We present an optimization heuristic to solve the operation balancing and scheduling problem on a Flexible Manufacturing Cell. The investigated problem is based on the study of an industrial case study of the Robert Bosch enterprise. The considered manufacturing system is a multi-stage CNC machining cell. Cell operations are grouped in four stages. At each stage, multiple spindles simultaneously work on a single work-piece; consequently spindle collision problem has to be considered. When, at each stage, operations are completed, a rotation mechanism simultaneously transfers each work-piece to the next stage. The innovation aspect of the present work consists in the possibility to model the geometric constraints between operations in order to avoid spindle collisions at the same stage. The proposed heuristic approach aims to maximize the system throughput, reducing the machine total cycle time and respecting complex industrial manufacturing constraints (geometrical and synchronization constraints). A Genetic Algorithm approach has been developed to solve the addressed problem. A real case study set has been solved in order to show the suitability of our approach.

In Flexible Manufacturing System, parts move among the resources in order to be processed. Usually, a classical pallet transport system adopts the railway carrier layout. Each time a pallet has to be moved in the system, a transport trip request is issued and waits to be satisfied by the transport system. The transport system optimization problem consists in determining the exact list of pallet trips performed by the carrier. In general, the objective consists in minimizing the makespan to perform all the trips. If the level of flexibility of the manufacturing system architecture is reduced, as in Focused Flexible Manufacturing Systems, the use of part transport system increases. Consequently, the transport system can become the system bottleneck. This leads to starvation and blocking on machining resources due to parts waiting to be moved by transport system. In such a case, the main goal consists in the minimization of the idle resource time due to transport system. Nevertheless, if the transport trip rate is remarkable, a single vehicle is not sufficient to fulfill the request. In this case, a trans- port system made of a double capacity vehicle or two single capacity vehicles can be adopted. This work proposes a graph-based approach for such an optimization problem. Different transport system architectures are compared. The validation of the method is performed on a case study in order to compare the performance.