Skip to main content
SpringerLink
Log in

Order-related acoustic characterization of production data

  • Original Paper
  • Published:
Logistics Research

Abstract

The conductor of an orchestra is able to distinguish not only between different instruments, but even among dozens of string players performing on instruments with similar sound qualities. Trained human ear not only is capable to highly differentiate between pitches and colors of sound, but also to localize the position, where the sound is coming from. This paper presents a parameter mapping sonification approach on production data, which is based on these human perceptual skills. Representatively for other logistic parameters, throughput times of orders are sonified and allocated in a sonic space. Additionally to auditory representations of the established resource and order oriented views in logistics, a third perspective is introduced, which displays the complete workflow of an order simultaneously as a multi-pitched spatial sound. Thus, causes and impacts of high throughput times in the data set example could be identified.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. http://www.icad.org.

  2. Playback speed of sonification can be set arbitrarily in the software.

  3. For confidential reasons, time-related information refers to neutral time unit.

  4. Fluctuations of work system 1 and 2 at least partly depended on incomplete data and therefore were not further considered.

  5. So to speak “acoustic fingerprints” of orders.

  6. The operation times (TOP) at the work systems were of comparable length and, given the overall duration of TTPs, negligible.

References

  1. Windt K, Philipp T, Böse F (2008) Complexity cube for the characterization of complex production systems. Int J Comput Integr Manuf 21(2):195–200

    Article  Google Scholar 

  2. Nyhuis P, Wiendahl H-P (2009) Fundamentals of production logistics. Springer, Berlin

    Book  Google Scholar 

  3. Choudhary AK, Harding JA, Tiwari MK (2008) Data mining in manufacturing: a review based on the kind of knowledge. J Intell Manuf 20(5):501–521

    Article  Google Scholar 

  4. Tukey JW (1977) Exploratory data analysis. Addison-Wesley, Reading, MA

    MATH  Google Scholar 

  5. Wainer H (2005) Graphic discovery: a trout in the milk and other visual adventures. Princeton University Press, Princeton

    Google Scholar 

  6. Iber M, Klein J, Windt K (2012) Die Grooving Factory, Logistische Datenanalyse im Klanglabor. In: Schoon A, Volmar A (eds) Das geschulte Ohr: Eine Kulturgeschichte der Sonifikation, 1st edn. Transcript, Bielefeld, pp 147–163

    Google Scholar 

  7. Gutenberg E (1983) Grundlagen der Betriebswirschaftslehre, Erster Band: Die Produktion, 24th edn. Springer, Berlin

    Google Scholar 

  8. Yu K-W (2001) Terminkennlinie, Eine Beschreibungsmethodik für die Terminabweichung im Produktionsbereich. VDI, Düsseldorf

    Google Scholar 

  9. Mizuyama H (2006) Artificial-neural-network-based MSQIM for exploratory analysis of manufacturing data. In: Proceedings of the 7 th Asia Pacific industrial engineering and management systems conference, 17–20 Dec 2006, Bangkok, Thailand, no. December, pp 10–19

  10. Windt K, Hütt M-T (2011) Exploring due date reliability in production systems using data mining methods adapted from gene expression analysis. CIRP Ann Manuf Technol 60(1):473–476

    Article  Google Scholar 

  11. Liao TW, Ting C-F, Chang P-C (2006) An adaptive genetic clustering method for exploratory mining of feature vector and time series data. Int J Prod Res 44(14):2731–2748

    Article  MATH  Google Scholar 

  12. Kramer G (1997) Sonification report: status of the field and research agenda. (Online). Available: http://www.icad.org. Accessed 19 Mar 2012

  13. Pereverzev SV, Loshak A, Backhaus S, Davis JC (1997) Quantum oscillations between two weakly coupled reservoirs of superfluid 3 He. Nature 388:449–452

    Article  Google Scholar 

  14. Frysinger SP (2005) A brief history of auditory data representation to the 1980s. In: First symposium on auditory graphs

  15. de Campo A, Dayé C, Frauenberger C, Vogt K, Wallscih A, Eckel G (2006) Sonification as an interdisciplinary working process. In: Proceedings of the 12th international conference on auditory display, pp 28–35

  16. Hermann T (2002) Sonification for exploratory data analysis. (Online). Available: http://pub.uni-bielefeld.de/pub?func=drec&id=2017263. Accessed 24 Feb 2012

  17. Wiendahl H-P (2008) Betriebsorganisation für Ingenieure. Carl Hanser Verlag, München und Wien

    Google Scholar 

  18. Gläsner J, Fastabend H Lecture presentation material of Institut für Fabrikanlagen (IFA), Leibniz University Hannover

Download references

Acknowledgments

The research of Prof. Dr.-Ing. Katja Windt is supported by the Alfried Krupp Prize for Young University Teachers of the Krupp Foundation. This project was initiated and supported by the research group “Rhythm” of The Young Academy at the Berlin-Brandenburg Academy of Sciences and Humanities and the German Academy of Natural Scientists Leopoldina: www.diejungeakademie.de.

Author information

Authors and Affiliations

  1. Jacobs University Bremen, Campus Ring 1, 28759, Bremen, Germany

    M. Iber & K. Windt

Authors
  1. M. Iber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Windt
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Iber.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Iber, M., Windt, K. Order-related acoustic characterization of production data. Logist. Res. 5, 89–98 (2012). https://doi.org/10.1007/s12159-012-0084-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12159-012-0084-y

Keywords

Search

Navigation