thoben
Publisher	Springer
Pages	291-300
Number of pages	10
ISBN (Electronic)	9783319331119
ISBN (Print)	9783319331102
DOIs	https://doi.org/10.1007/978-3-319-33111-9_27
Publication status	Published - 2016

Publication series

Name	IFIP Advances in Information and Communication Technology
Publisher	Springer
Volume	467
ISSN (Print)	1868-4238

Keywords

In-Service
Engineering project process
Process management
Process evolution

Access to Document

10.1007/978-3-319-33111-9_27

Full-text PDF (accepted author manuscript)
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LOCM: The Language of Collaborative Manufacturing
Gopsill, J. A. (Researcher), McAlpine, H. C. (Manager), McMahon, C. A. (Co-Principal Investigator), Snider, C. M. (Researcher), Shi, L. (Researcher), Watts, L. (Co-Principal Investigator), Jones, S. (Researcher), Johnson, P. (Co-Principal Investigator), Newnes, L. (Co-Principal Investigator), Payne, S. (Co-Principal Investigator), Culley, S. (Co-Principal Investigator) & Hicks, B. J. (Principal Investigator)
1/02/13 → 31/07/18
Project: Research

Cite this

Shi, L., Newnes, L. B., Cully, S., Gopsill, J. A., & Snider, C. (2016). Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects. In A. Bouras, B. Eynard, S. Foufou, & K.-D. Thoben (Eds.), Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers (pp. 291-300). (IFIP Advances in Information and Communication Technology; Vol. 467). Springer. https://doi.org/10.1007/978-3-319-33111-9_27

Shi, Lei ; Newnes, Linda B ; Cully, Steve et al. / Data-driven Modelling : Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects. Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers. editor / Abdelaziz Bouras ; Benoit Eynard ; Sebti Foufou ; Klaus-Dieter Thoben. Springer, 2016. pp. 291-300 (IFIP Advances in Information and Communication Technology).

@inproceedings{42652e59c43c4b8887a8872df5e30232,

title = "Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects",

abstract = "Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.",

keywords = "In-Service, Engineering project process, Process management, Process evolution",

author = "Lei Shi and Newnes, {Linda B} and Steve Cully and Gopsill, {James A} and Chris Snider",

year = "2016",

doi = "10.1007/978-3-319-33111-9_27",

language = "English",

isbn = "9783319331102",

series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer",

pages = "291--300",

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Shi, L, Newnes, LB, Cully, S, Gopsill, JA & Snider, C 2016, Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects. in A Bouras, B Eynard, S Foufou & K-D Thoben (eds), Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers. IFIP Advances in Information and Communication Technology, vol. 467, Springer, pp. 291-300. https://doi.org/10.1007/978-3-319-33111-9_27

Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects. / Shi, Lei; Newnes, Linda B; Cully, Steve et al.
Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers. ed. / Abdelaziz Bouras; Benoit Eynard; Sebti Foufou; Klaus-Dieter Thoben. Springer, 2016. p. 291-300 (IFIP Advances in Information and Communication Technology; Vol. 467).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Data-driven Modelling

T2 - Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

AU - Shi, Lei

AU - Newnes, Linda B

AU - Cully, Steve

AU - Gopsill, James A

AU - Snider, Chris

PY - 2016

Y1 - 2016

N2 - Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.

AB - Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.

KW - In-Service

KW - Engineering project process

KW - Process management

KW - Process evolution

U2 - 10.1007/978-3-319-33111-9_27

DO - 10.1007/978-3-319-33111-9_27

M3 - Conference Contribution (Conference Proceeding)

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T3 - IFIP Advances in Information and Communication Technology

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EP - 300

BT - Product Lifecycle Management in the Era of Internet of Things

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PB - Springer

ER -

Shi L, Newnes LB, Cully S, Gopsill JA , Snider C. Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects. In Bouras A, Eynard B, Foufou S, Thoben KD, editors, Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers. Springer. 2016. p. 291-300. (IFIP Advances in Information and Communication Technology). Epub 2016 Apr 21. doi: 10.1007/978-3-319-33111-9_27

Data-driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

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LOCM: The Language of Collaborative Manufacturing

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