Titlebook: Dynamics in Logistics; First International Hans-J?rg Kreowski,Bernd Scholz-Reiter,Hans-Dietri Conference proceedings 2008 Springer-Verlag

Vldl379

RFID-Based Intelligent Logistics for Distributed Production Networks

VAN

FADE

Botswana,urring in three waves: the first wave of the model is Technology Deployment, the next wave of Data Understanding, and, lastly, the final wave is Business Value Creation. In this paper, the first two waves of the model are explored briefly with the emphasis placed on proven business cases and potenti

ONYM

China,on of an innovation, and is now approaching the stage in which the adoption rate is rapidly increasing. Adoption is being led by large companies. Cost, lack of practical knowledge about application, difficulty of demonstrating ROI and difficulty of attaching tags were the major barriers to adoption,

NEX

intercede

ed papers and of 42 contributed papers on various subjects give an state-of-art overview on dynamics in logistics. They include routing in dynamic logistic networks, RFID in logistics and manufacturing networks978-3-642-09555-9978-3-540-76862-3

咽下

Challenges in Design of Heterarchical Controls for Dynamic Logistic Systemshedding new light on control design in the domain of logistic systems for production, transportation, etc. The spectrum of available organizational structures is reviewed and the case is made for choosing heterarchical structures. Then, principles for designing control systems and building and evolv

Indurate

Making the Business Case for RFID05. Since that announcement, the business value of RFID in the consumer packaged goods supply chain has been periodically questioned.Recently, a Wall Street Journal article asserted that RFID is not living up to its hype, and in reality is not providing the promised tangible business value throughou

拉開這車床

initiate

Dynamic Data Mining for Improved Forecasting in Logistics and Supply Chain Management in the sense that past data is used for model construction and evaluation without being updated adequately when new data becomes available.We propose a dynamic forecasting methodology and show its effectiveness in a real-world application.