Identifying 3D-printable Spare Parts for a Digitalized Supply Chain

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

In OEM's producing capital goods, aftersales services is a major part of the business. Managing spare parts cost-efficiently, while providing high service level for the customers is a challenge. Digital spare parts project (DIVA) studies a digital supply chain, where spare parts are 3D printed on demand close to the end user. This could simultaneously reduce costs and increase service level. The first challenge is how to identify parts suitable for 3D printing from the tens or hundreds of thousands of spare parts that companies manage, as not all are technologically or economically viable to 3D print. In this study, a similar method as developed by Knofius et al. (2016) is used to identify such spare parts in two OEMs producing capital goods. Based on the case studies, it is estimated that up to 20 % of the spare parts could be 3D printable in theory. This is reduced to around 6 % having good technological potential to be 3D printed. Furthermore, around 2 % would also be economically feasible to 3D print today. To improve the accuracy and automate the identification process, more structured spare part data is needed.
Original languageEnglish
Title of host publicationProceedings of the 2nd Annual SMACC Research Seminar 2017
PublisherTampere University of Technology
Pages37-40
ISBN (Print)978-952-15-4040-0
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventAnnual SMACC Research Seminar 2017 - Tampere, Finland
Duration: 7 Nov 20177 Nov 2017
Conference number: 2
http://smacc.fi

Seminar

SeminarAnnual SMACC Research Seminar 2017
CountryFinland
CityTampere
Period7/11/177/11/17
Internet address

Fingerprint

Supply chains
Printing
Costs
Industry

Keywords

  • 3D printing
  • additive manufacturing
  • aftersales supply chain
  • digital spare parts

Cite this

Reijonen, J. (2017). Identifying 3D-printable Spare Parts for a Digitalized Supply Chain. In Proceedings of the 2nd Annual SMACC Research Seminar 2017 (pp. 37-40). Tampere University of Technology.
Reijonen, Joni. / Identifying 3D-printable Spare Parts for a Digitalized Supply Chain. Proceedings of the 2nd Annual SMACC Research Seminar 2017. Tampere University of Technology, 2017. pp. 37-40
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title = "Identifying 3D-printable Spare Parts for a Digitalized Supply Chain",
abstract = "In OEM's producing capital goods, aftersales services is a major part of the business. Managing spare parts cost-efficiently, while providing high service level for the customers is a challenge. Digital spare parts project (DIVA) studies a digital supply chain, where spare parts are 3D printed on demand close to the end user. This could simultaneously reduce costs and increase service level. The first challenge is how to identify parts suitable for 3D printing from the tens or hundreds of thousands of spare parts that companies manage, as not all are technologically or economically viable to 3D print. In this study, a similar method as developed by Knofius et al. (2016) is used to identify such spare parts in two OEMs producing capital goods. Based on the case studies, it is estimated that up to 20 {\%} of the spare parts could be 3D printable in theory. This is reduced to around 6 {\%} having good technological potential to be 3D printed. Furthermore, around 2 {\%} would also be economically feasible to 3D print today. To improve the accuracy and automate the identification process, more structured spare part data is needed.",
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Reijonen, J 2017, Identifying 3D-printable Spare Parts for a Digitalized Supply Chain. in Proceedings of the 2nd Annual SMACC Research Seminar 2017. Tampere University of Technology, pp. 37-40, Annual SMACC Research Seminar 2017, Tampere, Finland, 7/11/17.

Identifying 3D-printable Spare Parts for a Digitalized Supply Chain. / Reijonen, Joni.

Proceedings of the 2nd Annual SMACC Research Seminar 2017. Tampere University of Technology, 2017. p. 37-40.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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N2 - In OEM's producing capital goods, aftersales services is a major part of the business. Managing spare parts cost-efficiently, while providing high service level for the customers is a challenge. Digital spare parts project (DIVA) studies a digital supply chain, where spare parts are 3D printed on demand close to the end user. This could simultaneously reduce costs and increase service level. The first challenge is how to identify parts suitable for 3D printing from the tens or hundreds of thousands of spare parts that companies manage, as not all are technologically or economically viable to 3D print. In this study, a similar method as developed by Knofius et al. (2016) is used to identify such spare parts in two OEMs producing capital goods. Based on the case studies, it is estimated that up to 20 % of the spare parts could be 3D printable in theory. This is reduced to around 6 % having good technological potential to be 3D printed. Furthermore, around 2 % would also be economically feasible to 3D print today. To improve the accuracy and automate the identification process, more structured spare part data is needed.

AB - In OEM's producing capital goods, aftersales services is a major part of the business. Managing spare parts cost-efficiently, while providing high service level for the customers is a challenge. Digital spare parts project (DIVA) studies a digital supply chain, where spare parts are 3D printed on demand close to the end user. This could simultaneously reduce costs and increase service level. The first challenge is how to identify parts suitable for 3D printing from the tens or hundreds of thousands of spare parts that companies manage, as not all are technologically or economically viable to 3D print. In this study, a similar method as developed by Knofius et al. (2016) is used to identify such spare parts in two OEMs producing capital goods. Based on the case studies, it is estimated that up to 20 % of the spare parts could be 3D printable in theory. This is reduced to around 6 % having good technological potential to be 3D printed. Furthermore, around 2 % would also be economically feasible to 3D print today. To improve the accuracy and automate the identification process, more structured spare part data is needed.

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Reijonen J. Identifying 3D-printable Spare Parts for a Digitalized Supply Chain. In Proceedings of the 2nd Annual SMACC Research Seminar 2017. Tampere University of Technology. 2017. p. 37-40