Use Cases

So far we have described the general concept of the Smart Spare Part as well as the potential technological foundation. In order to show the value of the proposed approach, we show two practical examples which have been developed after interviews with experts working in the respective fields.

6.1 Flowmeters

The flowmeter market is very mature and saturated. Even in the brownfield area, there is a massive price battle. As a result, the feeling prevails that only by providing highly efficient service the market share can be maintained. A Smart Spare Part would provide the right tool set to meet this goal.

Unique Challenges: A key problem in the flowmeter market is obsolescence. Many installed meters are no longer available from their vendors and thus have to be replaced with newer models. However, such a replacement is rarely straightforward and requires an upgrade kit. If the proper kit is not taken to the customer site, the upgrade cannot be performed on the first visit.

Smart Spare Solution: As mentioned before, the Smart Spare Part provides installed base transparancy by collection and storing information about the customer’s assets. Using information about product versions owned by the customer, smart flowmeters can automatically order upgrade kits when they themselves are ordered for a particular customer.

During installation, the part will provide relevant information that helps the technician to apply the upgrade kit properly.

Since the parts understand the complexity of the installed base and the effects of obsolescence, they can use this information to plan their migration between warehouses. Such an automated parts migration can enable time-efficient delivery of parts to the customers.

Finally, the parts maximize their shelf life by complaining about wet storage conditions.

6.2 Low Voltage Motors

Low voltage motors are a common-place piece of equipment and thus it is easy for customers to switch loyalty. Also, they are produced and sold in larger quantities to improvement, so improvements to the spare unit business have a high savings potential. For these reasons, they are an interesting use case for the Smart Spare Part.

Unique Challenges: Low voltage motors are products which need maintenance even while in the warehouse, i.e. their shafts have to be turned periodically. They can suffer damage during transportation, e.g. through jolts and extreme temperatures below zero. If damage during transportation is not noticed, replacement units might fail quickly after installation. Finally, installation of motors requires some care, e.g. misalignment can lead to damage quickly.

Smart Spare Solution: The sensor and analytics capabilities of the smart spare parts (in this case spare motors) maximize shelf life by ensuring that the motor is properly maintained.

Since the maintenance schedule is tied directly to the motor, even complex journeys through the supply chain will not result in missed maintenance activity. Similarly, transportation incidents will be recorded and can be used to assess whether a motor should be scrapped in order to avoid warranty issues and loss of customer confidence. During installation the motor will provide information as to whether the motor is correctly installed, e.g. by checking the alignment.

7. Conclusions

In this paper we have presented a vision for a Smart Spare Part which addresses several key challenges in today’s spare parts logistics and use in service. We have further illustrated those challenges with use cases from two different domains. Our proposed concept in return raises a series of technical challenges which are identified in this paper and contrasted with the state of the art. While our vision is quite radical in some respects, it can be seen that its foundations

already exist today and with the roadmap laid out, work can commence on the foundation of a Smart Spare Part infrastructure.

References

Aberdeen Group (2012): “Analyst Insight Convergence 2012 People and Parts Linked Together to Solve Customer Issues.” http://www.aberdeen.com/Aberdeen-Library/8257/AI-service-parts-operations.aspx

D. Anicic, P. Fodor, S. Rudolph, R. Stühmer, N. Stojanovic und R. Studer (2010): “A Rule-Based Language for Complex Event Processing and Reasoning,” In: RR 2010: Proceedings of the Fourth International Conference on Web Reasoning and Rule Systems, Italy

D. Anicic, P. Fodor, S. Rudolph, N. Stojanovic (2011): “EP-SPARQL: Unified Language for Event Processing and Stream Reasoning,” In: WWW 2011: Proceedings of the Twentieth International World Wide Web Conference, India.

H. Biedermann (Hrsg.) (2007): „Wertschöpfendes Instandhaltungs- und Produktionsmanagement Erfolgreich durch Innovationen in Management und Technologie“, TÜVMedia, 2007

M. Botts und A. Robin (2007): “OpenGIS sensor model language (SensorML) implementation specification“. OpenGIS Implementation Specification OGC (2007): 07–000.

Christian Decker, Till Riedel, Michael Beigl, De Souza, Spiess, Muller, Haller (2007):

Collaborative business items, 3rd IET International Conference on Intelligent Environments IE 07(531 CP), p. 40-47,

C. Emmanouilidis (2009): “A Wireless Sensing Development Platform for Ubiquitous Condition Monitoring.” In: Proceedings of the 22nd International Congress on Condition Monitoring and Diagnostic, Engineering Management.

N. Fantana, und T. Riedel (2009): “Servicing industrial machinery: Challenges using wireless identification and networked sensing systems.” In: Networked Sensing Systems (INSS), 2009 Sixth International Conference on, 1-4.

Stephan Grimm, Michael Watzke, Thomas Hubauer, Falco Cescolini (2012) "Embedded EL+

Reasoning on Programmable Logic Controllers", In: International Semantic Web Conference (ISWC), pp.

66-81, 2012

E. Geisberger und Broy (2012): „Cyber-Physical Systems—Wissenschaftliche Herausforderungen bei der Entwicklung“. Cyber-Physical Systems (2012), S. 17–31.

R. Gitzel, I. Harjunkoski und C. Pinto (2012): “Stock Pooling Optimization“ In: ABB Review 4/2012, pp.

30.

R. Gitzel (2013): “Round Table Discussion What is the Impact of Uncertainty and Lack of Information on Spare Parts Logistics?” In: “Optimizing the International Spare Parts Management in the Machinery Industry”, Berlin, 24-25.1.2013

I. Horrocks, P. F. Patel-Schneider, F. Van Harmelen (2003): “From SHIQ and RDF to OWL: The making of web ontology language.” In: Web Semantics, 1(1), pp. 7-26

InDiNet (2013):http://www.software-cluster.com/de/forschung/projekte/verbundprojekte/indinet F. Jammes und H. Smit (2005): “Service-oriented paradigms in industrial automation,” In: IEEE Transactions on Industrial Informatics, vol. 1, 2005, pp. 62ff.

L. Krishnamurthy, R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, N. Kushalnagar, L. Nachman, und M. Yarvis M. (2005): “Design and deployment of industrial sensor networks: experiences from semiconductor plant and the north sea.” In: Proceedings of the SenSys '05. ACM, New York, NY, USA, 64-75

M. Loskyll, I. Heck, J. Schlick, M. Schwarz (2012): Context-Based Orchestration for Control of Resource-Efficient Manufacturing Processes. Future Internet, Vol. 4, Nr. 3, S. 737-761.

David Luckham(2002) The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley, Reading, MA, USA.

W. Männel (Hrsg.) (2001): „Tagungsband der Fachtagung Instandhaltung.“ Verlag der GAB, Lauf an der Pregnitz

N. D. Mexis (2004): „Die Philosophie der Instandhaltung.“, Institut für Analytik und Schwachstellenforschung, Mannheim, 2004.

RAN Projekt:http://www.autoran.de/

T. Riedel, N. Fantana, A. Genaid, D. Yordanov, H. Schmidtke, M. Beigl (2010), “Using Web Service Gateways and Code Generation for Sustainable IoT System Development”, Internet of Things 2010 Second International Conference for Academia and Industry (IOT2010)

Spyns, P., Meersman, R., Jarrar, M. (2002): “Data modelling versus ontology engineering.” In: SIGMOD Record, 31(4), pp. 12-17, 2002.

VDI/VDEh (2010): Einleitungsrede des 31. VDI VDEh Forums Instandhaltung 2010 "Effizienz im Anlagenmanagement"

W3C (2004): „Resource Description Framework (RDF): Concepts and Abstract Syntax“, online at:

http://www.w3.org/TR/2004/REC-rdf-concepts-20040210/