Academic literature on the topic 'Closed loop control; Magnetorhelogical finishing process'

Four algorithms for removing shape and waviness errors in sculptured surface production processes are described in the paper. One of the algorithms employs an open-loop strategy without inspection, error analysis, and error compensation. The other three algorithms employ closed-loop inspection error analysis and error compensation strategies to manipulate control surfaces used in sculptured surface production. Coordinate measurements made on the surface being produced are compared with a designed surface and the results are used to modify related control surfaces that are used to guide processing equipment. Two of the closed-loop algorithms also use intermediate planned surfaces to improve error compensation and production control. Experiments are described in the paper in which the algorithms were tested on an experimental surface finishing system that included an optical probe, grinding spindle, and computer control system integrated with a CNC machining center. The results obtained using open-loop and closed-loop algorithms are compared, and it is shown that surface inspection, surface error analysis, surface compensation, and surface grinding can be iteratively applied to converge rough-machined test surfaces to their designed shape. The closed-loop algorithms are shown to be capable of compensating for disturbances in the finishing process that went undetected when the open-loop algorithm was used. The closed-loop algorithms have significant potential for application in automated finishing systems for molds and dies.

This paper describes a method for finishing cast iron stamping dies. The task is to remove tool marks in the form of grooves and cusps left by a ball-end milling tool. The bottoms of the grooves represent the desired final surface profile. The method consists of using a closed-loop force-controlled robot with a flexible grinding disk coupled to a means for measuring the height of the partially ground cusps. Measurement is particularly easy, accurate, and sensitive if the tops of the partially ground cusps are flat, a condition that is not easy to obtain; otherwise accurate measurement is a chore. The Taguchi method is used to determine process parameters (grinding grit size, feed speed, disk speed, disk inclination angle, etc.) that yield flat tops. This grinding strategy has proven successful. A smooth, regular, and accurate final shape is obtained in spite of the relatively poor position accuracy of the robot. The measurement strategy has not been implemented yet but it appears feasible based on preliminary experiments.

Background: Intelligent manufacturing is perceived as a manufacturing mode with powerful learning and cognitive capabilities empowered by information technologies such as the internet of things, edge computing, and cloud computing. The mode can be used to address the problems of low intelligence and poor timeliness of traditional process planning. Methods: The framework includes the multi-objective process planning method based on real-time data, and the process closed-loop optimization mechanism of “cloud-based theoretical process planning plus edge MEC (multi-access edge computing) side online simulation verification and real-time feedback adjustment”, which realizes online process planning and iterative optimization in mass customization. Results: The feasibility of the online analysis method for thin-walled part milling deformation is verified by taking the finishing process of aerospace thin-walled parts as an example. The experimental results show that the simulation time on the single analysis step is reduced from 6s to 1s, and the accuracy rate is 86.9%. Conclusions: A new intelligent process planning theoretical framework integrating with online process planning and autonomous collaborative control, namely, digital twin and multi-access edge computing process planning (DT-MEC-PP) is proposed in this paper.

This paper proposes the novel idea of eliminating the front-end converters used indirect current (DC) bus voltage variation, thereby allowing for control of the speed of the brushless direct current (BLDC) motors in the two-quadrant operation of a permanent magnet brushless direct current (PMBLDC) motor, which is required for multiple bi-directional hot roughing steel rolling mills. The first phase of steel rolling, the manufacture of plates, strips etc., using hot slabs from the continuous casting stage, is carried out for thickness reduction, before the same is sent to the finishing mill for further mechanical processing. The hot roughing process involves applying high, compressive pressure, using a hydraulically operated mechanism, through a pair of backup rolls and work rolls for rolling. Overall, the processes consist of multiple passes of forward and reverse rolling at increasing roll speeds. The rolling process was modeled, taking into account parameters like roller dimensions, angle and length of contact, and rolling force, at various temperatures, using actual data obtained from a steel mill. From this data, speed and torque profiles at the motor shaft, covering the entire rolling process, were created. A profile-based feedback controller is proposed for setting the six-pulse inverter frequency and parameters of the pulse width modulated (PWM) waveform for current control, based on Hall sensor position, and the same is implemented for closed loop operation of the brushless direct current motor drive system. The performance enhancement of the two different controllers was also evaluated, during the rolling of 1005 hot rolled (HR) steel, and was taken into consideration in the research analysis. The entire process was simulated in the MATLAB/Simulink platform, and the results verify the suitability of an entire-drive system for industrial steel rolling applications.

If the shaft diameter can be measured in-situ during the finishing process, the closed-loop control of the shaft diameter processing process can be realized and the machining accuracy can be improved. Present work studies the measurement of shaft diameter with the structured light system composed of a laser linear light source and a camera. The shaft is a kind of part with rotationally symmetric structure. When the linear structured light irradiates the surface of the shaft, a light stripe will be formed, and the light stripe is a part of the ellipse. Therefore, the in-situ measurement of the shaft diameter can be realized by the light stripe and the rotational symmetry of the shaft. The measurement model of shaft diameter is established by the ellipse formed by the intersection of the light plane and the measured shaft surface. Firstly, in the camera coordinate system, normal vector of the light plane and the coordinates of the ellipse center are obtained by the calibration; then, the equation of oblique elliptic cone is established by taking the ellipse as the bottom and the optical center of the camera as the top. Next, the measurement model of shaft diameter is obtained by the established oblique elliptic cone equation and theoretical image plane equation. Finally, the accuracy of the measurement model of shaft diameter is tested by the checkerboard calibration plate and a lathe. The test results show that the measurement model of shaft diameter is correct, and when the shaft diameter is 36.162mm, the speed is 1250r/min, the maximum average measurement error is 0.019mm. The measurement accuracy meets the engineering requirement.

Purpose This paper aims to address the problem of integrating sensor feedback in robotized interior finishing operations. Its motivation is to finally realize automatic operations necessitating no human intervention. A vision-based approach is proposed for monitoring the execution status and changing the action accordingly. Design/methodology/approach First, a robotic system is proposed which can realize two typical interior finishing operations, namely, putty applying and wall sanding. Second, a new method based on a deep neural network is proposed to process the visual information capturing the execution status of the interior finishing operations. It helps to determine essential parameters on where should be processed and how to execute the corresponding operation. With the proposed method, vision information is embedded into the execution of interior finishing in a closed loop style. Findings The experiments demonstrate the feasibility of the proposal and reveal problems for further improvement of the autonomous interior finishing robot. Originality/value This provides an original insight into robotized interior finishing by addressing an attempt on integrating visual feedback into the manual process.

Abstract Industrial demands for higher quality, yet lower cost thermal spray coatings have driven the development of highly automated and fully integrated thermal spray systems. These systems include computer control of the powder, gas, electrical power, and cooling fed to the spray device, auxiliary cooling of the part, and motion of the part spray device. The subsystems may include closed-loop control of particular parameters such as the powder feed rate. More fundamental closed-loop or "intelligent" processing systems are under development. A key element in such systems is the ability to sense critical parameters that are indicative of the coating's properties in such a manner that changes in the process can be made to maintain its properties while the coating is being deposited. For example, it is widely recognized that the temperature, velocity, and size distribution of the powder particles during flight are largely responsible for the properties of the resultant coating. A variety of sensor systems have been developed recently that can measure one or more of these properties. At least one such system is capable of measuring all three parameters for the full cross section of the spray. Computer controls, closed loop systems, and intelligent processing cannot compensate for poorly designed, manufactured, or maintained equipment. Nor can they compensate for unsatisfactory preparation of the surface, feedstock (powder, gas, power), finishing equipment or materials, or training of operators. Sufficient attention to all of these factors may even make the investment in some more sophisticated systems questionable for some applications. This paper will attempt to provide an overview of the currently available highly automated and integrated thermal spray systems used for intelligent processing and consider some criteria for its selection and use.