In the context of Industry 5.0, the attention on the manufacturing systems is shifted from an entire economic profitability to a more eco-friendly and socially integrated manufacturing environment. In achieving the sustainability necessary in Industry 5.0 an important step can be represented by reusing existing equipment. Usually, in developing new products, new equipment and systems are developed to meet the production requirements, replacing the existing equipment. In applying the sustainability paradigm, existing equipment should be repurposed and integrated in new manufacturing systems. Integration of existing equipment presents different design challenges. This integration can be applied in cases where the proposed products variety closely resemble existent manufactured products, if not include them. In this context the adaptation of a laboratory manufacturing system to a flexible manufacturing system is presented. The capabilities of the initial manufacturing system, to assemble a personalized product, are upgraded to the possibility of manufacturing an extended product variety. This is achieved by integrating in the existing manufacturing system several new equipment and capabilities. The transformation of the manufacturing system was made in two stages. First stage was concentrated on the sustainability concept and manufacturing of the new products. The second stage concentrated on the resilience of the manufacturing system developed. Resulted a flexible manufacturing system, with two production flows, capable of manufacturing a total of five derived products, each with personalizing capabilities.

Modeling, monitoring and control of a multilevel architecture for an assembly/disassembly technology (A/DT) assisted by an autonomous cyber-physical system (ACPS). The hardware architecture consists of six workstations (6-WS), A/D mechatronics line (A/DML) connected to an A/D flexible cell (A/DFC) equipped with a 6-DOF industrial robotic manipulator (IRM). ACPS has in its structure two driving wheels and one free wheel (2DW/1FW)-wheeled mobile robot (WMR) equipped with a 7-DOF robotic manipulator (RM). A mobile visual servoing system (MVSS) is mounted on the end effector of the RM. A/DT assembles two different workpieces (WP1 and WP2), while disassembly only covers products that do not meet the quality test and component recovery through ACPS. ACPS takes the components from the disassembly locations and stores them in the appropriate warehouses for reuse. Synchronized Petri nets (SPN), for assembly, and synchronized hybrid Petri nets (SHPN), for disassembly, are used for modeling and simulation. Discrete-time trajectory-tracking sliding-mode control (DT-TTSMC), for WMR displacement, inverse kinematic (IKC) for 7-DOF RM control, and image moments for MVSS positioning are used to control ACPS subsystems. The design of the A/DT served by ACPS, was subordinated to the concept of Digital twin, by integrating, interfacing and synchronizing the simulation results of the SPN and SHPN models, with real-time management in a supervisory control and data acquisition (SCADA) system located on a Remote PC (RPC). The design and real-time control of A/DT served by ACPS were made in the vision of Industry 4.0 and Industry 5.0.

In this paper, we propose a unitary tool for modeling and analysis of discrete event systems monitoring. Uncertain knowledge of such tasks asks specific reasoning and adapted fuzzy logic modeling and analysis methods. In this context, we propose a new fuzzy Petri net called Fuzzy Reasoning Petri Net: the FRPN. The modeling consists in a set of two collaborative FRPN. The first is used for the fault dynamic state of the system by temporal spectrum of the marking. A monitoring fuzzy Petri net (MFPN) represents the fault tree. The second model, the recovery fuzzy Petri net (RFPN) corresponds to recovering activities. The two proposed models form a dynamic loop for production system monitoring and recovery. Production system is supposed to be modelized using temporal Petri nets, with the assumption that the primary fault symptoms are detected. These symptoms are considered in the MFPN and evolve according to all other derived faults of the system. Synchronizing signals, corresponding to different warning levels and alarms, form the interface between these two tools.