Modern Technologies and Manufacturing Systems, 2nd Volume

The three-body coupling grinding mode (3B-CGM) of spheres not only guarantees lot diameter variation and batch consistency of precision ball processing on the balling principle but also makes structural control easy and feasible. To assure balling quality under the three-body coupling grinding mode, it must improve dynamic mechanical precision control ability during processing. This study detailed contents covered the following three aspects: (1) The velocity equilibrium equation under the three-body coupling grinding mode was established under ideal conditions. This velocity equilibrium equation was transformed into the velocity equilibrium equation in the form of θ, Ω_b, and ω_b, thus laying the foundations to analyze the influencing degree of grinding uniformity; (2) On the basis of the velocity equilibrium equation, the characteristics of various sliding states were analyzed. Moreover, the sliding–friction ratio (S_c) was established to analyze the variation laws of the sliding state. The acquired mathematical model of evaluation indexes could realize optimization of the system control precision; (3) A multibody dynamics analysis software, i.e., ADMAS, was applied, and the standard deviation of uniformity of spherical track points in the simulation was created to evaluate influences of subsequent mechanical structural errors, including excessive loads, run-out, the tilt and out-of-roundness of upper and lower grinding discs, the diameter of grinding discs, and the V-shaped groove angle of grinding discs. This study establishes an accurate motion control model, as well as the optimal parameter analysis method. It improved the fine control over motion states. These models and indexes lay theoretical foundations for the realization of approximately ideal grinding effect in practical mass production. Full article

Silicon nitride ceramic balls are the key basic components of bearings in major equipment. Their key performance indices are accuracy and batch consistency. A grinding method with the most appropriate comprehensive performance is the basis and guarantee for optimizing these performance indices. In this study, an accurate wear model was established to predict the material removal rates (MRRs) of grinding methods and improve the dynamic grinding control ability of machinery during grinding, thus enabling the mass production of high-grade silicon nitride ceramic balls. A comprehensive analysis of various grinding and polishing methods revealed that the factors affecting sphericity were mainly manifested by the increase in ball sliding and the improvement in MRRs. More over, the three-body coupling grinding mode was considered as the grinding mode that was most applicable to silicon nitride ceramic balls. The upper disk served as an external nonlinear load, and the combination of the rotating speeds of the inner and outer disks of the lower grinding disk could actively control the ball’s angle of rotation. This three-body wear mode can fully envelop the grinding trajectory and ensure uniform grinding. The traditional two-body wear model was unsuitable for three-body coupling grinding. A wear model based on three-body wear was established to predict MRRs and understand the principle of material removal in the grinding of precision spheres. Theoretical analysis and experimental verification revealed that the MRRs of silicon nitride ceramic balls during wear are not only related to the process parameters of external load and speed but also to the physical properties and geometric parameters of balls, abrasives, and processing machinery. The wear model results of silicon nitride ceramic balls in the three-body coupling grinding mode can be obtained stably on the basis of the established wear model by removing adverse effects and adopting optimized processing parameters, thus verifying the correctness of the theoretical and simulation analyses. Full article

Rapid shifts in consumer preferences have prompted enterprises to offer products in small quantities and various options. To meet market demands, enterprises must be able to research the development of modern conceptions of manufacturing systems which has revolved around new practical and scientific results that are able to meet the assumptions of focused flexible manufacturing systems (FMSs) and the challenges of the Industry 4.0 philosophy. These FMSs, which incorporate automated facilities and computer control systems, play a crucial role in boosting the productivity of enterprises. In this study, the development trajectory and applications of FMS research were investigated. Scopus was used to collect and organize voluminous data, and main path analysis was used to identify the most relevant studies on FMS research. The results revealed that early FMS research concentrated on fundamental property analysis. After the flexibility and productivity of these systems were enhanced, the elimination of loading problems was discussed. Generally, FMS research has emphasized factor identification, flexibility evaluation, pre-simulation, and optimization. In this study, cluster analysis was used to identify five subfields: loading problem mitigation through scheduling, decision-making facilitation through simulation, FMS deadlock prevention, FMS flexibility measurement, and FMS composition. This study provides planning directions for industry, and the findings serve as a reference for manufacturing systems. The integrated analysis successfully determined the trajectory of FMS based technological development and applications as well as forecast the direction of future research. Full article

This paper proposes a genetic algorithm approach to solve the identical parallel machines problem with tooling constraints in job shop flexible manufacturing systems (JS-FMSs) with the consideration of tool wear. The approach takes into account the residual useful life of tools and allocates a set of jobs with specific processing times and tooling requirements on identical parallel machines. Two metrics are introduced to evaluate the scheduling decisions and optimize the scheduling process, with the competitive goal of maximizing tool utilization and minimizing production makespan. The proposed approach searches for a set of optimal solutions on the Pareto front that offers the best possible balance between these two objectives, achieving optimal local performance in terms of both makespan and tool utilization. The approach is implemented with a customized genetic algorithm and validated on a real case study from a company operating in the aerospace sector, which confirms its effectiveness in increasing tool utilization and reducing the makespan. The results show that the proposed approach has significant practical implications for the manufacturing industry, particularly in the production of high-value materials such as those in the aerospace sector that require costly tools. This paper contributes to the operational research community by providing advanced scheduling algorithms that can optimize both the makespan and the tool utilization concurrently, improving production efficiency and maintaining competitiveness in the manufacturing industry. Full article

In the manufacturing and production of hypoid gears, it is a necessary key problem to improve the tooth surface heat treatment precision and production efficiency of the hypoid gears. How to use advanced statistical theory and methods to evaluate the whole batch machining quality of the tooth surface after heat treatment is particularly urgent. In this connection, for the same batch of hypoid gears with the same gear material, numerical control gear milling method, and heat treatment specifications, a bootstrap-based statistics scheme of tooth surface errors after heat treatment is proposed in this paper. The bootstrap statistics model of the tooth surface errors for the batch hypoid gears is established. The bootstrap probability eigenvalues and confidence intervals of the measurement sequence points on the tooth surface errors are solved, and the optimizing selection of the single sampling numbers and the repeated sampling times is completed. On this basis, by applying the cubic NURBS surface fitting method, the mean value difference surface of the batch tooth surface errors data is constructed, the statistics laws of the whole batch tooth surface errors after heat treatment is determined, and the effective evaluation of the whole batch tooth surface accuracy is realized. Finally, the feasibility and correctness of the bootstrap-based statistics scheme are verified by the tooth surface errors bootstrap statistics application experiment of one kind of hypoid gear. The results show that with the help of the bootstrap statistics method proposed in this paper, it is not necessary to accurately measure the tooth surface errors of the whole batch of hypoid gears one by one. Only by randomly selecting 10 tooth surface samples and repeatedly sampling 2000 times, the original sample characteristic values of the whole batch tooth surface errors can be accurately estimated, and the heat treatment deformation statistics laws of the whole patch tooth surfaces can be also counted. Full article

Computer numerical control (CNC) lathes are optimized for machining workpieces into rotating shafts or cylindrical shapes of structures. However, because rotating mechanical parts are used on CNC lathes, vibration from spindles, servomotors, hydraulic pumps, and feed screws occurs. Therefore, periodic preventive maintenance is required to minimize vibrations. Additionally, alignment, balance, and adjustment operations are necessary for parts that perform linear or rotational movements. Thus, this study adjusts the tension of the V-belt that drives the spindle of the CNC lathe, analyzes the primary components and the vibrations occurring at the spindle and servomotor, and measures the surface roughness to identify the cutting quality according to the impact of the belt tension. The experimental results show that the peak value of the vibrating component increases as the cutting speed increases. We demonstrate that the optimal vibration characteristics and excellent surface roughness values are achieved at a relatively looser belt tension than the standard value. In particular, at a feed speed of 0.05 mm/rev, a cutting speed of 250 m/min, and a depth of cut of 0.8, the surface roughness in loose tension was reduced by up to 143.9% compared to tight tension. Additionally, the optimum processing quality is achieved at a cutting depth of 0.6 and 0.8 mm, corresponding to a turning insert nose R-value of 0.4 mm, and at cutting speeds ranging from 200 to 250 m/min. Full article

This paper reports the results of research on the influence of the compliance of the technological system used in grinding low-stiffness shafts on the shape accuracy of the workpieces. The level of accuracy achieved using passive compliance compensation was assessed, and technological assumptions were formulated to further increase the shape accuracy of the low-stiffness shafts obtained in the grinding process. Taking into account the limitations of passive compliance compensation, a method for the active compensation of the compliance of the elastic technological system during the machining process was developed. The experiments showed that the accuracy of grinding was most effectively increased by adjusting the compliance and controlling the bending moments, depending on the position of the cutting force (grinding wheel) along the part. The experimental results were largely consistent with the results of the theoretical study and confirmed the assumptions made. Adjusting the compliance in the proposed way allows for the significant improvement in the accuracy and productivity of machining of low-stiffness shafts. Full article

The paper deals with the issue of the mixed-reality usage in the design of production systems, its changes during expansion, or technological changes in the production, where it is necessary to flexibly and quickly verify the integration of a new machine into the existing layout and eliminate collision situations even before the installation of a physical machine in production. This is realized through Vumark’s design methodology, which was verified and applied in the conditions of the production environment of the Innovation and Prototyping Centre in the Faculty of Mechanical Engineering at the Technical University of Kosice. The individual parts of the paper describe the Vumark deployment procedure in the production area and the software and hardware resources that the user can apply. Three production machines and one robotic device selected from the Factory design software database were chosen for the experiment. The chosen method enables us to verify during the experiment several variants of deployment the machines in the layout and thus to find the optimal location in a very short time. The experiment showed that the chosen method is applicable in practice and brings savings of time, costs, and energy especially when changing the layout or replacing the machine in the production hall. Full article

Process understanding and process monitoring are of great importance in production in order to control processes and guarantee a high quality. Demanding customer requirements with an increasing number of variants pose an even greater challenge to the quality of the processes, as this must be maintained at the highest level even in the event of process changes. In addition, new regulations and standards require process data to be recorded and stored, especially in manufacturing environments for medical and safety equipment (e.g., surgical instruments, camera systems in the automotive industry). Continuous variations in production processes and changes to products and the production system mean that the planning effort required to implement process monitoring has become vast. This is where automated planning and decision support systems become important. They are able to manage the complexity arising from alternative solutions and present suitable alternatives to the user. This article deals with the computer-aided identification of assembly features, which influence process monitoring and the generation of production system-neutral tasks for process monitoring. Computer-aided feature recognition methods were used to derive features from three-dimensional models. Furthermore, a skill-based approach was used to formulate tasks for process monitoring. This publication thus aims at the automated and product-specific generation of processes for process monitoring. Full article

Inkjet printing for printed electronics is a growing market due to its advantages, including scalability, various usable materials and its digital, pixel based layout design. An important quality factor is the wetting of the ink on the substrate. This article proposes a workflow to evaluate the print quality of specific layouts by means of image analysis. A self-developed image analysis software, which compares a mask with the actual layout, enables a pixel-based analysis of the wetting behavior by the implementation of two parameters called over- and underwetting rate. A comparison of actual and targeted track widths can be performed for the evaluation of different parameters, such as the tested plasma treatment, drop spacing (DS) and substrate temperature. To prove the functionality of the image analyses tool, the print quality of Au structures inkjet printed on cyclic olefin copolymer (COC) substrates was studied experimentally by varying the three previously mentioned parameters. The experimental results showed that the wetting behavior of Au ink deposited on COC substrates influences various line widths differently, leading to higher spreading for smaller line widths. The proposed workflow is suitable for identifying and evaluating multiple tested parameter variations and might be easily adopted for printers for in-process print quality control in industrial manufacturing. Full article

Aiming at disadvantages of particle swarm optimization in the path planning of mobile robots, such as low convergence accuracy and easy maturity, this paper proposes an improved particle swarm optimization algorithm based on differential evolution. First, the concept of corporate governance is introduced, adding adaptive adjustment weights and acceleration coefficients to improve the traditional particle swarm optimization and increase the algorithm convergence speed. Then, in order to improve the performance of the differential evolution algorithm, the size of the mutation is controlled by adding adaptive parameters. Moreover, a “high-intensity training” mode is developed to use the improved differential evolution algorithm to intensively train the global optimal position of the particle swarm optimization, which can improve the search precision of the algorithm. Finally, the mathematical model for robot path planning is devised as a two-objective optimization with two indices, i.e., the path length and the degree of danger to optimize the path planning. The proposed algorithm is applied to different experiments for path planning simulation tests. The results demonstrate the feasibility and effectiveness of it in solving a mobile robot path-planning problem. Full article

Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the upcoming era of Industry 5.0. Currently, low recognition accuracy and low location precision of devices in intelligent monitoring remain a problem in production lines. This paper proposes a production line device recognition and localization method based on an improved YOLOv5s model. The proposed method can achieve real-time detection and localization of production line equipment such as robotic arms and AGV carts by introducing CA attention module in YOLOv5s network model architecture, GSConv lightweight convolution method and Slim-Neck method in Neck layer, add Decoupled Head structure to the Detect layer. The experimental results show that the improved method achieves 93.6% Precision, 85.6% recall, and 91.8% mAP@0.5, and the Pascal VOC2007 public dataset test shows that the improved method effectively improves the recognition accuracy. The research results can substantially improve the intelligence level of production lines and provide an important reference for manufacturing industries to realize intelligent and digital transformation. Full article

This paper focuses on the development, theoretical and experimental research on the structural units of an unconventional three-wheeled vehicle. The vehicle is designed in order to increase the stability when cornering in a low curvature radius. Current research work describes solutions to increase the cornering stability of either conventional three-wheeled vehicles or, more rarely, unconventional vehicles designed on the basis of complex wheel-tilting mechatronics. Thus, there is a gap in research in respect of consideration of a stability-enhancing mechanism for three-wheeled vehicles based on a combination of tilting and deflection of the front steered wheel in the course of cornering. This paper then compares the stability of a three-wheeled vehicle with one steered wheel in front and two wheels in the rear (1F2R) in conventional and unconventional designs. A particular linear formula for the stability of the three-wheeled vehicle in cornering is derived. This study further deals with the design of the frame intended to hold the unconventional steering mechanism of the front wheel of the vehicle, on the one hand, from the theoretical integrity point of view using CAD-, FEM- and MBS-based software and, on the other hand, from the experimental point of view by determining the multiaxial fatigue life of the test specimens. These were made from the frame structural material and loaded with an equivalent load (bending-torsion) corresponding to the real load of the frame in operation. It was discovered that the designed patented front wheel steering mechanism increased the passing speed by 19% in comparison with a conventional vehicle at the minimum possible radius of a corner. The designed vehicle meets the safety conditions in terms of frame integrity and load-bearing capacity. The vehicle frame is designed with respect to the fatigue life of the material, the results of which are presented in the work. The material employed for manufacturing the frame is aluminum alloy type EN AW6063, which makes the frame lightweight and strong. Full article

During the machining process, coolant is utilized to remove chips and tiny abrasive particles created during the machining process as well as to lessen heat concentration and friction between tools and chips. The machining performances, such as tool life, surface roughness, cutting forces, retention of mechanical properties of the work material, etc., are also desired to be retained or improved at the same time. This presented research work’s main goal is to investigate and analyze the impact of coolant at 0 °C on input machining parameters when turning SS304 (an austenitic stainless steel of the 300 series with high corrosion resistance) on a CNC lathe and to optimize the input variable factors, such as feed rate, cutting speed, and depth of cut for the best machining conditions, and each input cutting parameter is given a weight using the analytic hierarchy process (AHP) technique. A novel experimental setup is created to decrease the temperature of emulsion coolant and to use it in control conditions during machining operation. To research and assess the impact on the workpiece surface roughness, forces produced during actual cutting operations, the rate of tool wear, and the rate of material removal, twenty-seven sets of experiments using the partial factorial design approach are devised and carried out. Prioritizing the many optimal solutions accessible for this work is done using the technique for the order of preference by similarity to ideal solution (TOPSIS) and grey relation grade (GRG) approaches. Further, the surface finish of the workpiece after machining, rate of tool wear, cutting force generated during machining, and material removal rate from the workpiece were compared with traditionally/conventionally used input parameters with newly obtained optimized parameters through this work. Approximately a 30% improvement is observed in output parameters compared with using traditional parameters, and was close to the 50% of the result obtained through cryogenic machining. The work piece’s chip morphology along with tool wear was observed in form of SEM images, and it supports the claim of the surface finish and tool wear. The material removal rate was physically observed during machining. SEM pictures were used to physically validate the changes in tool wear. It has also been shown that keeping the coolant temperature at 0 °C significantly improves a number of work quality and machining characteristics. This method offers a substitute for cryogenic machining, making it useful for the manufacturing sectors. Full article

We are part of the digital transformation of society and industry. The digital transformation of industry is based on new technologies brought about by the fourth industrial revolution. The Internet of Things (IoT), Cloud Computing, Cyber–Physical Systems (CPS) and Big Data provide the digital link between machines and individuals in processes. This completely new system is based on efficient data collection, data analysis and immediate interventions in organizational processes based on the results of the analysis. Smart organizations are driven by data and not by models. By working efficiently with the vast amounts of data available, the smart organizations of the future can ensure business sustainability, increase competitiveness through process optimization and reduce costs. In general, the aim of this paper was to identify the means to achieve a paradigm shift from traditional organizations to smart organizations through the use of data in the context of integrating Industry 4.0 technologies. The aim of the research was to determine the extent to which different Industry 4.0 technologies are applied in the effective use of data from specific activities/processes in industrial organizations to bring about a paradigm shift from traditional organizations to smart organizations. The first part of the paper describes the theoretical background of the transition from traditional to smart organizations using selected Industry 4.0 technologies. The second part of the paper characterizes the research objective, the methods used in the paper and the basic statistics used to determine the research questions and hypotheses. The next section evaluates the research questions and hypotheses that were used to meet the research objective. The last part of the paper is a summary of the obtained results, based on which we conclude that the primary challenge for organizations in the Slovak Republic is to learn how to work with the collected data, the need for their appropriate structuring and subsequent archiving, which is manifested by the need for training and application of data analysts in a broader context. Full article

The article’s main goal is to describe the system design for the analysis of disinfection automated guided vehicle (AGV) utilisation so that the AGV’s optimal number can be determined. The simulation was used as the system’s main tool, allowing a relatively objective approach to imitate real system behaviour. With the proposed system, it is possible to determine the utilisation of AGVs and the number of necessary AGVs that carry out disinfection of the premises through the superstructure platforms. In the simulation model, two main modes of disinfection of ground AGV were tested. A regular circuit is carried out at specific intervals as well as a dynamic evaluation of the area and its possible contamination. When the area reaches a certain threshold, the instruction to disinfect the area is triggered. Experiments were carried out for a different number of AGVs, with the possible restriction of entry in the presence of the patient, and for a combination of specialised AGVs. Based on the results, we can conclude that the use of only surface-disinfecting AGVs is limited by the movement of patients and does not bring the same results as the use of a combination of surface- and air-disinfecting specialised AGVs. Full article

Thermal control systems have been introduced as an important part of electronic devices, enabling thermal management of their electronic components. Loop heat pipe (LHP) is a passive two-phase heat transfer device with significant potential for numerous applications, such as aerospace applications, high-power LEDs, and solar central receivers. Its advantages are high heat transfer capability, low thermal resistance, long-distance heat transfer, and compact structure. The essential role of wick structures on the performance of LHPs has already been highlighted, but no comprehensive review is available that deals with different parameters such as LHP design and wick size, which are largely decisive and effective in achieving a practical level of thermal transmission governed by wick structures. To rely on this necessity, this article summarizes, analyzes, and classifies advancements in the design and fabrication of wick structures. The main conclusion to be drawn after careful monitoring and weighing of the related literature is that LHPs with composites and additively manufactured wicks show a higher heat transfer coefficient than other conventional structures. Indeed, future works should be focused on the design of more structurally efficient wicks, which may allow us to optimize materials and geometrical parameters of wick structure for higher heat transfer through LHPs. Full article

In this study, a laser scanning machining system supporting on-the-fly machining and laser power follow-up adjustment was developed to address the increasing demands for high-speed, wide-area, and high-quality laser scanning machining. The developed laser scanning machining system is based on the two-master and multi-slave architecture with synchronization mechanism, and realizes the integrated and synchronous collaborative control of the motion stage or robot, the galvanometer scanner, and the laser over standard industrial ethernet networks. The galvanometer scanner can be connected to the industrial ethernet topology as a node, via the self-developed galvanometer scanner control gateway module, and a “one-transmission and multiple-conversion” approach is proposed to ensure real-time ability and synchronization. The proposal of a laser power follow-up adjustment approach could realize real-time synchronous modulation of the laser power, along with the motion of the galvanometer scanner, which is conducive to ensuring the machining quality. In addition, machining software was developed to realize timesaving and high-quality laser scanning machining. The feasibility and practicability of this laser scanning machining system were verified using specific cases. Results showed that the proposed system overcame the limitation of working field size and isolation between the galvanometer scanner controller with the stage motion controller, and achieved high-speed and efficient laser scanning machining for both large-area consecutively and discontinuously arrayed patterns. Moreover, the integration of laser power follow-up adjustment into the system was conducive to ensuring welding quality and inhibiting welding defects. The proposed system paves the way for high-speed, wide-area, and high-quality laser scanning machining and provides technical convenience and cost advantages for customized laser-processing applications, exhibiting great research value and application potential in the field of material processing engineering. Full article

Today, numerous design solutions require joining thin-walled sheets or profiles as the traditional methods of welding with a consumable electrode in gas shielding, most often used in production processes, do not work well. The reason for this is that a large amount of heat is supplied to the joint, causing numerous welding deformations, defects, and incompatibilities. Moreover, the visual aspect of the connections made more and more often plays an equally crucial role. Therefore, it is important to look for solutions and compare different joining processes in order to achieve production criteria. The paper compares the properties of a 1.5 mm thick steel sheet joined by the manual and robotic MAG 135 and 138 welding process, manual and robotic laser welding, CMT welding with the use of solid or flux-cored wire, and butt welding. The macro- and microstructure, as well as the microhardness distribution of individual regions of the joints, were analyzed depending on the type of joining technology used. Furthermore, the mechanical properties of individual zones of joints were investigated with the use of a digital image correlation system. On the basis of the obtained test results, it was found that the joints made by the processes of manual laser welding and butt welding were characterized by a very regular weld shape, the smallest joint width, and greater grain refinement compared to other analyzed processes. Moreover, this method was characterized by the narrowest zone of hardness increase, only 3 mm, compared to, e.g., a joint made in the process of robotic welding CMT, for which this zone was more than twice as wide. Furthermore, the heat-affected zone for the joints made in this way, in relation to the welds produced by the MAG 135/138 method, was, respectively, 2 and 2.7 times smaller. Full article

The product’s manufacturing process has an evident influence on product quality. In order to control the quality and identify the critical procedure of the product manufacturing process reasonably and effectively, a method combining genetic back-propagation (BP) neural network algorithm and grey relational analysis is proposed. Firstly, the genetic BP neural network algorithm is used to obtain the key quality characteristics (KQCs) in the product manufacturing process. At the same time, considering the three factors that have an essential impact on the quality of the procedures, the grey correlation analysis method is used to establish the correlation scoring matrix between the procedure and the KQCs to calculate the criticality of each procedure. Finally, taking the manufacturing process of the evaporator as a case, the application process of this method is introduced, and four critical procedures are identified. It provides a reference for the procedure quality control and improvement of enterprise in the future. Full article

Toxic gas leakage in metallurgic plants has emerged with the growth of crude steel production in recent years, causing damage to people, facilities, and the environment. Poisonous gas leakage can lead to other severe accidents including fires, explosions and gas poisoning. In this paper, we propose a risk assessment system (RAS) for toxic gas leakage using a fuzzy evaluation method integrating the entropy weighting method (EWM) and the order relationship method (ORM) and compiled an index system consisting of four first-level indices and fifteen secondary indices. The first-level indices are blast furnace safety performance, protective facilities, evacuation and dilution facilities, and poisonous gas management. The four first-level indices’ toxic gas leak evaluation result is 0.8581, 0.8971, 0.7733, and 0.8652, respectively. We observe that the overall status of the metallurgical plant is “excellent”, yet the result for the evacuation and dilution facilities was less than 0.8, indicating that there is still room for improvement. The risk evaluation time is reduced by forty percent by adopting RAS. Full article

The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area. Full article