Due to increasing demands for efficiency, traceability, and flexibility in modern manufacturing processes, the automation of internal logistics has become a key component of the industry 4.0 paradigm. While robotics cells, CNC machining centers, and supervisory systems are often highly automated, the supply of materials to these systems frequently remains manual, creating a bottleneck in production. This master's thesis addresses the problem of manual supply of automated robotic cells in the industrial environment, where a system for automated supply using an Automated Guided Vehicle (AGV) was developed and implemented.
To solve this problem, an initial analysis of the existing manual supply process was conducted, identifying its main shortcomings: dependence on human operators, reduced throughput, the possibility of errors, and increased safety risks. Based on this analysis, a system for automated supply using an AGV was designed, including the selection of appropriate hardware, the design of logistical routes, the definition of delivery points, and integration with the company's existing information system. The system enables fully autonomous transport of products from the intermediate warehouse to the individual production cells and the return of empty transport containers without human intervention.
The AGV is controlled via a central management system, which coordinates its operation according to the status of the production cells and inventory levels, while considering safety mechanisms such as obstacle detection and emergency stop functions. As part of the thesis, the entire system was implemented and tested in real industrial conditions. The collected data showed a significant reduction in manual interventions, improved synchronization of processes, reduced error rates, and an overall increase in safety and traceability within the production system.
The main conclusion of the thesis is that the implementation of an AGV represents a significant improvement towards full production automation and provides an effective approach to optimizing internal logistics in smart factories. The work demonstrates that, with proper planning and system integration, manual supply can be successfully replaced even in demanding industrial environments.
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