Zusammenfassung
In times of aggravating competition in the logistics industry, organizations need to distinguish themselves and enhance their logistics performance. Responsiveness to critical situations and deviations from plan serves exactly this goal as it may lead to measurable improvements in business performance. However, meaningful data needed to exploit and enhance this capability may reside in several widespread sources. Identifying and utilizing such sources can be pivotal on an organization’s path to survival and success on the market. Using smarter approaches to logistics is such a path. Cyber-physical systems and complex event processing may be adequate technological means to aspire for the transition towards smart logistics systems and processes.
Our contribution introduces enhanced techniques to engineer event-driven CPS with the ePoEM model. This allows to identify value-adding sensors, respective measurement and data models, and rules of event detection and reaction. A case study covering picking and distribution processes in a typical consigner company demonstrates how to add value with event processing and move towards smart logistics networks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Literatur
[1] M. Treiber and A. Kesting, Verkehrsdynamik und -simulation (Daten, Modelle und Anwendungen der Verkehrsflussdynamik), Berlin Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.
[2] N. G.F., “A simplified car-following theory: a lower order model.,” Institute of Transportation Studies, University of California, Berkeley, 2002.
[3] W. Jin, Traffic Flow Models and their Numerical Soluations. PhD, California: University of California, 2000.
[4] P. D. H. R. Schwarz and. P. D. N. Köckler, Numerische Mathematik, Wiesbaden: Vieweg+Teubner Verlag, 2011.
[5] M. Treiber, A. Hennecke and D. Helbing, “Congested traffic states in empirical observations and microscopic simulations,” 2000.
[6] Ministerium für Bauen, Wohnen, Stadtentwicklung und Verkehr, “https://www.verkehr.nrw/,” 20 07 2017. [Online]. Available: https://www.verkehr.nrw/.
[7] M. S. K. Nagel, “A cellular automaton model for freeway traffic,” in J. Phys. I France, 1992.
[8] PREMIUM, “Plug-In, Range-Extender, und Elektrofahrzeuge unter realen Mobilitätsumständen: Infrastruktur, Umweltbedingungen und Marktakzeptanz,” http://www.premium.uni-passau.de/das-projekt/, 2017.
[9] RUHRAUTOe, “RUHRAUTOe,” http://www.ruhrauto-e.de/, 2017.
[10] colognE-mobil, “colognE-mobil - Elektromobilitätslösungen für NRW,” http://colognemobil.de/, 2017.
[11] K. Reif, Kraftfahrzeug-Hybridantriebe, Vieweg+Teubner Verlag, 2012.
[12] UN/ECE, “Regelung Nr. 101 der Wirtschaftskommision der Vereinten Nationen für Europa,” 2012.
[13] M. Koppers and P. Driesch, “Simulationsgestützte Analyse verschiedener (teil-) elektrifizierter Antriebsvarianten für Pkw unter realen Betriebsbedingungen,” in Beiträge der 8. GMM-Fachtagung, Dortmund, VDA-Verlag, 2017, pp. 159-164.
[14] C. Bishop, Pattern Recognition and Machine Learning, New York: Springer-Verlag, 2006.
[15] V. Nair and G. E. Hinton, “Rectified linear units improve restricted boltzmann machines,” in Proceedings of the 27th International Conference on Machine Learning, Haifa, 2010.
[16] T. Hastie, R. Tibshirani and J. Friedman, The Elements of Statistical Learning, New York: Springer-Verlag, 2009.
[17] E. A. Lee, “CPS foundations,” in DAC, 2010 47th ACM IEEE, 2010.
[18] D. Uckelmann, “A Definition Approach to Smart Logistics,” in Next Generation Teletraffic and Wired/Wireless Advanced Networking, Berlin/Heidelberg, Germany, 2008.
[19] E. Fleisch, O. Christ and M. Dierkes, “Die betriebswirtschaftliche Vision des Internets der Dinge,” in Das Internet der Dinge. Ubiquitous Computing und RFID in der Praxis: Visionen, Technologien, Anwendungen, Handlungsanleitungen., Berlin, Germany, Springer, 2005, p. 3–37.
[20] F. Straube, “Smarte Technologien in der Logistik,” [Online]. Available: http://www.bvl.de/wissen/logistik-bereiche/smarte-logistik.
[21] B. Scholz-Reiter, K. Windt and M. Freitag, “Autonomous logistic processes: new demands and first approaches,” in Digital enterprises, production networks, Budapest, Hungary, 2004.
[22] B. Scholz-Reiter, M. Freitag and O. Herzog, “Selbststeuerung logistischer Prozesse – Ein Paradigmenwechsel und seine Grenzen,” Industrie Management, p. 23–27, 2004.
[23] T. van Woensel, “Smart Logistics,” in Inaugural lecture, Eindhoven, The Netherlands, 2012.
[24] E. Hofmann and M. Rüsch, “Industry 4.0 and the current status as well as future prospects on logistics,” Computers in Industry, p. 23–34, 2017.
[25] W. Kersten, M. Seiter, B. v. See, N. Hackius, C. Rosentritt, C. Böhle, G. Reich, T. Maurer and R. Sauter, “Trends und Strategien in Supply Chain Management und Logistik – Chancen der digitalen Transformation,” in Den Wandel gestalten. Driving change., Hamburg, Germany, 2016.
[26] C. Alias, Y. Kalkan, E. Koc and B. Noche, “Enabling Improved Process Control Opportunities by Means of Logistics Control Towers and Vision-Based Monitoring,” in ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1B: 34th Computers and Information in Engineering Conference., Buffalo (NY), USA, 2014.
[27] C. Alias, V. Lederman Rawet, H. X. Ratton Neto and J. d. E. Neirão Reymão, “Investigating into the Prevalence of Complex Event Processing and Predictive Analytics in the Transportation and Logistics Sector: Initial Findings from Scientific Literature,” in Proceedings of the 10th Mediterranean Conference on Information Systems 2016 (MCIS 2016), Paphos, Cyprus, 2016.
[28] C. Alias, Ç. Özgür and B. Noche, “Monitoring production and logistics processes with the help of industrial image processing,” in Proceedings of the 27th Annual POMS Conference 2016, Orlando (FL), USA, 2016.
[29] C. Alias, Ç. Özgür, Q. Yang and B. Noche, “A System of Multi-Sensor Fusion for Activity Monitoring of Industrial Trucks in Logistics Warehouses,” in ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1B: 35th Computers and Information in Engineering Conference., Boston (MA), USA, 2015.
[30] Ç. Özgür, C. Alias and B. Noche, “Comparing sensor-based and camera-based approaches to recognizing the occupancy status of the load handling device of forklift trucks,” Logistics Journal, 2016.
[31] P. Leitao, A. W. Colombo and S. Karnouskos, “Industrial automation based on cyberphysical systems technologies: Prototype implementations and challenges,” Computers in Industry, 2015.
[32] C. Talcott, “Cyber-physical systems and events,” in Lecture Notes in Computer Science, 2008.
[33] D. C. Luckham, “A Short History of Complex Event Processing Part 3: the formative years,” Business, pp. 2-7, 2008.
[34] Research and Markets, “Complex Event Processing Market by Application,” Februar 2016. [Online]. Available: http://www.researchandmarkets.com/reports/3616997/complex-event-processing-market-by-application. [Accessed 7 April 2017].
[35] F. Saglietti, D. Fohrweiser, S. Winzinger and R. Lill, “Model-Based Design and Testing of Decisional Autonomy and Cooperation in Cyber-Physical Systems,” in SEAA, 2015.
[36] M. Book, V. Gruhn and R. Striemer, Tamed Agility, Springer, 2016.
[37] J. Ollesch, M. Hesenius and V. Gruhn, “Engineering Events in CPS - Experiences and Lessons Learned (in press),” in 3rd International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS’17) in conjunction with ICSE 2017, Buenos Aires, 2017.
[38] O. P. Patri, V. S. Sorathia, A. V. Panangadan and V. K. Prasanna, “The process-oriented event model (PoEM): a conceptual model for industrial events,” in Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, 2014.
[39] M. Book, V. Gruhn and R. Striemer, Tamed Agility, Heidelberg: Springer, 2016.
[40] C. Alias, C. Ozgur, M. Jawale and B. Noche, “Analyzing the potential of Future-Internetbased logistics control tower solutions in warehouses,” in Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, Qingdao, China PR, 2014.
[41] Google Inc., “Google Maps,” [Online]. Available: www.google.de/maps.
[42] C. Alias, M. Jawale, A. Goudz and B. Noche, “Applying Novel Future-Internet-Based Supply Chain Control Towers to the Transport and Logistics Domain,” in ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis. Volume 3: Engineering Systems; Heat Transfer and Thermal Engineering; Materials and Tribology; Mechatronics; Robotics, Copenhagen, Denmark, 2014.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Fachmedien Wiesbaden GmbH
About this chapter
Cite this chapter
Ollesch, J., Hesenius, M., Gruhn, V., Alias, C. (2018). Real-time Event Processing for Smart Logistics Networks. In: Proff, H., Fojcik, T. (eds) Mobilität und digitale Transformation. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-20779-3_32
Download citation
DOI: https://doi.org/10.1007/978-3-658-20779-3_32
Published:
Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-20778-6
Online ISBN: 978-3-658-20779-3
eBook Packages: Business and Economics (German Language)