Choosing Identification Technologies for Implementation of Traceability in order to Increase Overall Equipment Effectiveness

Abstract:

Article Preview

Increasing the overall equipment effectiveness is a major task in order to further improve productive times and thereby increase energy efficiency. One main reason for ``energy waste" besides inefficient machinery is spending energy on production or assembly of ultimately rejected parts. In order to decrease this kind of waste, traceability can be applied for identifying components and observing related parameters for detecting quality deviations in early states.Here, we show the required identification technologies in order to establish a traceability concept for assembly of discrete units. Evaluating existing techniques regarding their applicability depending on various constraints, is a major task when planning the traceability system. Therefore, we assessed different technologies generically to give hints for choosing techniques to consider. As known technologies often are accompanied by variable costs, additionally an efficient solution for low-value bulk goods is required. We describe some technical possibilities in order to enable implementation of a holistic traceability system.The given evaluation may be applied as basis for detailed investigations regarding technologies to use for identification of discrete objects in order to implement traceability. Through implementation of such measures significant scrap reduction and thereby an improvement of energy efficiency in various applications is possible. Nevertheless, further research may be taken on efficiently identifying low-value bulk goods.

Info:

Periodical:

Edited by:

Jörg Franke, Sven Kreitlein, Gunther Reinhart, Christian Gebbe, Rolf Steinhilper and Johannes Böhner

Pages:

87-96

Citation:

L. Baier et al., "Choosing Identification Technologies for Implementation of Traceability in order to Increase Overall Equipment Effectiveness", Applied Mechanics and Materials, Vol. 871, pp. 87-96, 2017

Online since:

October 2017

Export:

Price:

$41.00

* - Corresponding Author

[1] Kraftfahrt-Bundesamt, Jahresbericht 2013/2014, Flensburg, (2015).

[2] F. Böse, D. Uckelmann, Von der Chargenverfolgung zur Produktverfolgung-Veränderungen in der logistischen Rückverfolgung auf Basis innovativer Identifikationstechnologien, in: Chargenverfolgung: Möglichkeiten, Grenzen, Anwendungsgebiete, ed. by C. Engelhardt-Nowitzki, E. Lackner, 1. Aufl, Leobener Logistik Cases, Wiesbaden: Dt. Univ. -Verl, 2006, pp.133-148.

DOI: https://doi.org/10.1007/978-3-8350-9482-6_9

[3] G. Reimann, S. Zimmermann, TraceabilityAls Basis Für Industrie 4. 0, in: VDMA-Nachrichten, no. 1, (2016), pp.13-32.

[4] Landesamt für Statistik, Energieverbrauch Der Bayerischen Industrie 2014 Leicht Gesunken, München, (2015).

[5] Statistisches Bundesamt, Verarb. Gewerbe, Bergbau, Gew. v. Steinen u. Erden: Produktionswert und Unternehmen der Vierteljährlichen Produktionserhebung: Deutschland, Jahre, Güterverzeichnis (2-/4-Steller), (2015).

[6] S. Wegner-Hambloch, ed., Rückverfolgbarkeit in der Praxis: Artikel 18 und 19 der VO (EG) Nr. 178/2002 schnell und einfach umgesetzt, 1. Aufl., 1., überarb. Nachdr, Hamburg: Behr, (2005).

[7] E. Goldberg, Statistical Machine, US1838389 A, (1931).

[8] J. H. Munson, Experiments in the Recognition of Hand-Printed Text, Part I: Character Recognition, in: Proceedings of the December 9-11, 1968, Fall Joint Computer Conference, Part II, ACM, (1968), pp.1125-1138.

DOI: https://doi.org/10.1145/1476706.1476735

[9] J. Mantas, An Overview of Character Recognition Methodologies, in: Pattern recognition, volume 19, no. 6, (1986), pp.425-430.

DOI: https://doi.org/10.1016/0031-3203(86)90040-3

[10] N. Arica, F. T. Yarman-Vural, Optical Character Recognition for Cursive Handwriting, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 24, no. 6, (2002), pp.801-813.

DOI: https://doi.org/10.1109/tpami.2002.1008386

[11] N. J. Woodland, B. Silver, Classifying Apparatus and Method, US2612994 A, (1952).

[12] H. Kato, K. T. Tan, Pervasive 2D Barcodes for Camera Phone Applications, in: IEEE Pervasive Computing, volume 6, no. 4, (2007), pp.76-85.

DOI: https://doi.org/10.1109/mprv.2007.80

[13] K. A. H. Nurwono, R. Kosala, Color Quick Response Code for Mobile Content Distribution, in: Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia, ACM, (2009), pp.267-271.

DOI: https://doi.org/10.1145/1821748.1821799

[14] F. C. Parry, Identification Card, in: IBM Technical Disclosure Bulletin, volume 3, no. 6, (1960), p.8.

[15] R. Moreno, Procédé et Dispositif de Commande Électronique, FR2266222, (1974).

[16] M. W. Cardullo, W. L. Parks, Transponder Apparatus and System, US3713148 A, (1973).

[17] R. Want, An Introduction to RFID Technology, in: IEEE Pervasive Computing, volume 5, no. 1, (2006), pp.25-33.

[18] D. Paunescu, W. J. Stark, R. N. Grass, Particles with an Identity: Tracking and Tracing in Commodity Products, in: Powder Technology, volume 291, (2016), pp.344-350.

DOI: https://doi.org/10.1016/j.powtec.2015.12.035

[19] R. N. Grass et al., Robust Chemical Preservation of Digital Information on DNA in Silica with Error-Correcting Codes, in: Angewandte Chemie International Edition, volume 54, no. 8, (2015), pp.2552-2555.

DOI: https://doi.org/10.1002/anie.201411378

[20] P. K. Lee, Method of Tagging with Color-Coded Microparticles, US4053433 A, (1977).

[21] R. Ishiyama, Y. Kudo, T. Takahashi, mIDoT: Micro Identifier Dot on Things-A Tiny, Efficient Alternative to Barcodes, Tags, or Marking for Industrial Parts Traceability, in: Industrial Technology (ICIT), 2016 IEEE International Conference On, IEEE, (2016).

DOI: https://doi.org/10.1109/icit.2016.7474850

[22] T. Baque, Method of Authenticating and/or Identifying an Article, US8590800 B2, (2013).

[23] R. Cowburn, Laser Surface Authentication - Reading Nature's Own Security Code, in: Contemporary Physics, volume 49, no. 5, (2008), pp.331-342.

DOI: https://doi.org/10.1080/00107510802583948

[24] P. de Groot, L. Deck, Surface Profiling byAnalysis of White-Light Interferograms in the Spatial Frequency Domain, in: Journal of Modern Optics, volume 42, no. 2, (1995), pp.389-401.

DOI: https://doi.org/10.1080/09500349514550341

[25] J. Seewig, T. Böttner, D. Broschart, Uncertainty of Height Information in Coherence Scanning Interferometry, in: SPIE Proceedings, Optical Measurement Systems for Industrial Inspection VII, volume 8082, (2011), p. 80820V.

DOI: https://doi.org/10.1117/12.889796

[26] J. W. Goodman, Introduction to Fourier Optics, Roberts and Company Publishers, (2005).

[27] B. J. Pernick, Surface Roughness Measurements with an Optical Fourier Spectrum Analyzer, in: Applied optics, volume 18, no. 6, (1979), pp.796-801.

DOI: https://doi.org/10.1364/ao.18.000796

[28] N. Saum et al., Oberfläche so Einzigartig Wie Der Fingerabdruck, in: Qualität und Zuverlässigkeit, volume 61, no. 4, (2016), pp.113-115.

[29] F. Mauren, Veränderliche Merkmalswerte von Rohteilen in Der Spanenden Fertigung, Technische Universität Kaiserslautern, (2008).