After sales supply chain risk management.

Lean supply chains with cost optimized production and logistics processes in the automotive industry have become a benchmark for other industries. Short delivery times, low inventories and high availability are parameters which assume a robust supply chain. In industrial practice we see, however, that in the After Sales business particularly related to the supply of automotive spare parts, that there are always unforeseen delays in delivery. In order to avoid service level losses on the focal firm level due to missing parts it is necessary to understand the risk structure on the supplier side. For this reason, a risk model for the After Sales inbound SC is developed through this work. Based on an extensive analysis of delivery data a central risk size was derived. Comprehensively researched SC risks are supplemented by After Sales specific risks derived through an empirical supplier survey. A reference network, which is methodologically based on the Bayesian theorem, to control the dynamic relationships was developed. The developed risk model allows for the identification of proactive and reactive measures by top-down and bottom-up analyzes to make lean supply chains for after sales requirements in the best cases robust and resilient. A big advantage of the developed model is not only the ability to quantify the cause and effect of supply chain risks but also to describe the constantly changing risk environment of the supply chain through continuous belief updates within the model. The risk analysis in the developed model potentially reduces the delivery delay of spare parts by 65 percent and diminishes the buffer stock value by 50 percent. To achieve such improvements in the real world organizations must be able to implement measures in explicit SC risk clusters for sustainable supply chain performance and inventory management. Improvements in the internal supplier processes, due to risks like prioritized series supply, or inappropriate after sales supply strategies are necessary. Utilizing the developed After Sales Risk Management Model (ASRIM) organizations will be able to implement proactive risk mitigation strategies, facilitating agile SC performance, while simultaneously reducing buffer stocks

Ultracold atoms in multiple-radiofrequency dressed adiabatic potentials

We present the first experimental demonstration of a multiple-radiofrequency dressed potential for the configurable magnetic confinement of ultracold atoms. We load cold $^{87}$Rb atoms into a double well potential with an adjustable barrier height, formed by three radiofrequencies applied to atoms in a static quadrupole magnetic field. Our multiple-radiofrequency approach gives precise control over the double well characteristics, including the depth of individual wells and the height of the barrier, and enables reliable transfer of atoms between the available trapping geometries. We have characterised the multiple-radiofrequency dressed system using radiofrequency spectroscopy, finding good agreement with the eigenvalues numerically calculated using Floquet theory. This method creates trapping potentials that can be reconfigured by changing the amplitudes, polarizations and frequencies of the applied dressing fields, and easily extended with additional dressing frequencies.Comment: 16 pages, 6 figure