Conceptual Considerations for Real-Time Supply Chain Efficiency Monitoring

• Autorzy: Winkler H.

Identyfikatory

DOI

10.21008/j.2083-4950.2016.6.5.2

• Języki publikacji: EN

Abstrakty

EN

A recent simulation study proved that the efficiency of supply chains is highly volatile because of a number of different factors. Therefore, we elaborated a model to evaluate supply chain efficiency. In our contribution, we will show the results of a case study and present considerations for real-time efficiency monitoring.

Słowa kluczowe

EN

supply chain; efficiency; simulation; real-time monitoring

• Wydawca: Publishing House of Poznan University of Technology
• Czasopismo: Research in Logistics & Production
• Rocznik: 2016
• Tom: Vol. 6, No. 5
• Strony: 393--405
• Opis fizyczny: Bibliogr. 14 poz., fig.

Twórcy

autor

Winkler H.

• Department Production/Operations Management, Brandenburg University of Technology Cottbus-Senftenberg, Siemens-Halske-Ring 6, 03046 Cottbus, Germany

Bibliografia

• 1. Braglia M., Frosolini M. & Zammori F. (2009), Overall equipment effectiveness of a manufacturing line (OEEML), An integrated approach to assess systems performance, Journal of Manufacturing Technology Management, Vol. 20(1), pp. 8–29.
• 2. Cerami E. (2002), Web Services Essentials, O’Reilly, Sebastopol.
• 3. Cutting-Decelle A.F., Barraud J.L., Veenendaal B. & Young R.I. (2012), Production information interoperability over the Internet, A standardized data acquisition tool developed for industrial enterprises, Computers in Industry Vol. 63(8), pp. 824–834.
• 4. Daigneau R. (2012), Service Design Patterns – Fundamental Design Solutions for SOAP/WSDL and RESTful Web Services, Pearson, Upper Saddle River.
• 5. Delivand M., Barz M. & Gheewala S. (2011), Logistics cost analysis of rice straw for bio-mass power generation in Thailand, Energy, Vol. 36(3), pp. 1435–1441.
• 6. Engblom J., Solakivi T., Töyli J. & Ojala L. (2012), Multiple-method analysis of logistics costs, International Journal of Production Economics, Vol. 137(1), pp. 29–35.
• 7. Kuss C. & Winkler H. (2014), Using simulations to improve logistics efficiency along supply chains. Proceedings of The 11th International Conference on Logistics & Sustainable Transport, Celje.
• 8. Muchiri P. & Pintelon L. (2008), Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion, International Journal of Operations & Production Management, Vol. 46(13), pp. 3517–3535.
• 9. Newcomer E. (2002), Understanding Web Services, Pearson, Boston, MA.
• 10. Nurmilaakso J.M. (2008), Adoption of e-business functions and migration from EDI-based to XML-based e-business frameworks in supply chain integration, International Journal of Production Economics, Vol. 113(2), pp. 721–733.
• 11. Stewart G. (1995), Supply chain performance benchmarking study reveals keys to supply chain excellence, Logistics Information Management, Vol. 8(2), pp. 38–44.
• 12. Winkler H. (2011), Closed-loop production systems – A sustainable supply chain approach, CIRP Journal of Manufacturing Science and Technology, Vol. 4(3), pp. 243–246.
• 13. Winkler H. & Kaluza B. (2006), Integrated Performance and Risk Management in Supply Chains – Basics and Methods. In: W. Kersten & T. Blecker (eds.), Managing Risks in Supply Chains – How to Build Reliable Collaboration in Logistics, Berlin, pp. 19–36.
• 14. Winkler H., Wurzer Th., Kuss C. & Seebacher G. (2013), Improving Logistics Efficiency in Supply Chains using a Supply Chain Improvement System (SCIS). Proceedings of the 10th International Conference on Logistics & Sustainable Transport, Celje.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.