Abstract
Information Technology (IT) support in the manufacturing sector has reached a watershed with digital components beginning to permeate all products and processes. The classical divide between “technical” IT and “business” IT begins to blend more and more. Data from design, manufacturing, product use, service, and support is made available across the complete product lifecycle and supply chain. This goes hand in hand with the diffusion of sensor and identification technology and the availability of relevant information streams on the customer side—leading to unprecedented amounts of data. The challenge is to purposefully apply emerging BI concepts for a comprehensive decision support that integrates product and shop floor design phases, the steering and design of operational industrial processes, as well as big and unstructured data sources. This chapter brings those pieces together in order to derive an integrated framework for management and decision support in the manufacturing sector.
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
References
ActionPlanT: ICT for manufacturing—the ActionPlanT roadmap for manufacturing 2.0 (2012). Available via http://www.actionplant-project.eu/public/documents/roadmap.pdf. Accessed 25th July 2012
Alter, A.: Business intelligence—are your BI systems making you smarter? CIO Insight 05/2003, 77–85 (2003)
Baars, H., Kemper, H.G.: Management support with structured and unstructured data—an integrated business intelligence framework. Inf. Syst. Manag. 25(2), 132–148 (2008)
Baars, H., Kemper, H.G.: Ubiquitous computing—an application domain for business intelligence in the cloud? In: Proceedings of the 17th Americas Conference on Information Systems (AMCIS), USA (2011)
Baars, H., Qie, L.: BI in the Cloud – Die Cloud als neuer Ansatz zur Erhöhung der BI-Agilität? BI Spektrum 7(2), 26–29 (2012)
Baars, H., Sun, X.: Multidimensional analysis of RFID data in logistics. In: Proceedings of the 42th Hawaii International Conference on System Sciences (HICSS-42), USA (2009)
Baars, H., Gille, D., Strüker, J.: Evaluation of RFID applications for logistics: a framework for identifying, forecasting and assessing benefits. Eur. J. Inf. Syst. (EJIS) 18(6), 578–591 (2009)
Baars, H., Kemper, H.G., Lasi, H., Siegel, M.: Combining RFID technology and business intelligence for supply chain optimization—scenarios for retail logistics. In: Proceedings of the 41th Hawaii International Conference on System Sciences (HICSS-41), USA (2008)
Bottani, E., Bertolini, M., Montanari, R., Volpi, A.: RFID-enabled business intelligence modules for supply chain optimization. Int. J. Technol.: Res. Appl. 1(4), 253–278 (2009)
Brinkmann, A., Effert, S., Heidebuer, M., Vodisek, M., Baars, H.: An integrated architecture for business intelligence support from application down to storage. In: Proceedings of the 3rd International Workshop on Storage Network Architecture and Parallel I/Os, Saint Louis, USA (2005)
Bucher, T., Gericke, A.: Process-centric business intelligence. Bus. Process. Manag. J. 15(3), 408–429 (2009)
Cattell, R.: Scalable SQL and NoSQL data stores. SIGMOD Rec. 39(4), 12–27 (2010)
Cho, D.Y.: Ubiquitous data warehouse—integrating RFID with multidimensional online analysis. In: Proceedings of the San Diego International Systems Conference, San Diego (2005)
Chow, H.K.H., Choy, K.L., Lee, W.B., Chan, F.T.S.: Design of a knowledge-based logistics strategy system. Expert Syst. Appl. 29, 272–290 (2005)
Curtin, J., Kauffman, R.J., Riggins, F.J.: Making the ‘Most’ out of RFID technology: a research agenda for the study of the adoption, usage and impact of RFID. Inf. Technol. Manag. 8(2), 87–110 (2007)
Dayal, U., Hsu, M., Ladin, R.: Business process coordination: state of the art, trends, and open issues. In: Proceedings of the 27th International Conference on Very Large Data Bases (VLDB), Italy (2001)
Eckerson, W.E.: Best practices in operational BI—converging analytical and operational processes. In: TDWI best practice report, 3rd quarter 2007 (2007)
Ehrlenspiel, K.: Integrierte Produktentwicklung, 3rd edn. Hanser, München (2007)
Eigner, M., Stelzer, R.: Product Lifecycle Management, 2nd edn. Springer, Heidelberg (2009)
Fleisch, E.: What is the internet of things? An economic perspective. In: Auto-ID Labs white paper (WP-BIZAPP-053), Auto-ID Labs, St. Gallen (2010)
Giannakakis, T., Vosniakos, G.C.: Sheet metal cutting and piercing operations planning and tools configuration by an expert system. Int. J. Adv. Manuf. Technol. 36(7–8), 658–670 (2008)
Golfarelli, M., Rizzi, S., Cella, I.: Beyond data warehousing: what’s next in business intelligence? In: Proceedings of the 7th ACM International Workshop on Data Warehousing and OLAP, USA (2004)
Grigoria, D., Casatib, F., Castellanosb, M., Dayalb, U., Sayalb, M., Shan, S.C.: Business process intelligence. Comput. Ind. 53, 321–343 (2004)
GS1: EPCglobal standards (2012). Available via http://www.gs1.org/gsmp/kc/epcglobal. Accessed 25 July 2012
Günther, O., Kletti, W., Kurbach, U.: RFID in Manufacturing. Springer, Heidelberg (2008)
Jacobs, A.: The pathologies of big data. Commun. ACM 52(8), 36–44 (2009)
Kemper, H.G., Baars, H.: From data warehouses to transformation hubs—a conceptual architecture. In: Proceedings of the 17th European Conference on Information Systems (ECIS), Italy (2009)
Kemper, H.G., Baars, H., Mehanna, W.: Business Intelligence – Grundlagen und praktische Anwendungen, 3rd edn. Vieweg, Wiesbaden (2010)
Kendal, S.: An Introduction to Knowledge Engineering. Springer, London (2007)
Klawans, B.: Embedded or conventional BI—determining the right combination of BI for your business. Bus. Intell. J. 13(1), 30–36 (2008)
Kletti, J.: Manufacturing Execution System: MES. Springer, Heidelberg (2007)
Koch, M., Baars, H., Lasi, H., Kemper, H.G.: Manufacturing execution systems and business intelligence for production environments. In: Proceedings of the 16th Americas Conference on Information Systems, Peru (2010)
Lasi, H.: Industrial intelligence—a BI-based approach to enhance manufacturing engineering in industrial companies. In: Proceedings of the 8th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME), Italy (2012)
Lasi, H.: Decision support within knowledge-based engineering—a business intelligence-based concept. In: Proceedings of the 18th Americas Conference on Information Systems (AMCIS), USA (2012)
Lasi, H., Hollstein, P., Kemper, H.G.: Heterogeneous IT landscapes in innovation processes—an empirical analyses of integration approaches. In: Proceedings of the International Conference Information Systems (IADIS), Portugal (2010)
Lyytinnen, K., Yoo, Y.: Issues and challenges in ubiquitous computing. Commun. ACM 45(12), 42–65 (2002)
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big Data: the Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute (2011)
Marjanovic, O.: The next stage of operational business intelligence: creating new challenges for business process management. In: Proceedings of the 40th Annual Hawaii International Conference on System Sciences. IEEE Comput. Soc., New York (2007)
Mell, P., Grance, T.: The NIST definition of cloud computing. National Institute of Standards and Technology, Special Publication 800-145 (2011)
Platter, H.: A common database approach for OLTP and OLAP using an in-memory column database. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, Providence, USA (2009)
Plattner, H., Zeier, A.: In-Memory Data Management: An Inflection Point for Enterprise Applications. Springer, Heidelberg (2011)
Pourshahid, A., Chen, P., Amyot, D., Weiss, M., Forster, A.J.: Business process monitoring and alignment: an approach based on the user requirements notation and business intelligence tools. In: Proceedings of the 10th Workshop of Requirement Engineering, Canada, pp. 149–159 (2007)
Röhner, S., Breitsprecher, T., Wartzack, S.: Acquisition of design-relevant knowledge within the development of sheet-bulk metal forming. In: Proceedings of the International Conference on Engineering Design (ICED11), Denmark (2011)
Song, M., van der Aalst, W.M.P.: Towards comprehensive support for organizational mining. Decis. Support Syst. 46(11), 300–317 (2008)
Strauch, C.: NoSQL databases (2011). Available via http://www.christof-strauch.de/nosqldbs.pdf. Accessed 25 July 2012
Thomson, W.J.J., van der Walt, J.S.: Business intelligence in the cloud. South African J. Inf. Manag. 12(1), 1–5 (2010)
van der Aalst, W.M.P., Weijters, J.M.M.: Process mining: a research agenda. Comput. Ind. 53(3), 231–244 (2004)
Weber, P.: Digital Mock-up im Maschinenbau. Shaker, Aachen (2003)
Weiser, M.: Ubiquitous computing (1996). Available via: http://sandbox.xerox.com/ubicomp. Accessed 25th July 2012
zur Mühlen, M.: Process-driven management information systems—combining data warehouses and workflow technology. In: Proceedings of the 4th International Conference on Electronic Commerce Research (ICECR-4), USA, pp. 550–566 (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
Kemper, HG., Baars, H., Lasi, H. (2013). An Integrated Business Intelligence Framework. In: Rausch, P., Sheta, A., Ayesh, A. (eds) Business Intelligence and Performance Management. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-4866-1_2
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4866-1_2
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4865-4
Online ISBN: 978-1-4471-4866-1
eBook Packages: Computer ScienceComputer Science (R0)