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Advanced cascaded scheduling for highly autonomous production cells with material flow and tool lifetime consideration using AGVs

Miller Eddi, Engelmann Bastian, Kaupp Tobias, Schmitt Jan

Journal of Machine Engineering

2023

Vol. 23, No. 3

69--85

In today’s manufacturing systems, especially in Industry 4.0, highly autonomous production cells play an important role. To reach this goal of autonomy, different technologies like industrial robots, machine tools, and automated guided vehicles (AGV) are deployed simultaneously which creates numerous challenges on various automation levels. One of those challenges regards the scheduling of all applied resources and their corresponding tasks. Combining data from a real production environment and Constraint Programming (CP-SAT), we provide a cascaded scheduling approach that plans production orders for machine tools to minimize makespan and tool changeover time while enabling the corresponding robot for robot-collaborated processes. Simultaneously, AGVs provide all production cells with the necessary material and tools. Hereby, magazine capacity for raw material as well as finished parts and tool service life are taken into account.

Some heuristics for makespan minimization in permutation flow-shop

Dolgui A., Ofitserov D.

Management and Production Engineering Review

2010

Vol. 1, No. 4

19-25

This paper deals with the study of makespan optimization for the flow-shop production systems with or without infinite buffers between machines. Two scheduling algorithms are presented. They are based on several ideas from global optimization for continuous functions. In particular, ψ-transform technique is employed. This is a very interesting research direction to find heuristics with solid theoretical foundations and with a possibility to estimate subsequently their error. Consequently, problems of real size and actual complexity can be dealt with a certain confidence in the quality of the results. The algorithms proposed include also the Petrov matrix and the Gilmore-Gomory methods. The effciency of the algorithms proposed is illustrated with numerical tests on examples known in literature and on randomly generated tests.