Optimal Control of Automated Resupply on a Flexible Manufacturing Mechatronics Line | IEEE Conference Publication | IEEE Xplore

Optimal Control of Automated Resupply on a Flexible Manufacturing Mechatronics Line


Abstract:

This paper proposes a new control algorithm for real-time replenishment the warehouses of a flexible manufacturing process, in order to optimize the stocks. The supply / ...Show More

Abstract:

This paper proposes a new control algorithm for real-time replenishment the warehouses of a flexible manufacturing process, in order to optimize the stocks. The supply / resupply strategy is based on the proposed optimization function that integrates two components: a predictive component of the necessary stocks corresponding to the forecasted time interval, and the optimization of the cycle times for the real-time replenishment of the stations. For the implementation of the proposed optimization function, data provided by real-time monitoring of the assembly / disassembly process on the mechatronic line (A / DML) are used - signals provided by the integrated sensor system. It also exploits information about production orders, taken in real time through a Client Application, implemented on a dedicated web server. All this information is stored in real-time SQL databases and is processed by specific SQL functions. The optimization function considers the results of Petri Nets modelling/simulation of the A/DML process served by the mobile robot (MR). Finally, the optimization function determines for each workstation, the minimum waiting time to initiate a new replenishment sequences, respectively the duration of the optimal cycle for replenishing a station warehouse. Based on these reasoning and results, real-time resupply planning was implemented, implicitly MR control for automated resupply of the warehouses for flexible manufacturing process. In future research we aim to integrate the component of optimization of resupply cycles, in remote control and supervision of the A/DML process according to Industry 4.0 concepts.
Date of Conference: 08-10 October 2020
Date Added to IEEE Xplore: 23 November 2020
ISBN Information:
Print on Demand(PoD) ISSN: 2372-1618
Conference Location: Sinaia, Romania

References

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