The paper focus on the synchronous servo motors controller to minimize the synchronous errors. The motion command is transmitted simultaneously for two motors in the micro-precision servo press. Based on an available process model, the feedback control makes the system stable; the feed-forward control reduces tracking error due to friction, identified model of the linear motor drive system and PI control tracks errors that occur while the press is processing. The results of this research show that the relationships between the position of the slider and the angular velocity of the motor can predict the required position of the slider. The speed of the output torque creates the conditions for real-time response. The angular position of the motor is determined by the controller and can be tracked by the predefined speed control.
Industry 4.0 aimed use of the IOT (Internet of Things) to change the future of industrial innovation including in the field of equipment manufacturing and production efficiency. The supplier can respond quickly to the customer demand. The customer can directly order in a manufacturing enterprise marketing platform and select the processing machine with lower production costs. This paper builds the knowledge engineer of machining process that analyze the supplier information, customer demand information and the manufacturing process information. Using Analytic hierarchy process (AHP) for supplier selection methodology, it helps the customer with a reliable way to find suppliers and select the right machining tool.Index Terms-Tool machining knowledge, supplier selection, customer matching.
In this research, a knowledge-based system with a function module in manufacturing processing is used to recommend machining algorithms and to provide a cost analysis for manufacturers and clients. In each manufacturing segment, metal processing plants will be able to upload an engineering drawing into a machine information database system. Machine processing capability for management work is then analyzed via Siemens PLM Software NX. The result of the analysis includes axes of movement, mass, volume, accuracy, surface roughness, geometric features and other information uploaded into the database system. Users select the recommended machine specification requirements and establish a postprocessor. This research aims to improve the customized manufacturing and manufacturing capabilities of metal processing companies in order to quickly respond to the target date and to integrate the three technical keywords “Selecting machine system”, “Cost estimation” and “Machine recommendation algorithms”.
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