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Decentralized control of assembly processes driven by Gentelligent® Parts

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

Decentralized control of assembly processes driven by Gentelligent® Parts. / Schmidt, Matthias; Fronia, Philip; Nyhuis, Peter.
In: International Journal of Management Science and Engineering Management, Vol. 5, No. 1, 05.2010, p. 59-64.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Schmidt, M, Fronia, P & Nyhuis, P 2010, 'Decentralized control of assembly processes driven by Gentelligent® Parts', International Journal of Management Science and Engineering Management, vol. 5, no. 1, pp. 59-64. https://doi.org/10.1080/17509653.2010.10671092

APA

Schmidt, M., Fronia, P., & Nyhuis, P. (2010). Decentralized control of assembly processes driven by Gentelligent® Parts. International Journal of Management Science and Engineering Management, 5(1), 59-64. https://doi.org/10.1080/17509653.2010.10671092

Vancouver

Schmidt M, Fronia P, Nyhuis P. Decentralized control of assembly processes driven by Gentelligent® Parts. International Journal of Management Science and Engineering Management. 2010 May;5(1):59-64. doi: 10.1080/17509653.2010.10671092

Bibtex

@article{07882871b80c4bb38a9d63d3da43a958,
title = "Decentralized control of assembly processes driven by Gentelligent{\textregistered} Parts",
abstract = "Logistically controlling assembly areas is based on processing information. The availability of the required information is thus a decisive factor. This paper introduces an approach for controlling assembly areas. The method is based on processing information from so called Gentelligent{\textregistered} Parts. These parts can be used as storage mediums and as such are able to record, save, process and communicate information. Due to these properties, Gentelligent{\textregistered} Parts can function as a decentralized Enterprise Information System. As a result, extensive potential for improving logistic and technical processes arises along the product evolutionary process and during the usage phase.",
keywords = "Engineering, production planning and control, supply chain management, intelligent manufacturing",
author = "Matthias Schmidt and Philip Fronia and Peter Nyhuis",
year = "2010",
month = may,
doi = "10.1080/17509653.2010.10671092",
language = "English",
volume = "5",
pages = "59--64",
journal = "International Journal of Management Science and Engineering Management",
issn = "1750-9661",
publisher = "Taylor and Francis Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Decentralized control of assembly processes driven by Gentelligent® Parts

AU - Schmidt, Matthias

AU - Fronia, Philip

AU - Nyhuis, Peter

PY - 2010/5

Y1 - 2010/5

N2 - Logistically controlling assembly areas is based on processing information. The availability of the required information is thus a decisive factor. This paper introduces an approach for controlling assembly areas. The method is based on processing information from so called Gentelligent® Parts. These parts can be used as storage mediums and as such are able to record, save, process and communicate information. Due to these properties, Gentelligent® Parts can function as a decentralized Enterprise Information System. As a result, extensive potential for improving logistic and technical processes arises along the product evolutionary process and during the usage phase.

AB - Logistically controlling assembly areas is based on processing information. The availability of the required information is thus a decisive factor. This paper introduces an approach for controlling assembly areas. The method is based on processing information from so called Gentelligent® Parts. These parts can be used as storage mediums and as such are able to record, save, process and communicate information. Due to these properties, Gentelligent® Parts can function as a decentralized Enterprise Information System. As a result, extensive potential for improving logistic and technical processes arises along the product evolutionary process and during the usage phase.

KW - Engineering

KW - production planning and control

KW - supply chain management

KW - intelligent manufacturing

UR - https://www.mendeley.com/catalogue/f4423620-5abe-3f05-a3d9-01842e86e0ca/

U2 - 10.1080/17509653.2010.10671092

DO - 10.1080/17509653.2010.10671092

M3 - Journal articles

VL - 5

SP - 59

EP - 64

JO - International Journal of Management Science and Engineering Management

JF - International Journal of Management Science and Engineering Management

SN - 1750-9661

IS - 1

ER -

Other publications by the same author(s)

Implementierung von Produktrückführungsprozessen in bestehende Produktionsabläufe: Herausforderungen und Anforderungen

Sandner, S., Nübel, M., Schulz, J., Metternich, J. & Schmidt, M., 20.06.2025, In: ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb. 120, 6, p. 397-403 7 p.

Research output: Journal contributions › Journal articles › Research › peer-review

Machine Learning For Determining Planned Order Lead Times In Job Shop Production: A Systematic Review Of Input Factors And Applied Methods

Wolter, F., Rokoss, A. & Schmidt, M., 2025, Conference on Production Systems and Logistics: University of San Ignacio de Loyola Lima, Peru, 18th – 21th March 2025, Proceedings. Herberger, D. & Hübner, M. (eds.). Offenburg: publish-Ing., p. 374-384 11 p. 32. (Proceedings of the ... Conference on Production Systems and Logistics; no. 7).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Understanding Resulting Interdependencies Within Production Planning And Control In Hybrid Manufacturing/Remanufacturing Systems

Schulz, J., Hofmann, H., Rokoss, A. & Schmidt, M., 05.2025, Proceedings of the Conference on Production Systems and Logistics: CPSL 2025: 18th – 21th March 2025, University of San Ignacio de Loyola Lima, Peru. Herberger, D. & Hübner, M. (eds.). Offenburg: publish-Ing., p. 114 - 126 13 p. (Proceedings of the ... Conference on Production Systems and Logistics; vol. 7).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Analysis of the relevance of models, influencing factors and the point in time of the forecast on the prediction quality in order-related delivery time determination using machine learning

Rokoss, A., Popkes, L. & Schmidt, M., 2024, Proceedings of the CPSL 2024. Herberger, D. & Hübner, M. (eds.). Hannover: publish-Ing., p. 415-431 17 p. (Proceedings of the Conference on Production Systems and Logistics; vol. 2024).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Case study on delivery time determination using a machine learning approach in small batch production companies

Rokoss, A., Syberg, M., Tomidei, L., Hülsing, C., Deuse, J. & Schmidt, M., 12.2024, In: Journal of Intelligent Manufacturing. 35, 8, p. 3937-3958 22 p.

Research output: Journal contributions › Journal articles › Research › peer-review

DOI

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