Study of an advanced transport system exploiting magnetic levitation: the Beckhoff XPlanar

The transport system is one of the most important components to be chosen in the design of an automatic machine. There is a wide variety of different choices that can be made in picking this element, each one having its own strengths and its own drawbacks. If it is desired to obtain some elaborate behaviour from the transport system, it is a good idea to think about some flexible and advanced solutions. Among these transport systems, the newest is the Beckhoff XPlanar. This transport system exploits magnetic levitation to move some passive magnetic movers on a completely customizable plane, in an entirely contact-free way. This provides a fast, clean, and noiseless motion, which is extremely desirable in a modern automatic machine. The purpose of this Thesis is to analyse the potentialities and the problems of this new device, starting from the basics. After having presented in detail the topic, an analysis on the hardware components needed to build this system is performed. Then, it is conducted a study on the concepts needed to know how to build a controller having the purpose of dealing with this system. After that, the various types of motion are studied and executed and, later on, some experiments on the real kit are carried out. These studies start from the diagnostic and involve other analyses that are used to test the limits of this transport system. In performing these analyses, it is noticed how the kit presents some problems in reaching the limits of the dynamics. Finally, two different types of station cycle are implemented, which are useful to get a rough idea on the potentialities of this new advanced transport system.

Design and management of a supply chain: a joint location-inventory problem under uncertainty (Part A)

In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.