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This study aims at compensating for sintering deformation of components manufactured by metal binder jetting (MBJ) technology.

In the present research, numerical simulations are used to predict sintering deformation. Subsequently, an algorithm is developed to counteract the deformations, and the compensated deformations are morphed into a CAD model for printing. Several test cases are designed, compensated and manufactured to evaluate the accuracy of the compensation calculations. A consistent accuracy measurement method is developed for both green and sintered parts. The final sintered parts are compared with the desired final shape, and the accuracy of the model is discussed. Furthermore, the effect of initial assumptions in the calculations, including green part densities, and green part dimensions on the final dimensional accuracy are studied.

The proposed computational framework can compensate for the sintering deformations with acceptable accuracy, especially in the directions, for which the used material model has been calibrated. The precise assumption of green part density values is important for the accuracy of compensation calculations. For achieving tighter dimensional accuracy, green part dimensions should be incorporated into the computational framework.

Several studies have already predicted sintering deformations using numerical methods for MBJ parts. However, very little research has been dedicated to the compensation of sintering deformations with numerical simulations, and to the best of the best of the authors' knowledge, no previous work has studied the effect of green part properties on dimensional accuracy of compensation calculations. This paper introduces a method to omit or minimize the trial-and-error experiments and leads to the manufacturing of dimensionally accurate geometries.

The purpose of this study is to mitigate the dimensional inaccuracy due to vertical curling/bending deformation of three-dimensional (3D) printed parts produced by selective laser sintering (SLS) using PA12 based on dimensional compensation of the computer-aided design (CAD) model.

To carry out this study, specially designed features are initially produced as references, and the dimensional deviations from the vertical bending deformation of the SLS process are analyzed. Next, the deformation patterns are formulated using a polynomial regression model in the global Cartesian coordinates of the building platform. Then, the compensation algorithm is implemented and the original 3D CAD file is preprocessed with an inverse transformation of the features to compensate the deformation errors.

It was found that the 3D printed parts from the SLS process have the dimensional inaccuracy due to the vertical bending pattern of the quadratic form. By implementing the compensation algorithm, it was statistically shown to effectively reduce bending deformations of various sample parts, including the automotive components, in SLS.

The position of samples in a batch has a direct impact on not only bending deformation but also on horizontal shape geometry error. However, the application of this algorithm is focused on the vertical bending deformation, which is estimated as a major part of dimensional inaccuracy.

This paper provides a practical case study with a real vehicle part. The algorithm was shown to provide a more realistic solution to the dimensional deformation of printed products, which is not manageable by simply using the constant scale factors provided by SLS 3D printer manufacturers.

This paper suggests that the vertical bending deformation from SLS’s 3D printed complex parts can be improved through the proposed compensation algorithm. The compensation algorithm was constructed by using the predictive regression model created from the bending deformation patterns of reference samples. The proposed compensation algorithm can be further used and applied for other complex samples without making additional reference parts.

The purpose of this paper is to accurately obtain the deformation of a hybrid robot and rapidly enable real-time compensation in friction stir welding (FSW). In this paper, a prediction algorithm based on the back-propagation neural network (BPNN) optimized by the adaptive genetic algorithm (GA) is presented.

Via the algorithm, the deformations of a five-degree-of-freedom (5-DOF) hybrid robot TriMule800 at a limited number of positions are taken as the training set. The current position of the robot and the axial force it is subjected to are used as the input; the deformation of the robot is taken as the output to construct a BPNN; and an adaptive GA is adopted to optimize the weights and thresholds of the BPNN.

This algorithm can quickly predict the deformation of a robot at any point in the workspace. In this study, a force-deformation experiment bench is built, and the experiment proves that the correspondence between the simulated and actual deformations is as high as 98%; therefore, the simulation data can be used as the actual deformation. Finally, 40 sets of data are taken as examples for the prediction, the errors of predicted and simulated deformations are calculated and the accuracy of the prediction algorithm is verified.

The entire algorithm is verified by the laboratory-developed 5-DOF hybrid robot, and it can be applied to other hybrid robots as well.

Robots have been widely used in FSW. Traditional series robots cannot bear the large axial force during welding, and the deformation of the robot will affect the machining quality. In some research studies, hybrid robots have been used in FSW. However, the deformation of a hybrid robot in thick-plate welding applications cannot be ignored. Presently, there is no research on the deformation of hybrid robots in FSW, let alone the analysis and prediction of their deformation. This research provides a feasible methodology for analysing the deformation and compensation of hybrid robots in FSW. This makes it possible to calculate the deformation of the hybrid robot in FSW without external sensors.

The purpose of this paper is to propose a posture evaluation approach based on temperature compensation and three-dimensional (3-D) tolerance for the key points (KPs).

A large component 3-D compensation model of thermal deformation considering characteristics of the assembly object is developed. Then, the thermal deformation compensation model is used to modify the nominal coordinates for the KPs. By using a combination of relative deviations of KPs as the objective and 3-D tolerance as the constraints, an optimization model for posture evaluation is established.

Deviations of posture and KPs’ coordinates are obtained by solving the non-linear constrained optimization problem. The posture evaluation method is demonstrated in both a simulation case and practical implication of the aircraft components assembly system with the result that a good performance is obtained.

The proposed method has been used in several aircraft assembly projects in China, and gained a good effect.

This paper proposes a method for eliminating the affection of thermal deformation during posture evaluation process and improving the consistency and stability of posture evaluation results. The results of this research will help to systematically improve the manufacturing process and tolerance allocation efficiency in large aircraft assembly.

The purpose of this paper is to propose an innovative method to extend the operating range of the laser tracking system and improve the accuracy and automation of boresighting by designing a measurement instrument. Boresighting is a process that aligns the direction of special equipment with the aircraft reference axis. Sometimes the accurate measurement and adjustment of the equipment and the aircraft are hard to achieve.

The aircraft is moved by an automatic adjustment system which consists of three numerical control positioners. For obtaining the position of the bore axis, an instrument with two measurement points is designed. Based on the multivariate normal distribution hypothesis, an uncertainty evaluation method for the aiming points is introduced. The accuracy of the measurement point is described by an uncertainty ellipsoid. A compensation and calibration method is proposed to decrease the effect of manufacturing error and deflection error by the finite element analysis.

The experimental results of the boresighting measurement prove that the proposed method is effective and reliable in digital assembly. The measurement accuracy of the angle between the bore axis and the reference axis is about ±0.004°. In addition, the measurement result is mainly influenced by the position error of the instrument.

The results of this study will provide a new way to obtain and control the installation deviation of part in aircraft digital assembly and will help to improve the precision and efficiency. This measurement method can be applied to obtain the axis of a deep blind hole.

The purpose of this study with the rapid development of the heavy/large mechanical equipment, the heavy computer numerical control (CNC) vertical lathe has become the ideal processing equipment for the parts of those mechanical equipments. The main factor which affects the machining quality and efficiency of heavy CNC vertical lathe is the mechanical properties of the hydrostatic thrust bearing.

This paper did the research based on the large size sector oil pad’s lubrication performance of the hydrostatic thrust bearing in the heavy/large equipments, establishing the lubrication performance distribution mathematical model of the velocity field, flow field, pressure field and so on, analyzing the bearing behavior of the large size sector oil pad.

The results show that the oil flow generated by the plate relative motion will be greater than that generated by the pressure difference in area B, with the rotational speed’s increasing of the hydrostatic thrust bearing, and the direction is opposite. The oil flow generated by the centrifugal force will be greater than that generated by the pressure difference in area C, with the rotational speed’s increasing of the hydrostatic thrust bearing, and the direction is opposite. When the rotational speed of the hydrostatic thrust bearing is too high, the friction heat will be not easy to be sent out. The bearing rotating speed should be lower than the comparatively smaller one of ω1 and ω2, which can help avoid the rise of too high temperature.

The research provides powerful theoretical foundation for practical application of the large size sector oil pad hydrostatic thrust bearing, its structure design and operating reliability, realizing the lubrication performance prediction of the large size hydrostatic thrust bearing.

This paper aims to present the critical issues and methodologies to improve robotic machining performance with flexile industrial robots.

A complete solution using active force control is introduced to address various issues during the robotic machining process.

Programming complex couture parts without a CAD model is made easy by using force control functions such as lead‐through and path‐learning. The problem of process control is treated with a novel methodology that consists of stiffness modeling, real‐time deformation compensation for quality and controlled material removal rate for process efficiency.

Experimental results showed that higher productivity as well as better surface quality can be achieved, indicating a promising and practical use of industrial robots for machining applications that is not available at present.

Flexible automation robotic systems and off‐line programming methods have recently received much attention. Studies the problem of robot auto‐marking and auto‐cutting of shipbuilding panels, using an integrated computer aided design/manufacturing (CAD/CAM) system based on computer technology and off‐line programming of the robot. The following three points are focused on in this paper: marking and cutting information of the panel’s CAD model; measurement of the panel’s deformation and its compensation algorithm; robot auto‐making and auto‐cutting of the panel using the CAM system. Robot auto‐marking and auto‐cutting of shipbuilding panels solves the difficulty associated with panel marking and cutting by hand. Furthermore this system possesses high processing precision and automatically compensates for the deformation of the panel. Our experiments prove the feasibility and efficiency of this system at the end of this paper.

The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.

Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.

The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10⁻¹ mm and the maximum value of posture error is reduced from 1.07 × 10⁻³ rad to 6.02 × 10⁻⁴ rad, which is superior to the accuracy without considering the gravity factor.

This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.

Remote handling (RH) manipulators have been widely studied for maintenance tasks in fusion reactors. Those tasks always require heavy load, high accuracy and large work space for manipulators. Traditionally, the maintenance of fusion devices always depends on manual RH. With the development of calculating ability, the intelligent automatic maintenance makes it possible for a fusion device instead of the previous manual operation. As the flexibility of arm and the deformation of manipulator will cause problems, which are mainly inaccuracy and lower efficiency. This paper aims to study an effective way to promote the arm behavior to solve these problems.

By making use of the experimental advanced superconducting tokamak articulated maintenance arm as a platform, a series of experiments is designed to measure errors of kinematics and to collect the database of the flexible arm. Through studying the data and the arm structure, recurrent neural network (RNN) method was adopted to estimate the deformation of flexible arm and eventually compensate deformation in robot control to achieve higher accuracy.

By means of delicate RNN modeling, errors of kinematics have been reduced to a smaller order than the RH mode. This intelligent maintenance method will also reduce complexity of operations in maintenance.

This paper presents the use of an artificial intelligent algorithm to solve a nonlinear deformation problem of the flexible arm. The results demonstrate that it is efficient in dealing with this problem in fusion application. The RNN’s successful application has also shown that intelligent algorithms can be widely applied in fusion maintenance.