1. //
  2. Start
  3. //
  4. Publications
  5. A genetic algorithm for a self-learning ...
  6. Output formats
  7. //

A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly

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

Standard

A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly. / Busch, Jan; Quirico, Melissa; Richter, Lukas et al.
In: CIRP Annals - Manufacturing Technology, Vol. 64, No. 1, 2015, p. 5-8.

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

Harvard

Busch, J, Quirico, M, Richter, L, Schmidt, M, Raatz, A & Nyhuis, P 2015, 'A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly', CIRP Annals - Manufacturing Technology, vol. 64, no. 1, pp. 5-8. https://doi.org/10.1016/j.cirp.2015.04.044

APA

Busch, J., Quirico, M., Richter, L., Schmidt, M., Raatz, A., & Nyhuis, P. (2015). A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly. CIRP Annals - Manufacturing Technology, 64(1), 5-8. https://doi.org/10.1016/j.cirp.2015.04.044

Vancouver

Busch J, Quirico M, Richter L, Schmidt M, Raatz A, Nyhuis P. A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly. CIRP Annals - Manufacturing Technology. 2015;64(1):5-8. doi: 10.1016/j.cirp.2015.04.044

Bibtex

@article{7607604e84b04f6fb88ca1e31e9bf425,
title = "A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly",
abstract = "The aerodynamic feeding technology developed at the IFA allows feeding rates up to 800 parts per minute while maintaining high reliability and variant flexibility. The machine's setup procedure requires the adaptation of only four machine parameters. Currently, optimal parameter configurations need to be identified manually. This task is greatly time-consuming and requires a high level of expertise. Prospectively, the machine should utilize an algorithm that autonomously identifies optimal parameter configurations for new workpieces to realize fast setup procedures. This paper presents a genetic algorithm for a self-learning feeding system that has been validated in comprehensive simulation studies.",
keywords = "Algorithm, Assembly, Optimization, Engineering",
author = "Jan Busch and Melissa Quirico and Lukas Richter and Matthias Schmidt and Annika Raatz and Peter Nyhuis",
year = "2015",
doi = "10.1016/j.cirp.2015.04.044",
language = "English",
volume = "64",
pages = "5--8",
journal = "CIRP Annals - Manufacturing Technology",
issn = "0007-8506",
publisher = "Elsevier Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - A genetic algorithm for a self-learning parameterization of an aerodynamic part feeding system for high-speed assembly

AU - Busch, Jan

AU - Quirico, Melissa

AU - Richter, Lukas

AU - Schmidt, Matthias

AU - Raatz, Annika

AU - Nyhuis, Peter

PY - 2015

Y1 - 2015

N2 - The aerodynamic feeding technology developed at the IFA allows feeding rates up to 800 parts per minute while maintaining high reliability and variant flexibility. The machine's setup procedure requires the adaptation of only four machine parameters. Currently, optimal parameter configurations need to be identified manually. This task is greatly time-consuming and requires a high level of expertise. Prospectively, the machine should utilize an algorithm that autonomously identifies optimal parameter configurations for new workpieces to realize fast setup procedures. This paper presents a genetic algorithm for a self-learning feeding system that has been validated in comprehensive simulation studies.

AB - The aerodynamic feeding technology developed at the IFA allows feeding rates up to 800 parts per minute while maintaining high reliability and variant flexibility. The machine's setup procedure requires the adaptation of only four machine parameters. Currently, optimal parameter configurations need to be identified manually. This task is greatly time-consuming and requires a high level of expertise. Prospectively, the machine should utilize an algorithm that autonomously identifies optimal parameter configurations for new workpieces to realize fast setup procedures. This paper presents a genetic algorithm for a self-learning feeding system that has been validated in comprehensive simulation studies.

KW - Algorithm

KW - Assembly

KW - Optimization

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=84933677914&partnerID=8YFLogxK

U2 - 10.1016/j.cirp.2015.04.044

DO - 10.1016/j.cirp.2015.04.044

M3 - Journal articles

AN - SCOPUS:84933677914

VL - 64

SP - 5

EP - 8

JO - CIRP Annals - Manufacturing Technology

JF - CIRP Annals - Manufacturing Technology

SN - 0007-8506

IS - 1

ER -

Related by journal

Dynamic pricing of product and delivery time in multi-variant production using an actor critic reinforcement learning

Stamer, F. & Lanza, G., 01.2023, In: CIRP Annals. 72, 1, p. 405-408 4 p.

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

New concepts of extrusion dies to reduce the anisotropy of extruded profiles by means of additive manufacturing

Khalifa, N. B., Isakovic, J. & Bohlen, J., 2021, In: CIRP Annals. 70, 1, p. 231-234 4 p.

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

Incremental sheet forming with active medium

Ben Khalifa, N. & Thiery, S., 2019, In: CIRP Annals - Manufacturing Technology. 68, 1, p. 313-316 4 p.

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

Model-based logistic controlling of converging material flows

Nyhuis, P., Beck, S. & Schmidt, M., 01.01.2013, In: CIRP Annals - Manufacturing Technology. 62, 1, p. 431-434 4 p.

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

Reduction of capital tie up for assembly processes

Nyhuis, P., Schmidt, M. & Wriggers, F. S., 01.01.2008, In: CIRP Annals - Manufacturing Technology. 57, 1, p. 481-484 4 p.

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

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

Recently viewed

Activities

  1. A Coding Scheme to Analyse Global Text Processing in Computer Supported Collaborative Learning: What Eye Movements Can Tell Us
  2. What we know about conceptual learning in open inquiry settings in science education
  3. Theorizing about Financing Behavior of New Ventures: Towards an Effectual Logic
  4. CTRL + F_eminist futures: Hacking algorithmic architectures of cities to come
  5. Unboxing Uncertainties – Interrogating Forecasting and Foreclosing Future Infrastructures in the Amazon Town
  6. Workshop on the Exploration of Low Temperature plasma Physics - WELTPP 2019
  7. Predicting negotiation success with a multitude of negotiators’ inter-individual differences—a latent personality model of the successful negotiator
  8. Presentation: “Organizational Identity Formation in a Real Utopia: Provisional Identity and the Interplay between Desirable and Undesirable Futures”
  9. Effects of an international student exchange program on knowledge of international health care systems based on a real patient ́s case
  10. Probleme mit zukünftigen Generationen
  11. Workshop on the Exploration of Low Temperature plasma Physics - WELTPP 2018
  12. Teachers beliefs and goals concerning inquiry-based science
  13. 3rd Transalpine Organizing Creativity Paper Development Workshop
  14. Moderation der Arbeitsgruppe: "Qualitative Inhaltsanalyse"

Publications

  1. Derivative approximation using a discrete dynamic system
  2. OKBQA framework towards an open collaboration for development of natural language question-answering systems over knowledge bases
  3. Second language learners' performance in mathematics
  4. Applied quality assurance methods under the open source development model
  5. Temporal dynamics of conflict monitoring and the effects of one or two conflict sources on error-(related) negativity
  6. Users’ handedness and performance when controlling integrated input devices
  7. Differences in adjustment flexibility between regular and temporary agency work
  8. An innovative efficiency of incubator to enhance organization supportive business using machine learning approach
  9. ASSESS — automatic self-assessment using linked data
  10. Organizing Events for Configuring and Maintaining Creative Fields
  11. Blueprint of a smokescreen
  12. ShortPathQA
  13. The Plane of Obscurity — Simulation and Philosophy
  14. Biological Computer Laboratory
  15. From Feedback to Formative Guidance
  16. Exploring the uncanny valley effect in affective social robotics
  17. Operation B
  18. What drives the spatial distribution and dynamics of local species richness in tropical forest?
  19. Revidierbarkeit, ein Muster der Hypersphäre
  20. The development of an eco-label for software products
  21. Development of a Questionnaire Assessing Discomfort – The Disco-Scale
  22. Religious Loyality and Acceptance of Corruption.