Data-driven flexible manufacturing optimization

OData support
Supervisor:
Dr. Gönczy László
Department of Measurement and Information Systems

There is a great role for optimalization in logistics, manufacturing and in every aspect of life too; during production, each and every sistem automatically measures and values the amount and time in order to help the schedule of manufacturing tasks. To the proper energy and time management, it is important in the production planning to collect and alanalyze previous datas, and correctly forecast them.

In the case of one of this optimizing task we must transform the informations from the real world into mathematical models what we can handle, so with processing these datas we can provide informations int he direction of the real word.

In my dissertation I present several mathematical models along with their possible sollutions, comparison with the possibilities and boundaries of each optimalizing software. Furthermore I’ll mention how other platforms can use the already done program in order to ease up the embedding process into other programming languages. Besides I’ll present the logic of a sequential solution that does not use any optimizing libraries.

The program made like this, within certain limits, can help to solve a produntion optimalization schedule.

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