Position Of Workpiece Research Articles

Improved Stiffness Modeling for An Exechon-Like Parallel Kinematic Machine (PKM) and Its Application

Hole drilling or contour milling for the large and complex workpieces such as automobile panels and aircraft fuselages makes a high combined demand on machining accuracy, stiffness and workspace of machining equipment. Therefore, a 5-DOF (degrees of freedom) parallel kinematic machine (PKM) with redundant constraints is proposed. Based on the kinematics analysis of the parallel mechanism using intermediate variables, the kinematics problems of the PKM are solved through equivalent kinematics model. The structural stiffness matrix method is adopted to model the stiffness of the parallel mechanism of the PKM, where the stiffness of each joint and branch component is obtained by stiffness formula and finite element analysis. And the stiffness model of the parallel mechanism is improved by correction coefficient matrix, each element of which is constructed as a polynomial function of three independent end variables of the parallel mechanism. The terminal stiffness matrices obtained by simulation result are used to determine the coefficients of polynomial function by least square fitting to describe the correction coefficient over the workspace of the parallel mechanism quantitatively. The experiment results prove that the modification method can greatly improve the stiffness model of the parallel mechanism. To enhance the machining accuracy of the PKM, the proposed kinematics model and the improved stiffness model are utilized to optimize the working stiffness of parallel machine by searching the best relative position of parallel machine and workpiece. A plate workpiece taken as example is examined in the case study section, which demonstrates the effectiveness of optimization method.

Binocular stereovision omnidirectional motion handling robot

Binocular stereovision has become one of the development trends of machine vision and has been widely used in robot recognition and positioning. However, the current research on omnidirectional motion handling robots at home and abroad is too limited, and many problems cannot be solved well, such as single operating systems, complex algorithms, and low recognition rates. To make a high-efficiency handling robot with high recognition rate, this article studies the problem of robot image feature extraction and matching and proposes an improved speeded up robust features (SURF) algorithm that combines the advantages of both SURF and Binary Robust Independent Elementary Features. The algorithm greatly simplifies the complexity of the algorithm. Experiments show that the improved algorithm greatly improves the speed of matching and ensures the real-time and robustness of the algorithm. In this article, the problem of positioning the target workpiece of the robot is studied. The three-dimensional (3-D) reconstruction of the target workpiece position is performed to obtain the 3-D coordinates of the target workpiece position, thereby completing the positioning work. This article designs a software framework for real-time 3-D object reconstruction. A Bayesian-based matching algorithm combined with Delaunay triangulation is used to obtain the relationship between supported and nonsupported points, and 3-D reconstruction of target objects from sparse to dense matches is achieved.

Complex Workpiece Positioning System With Nonrigid Registration Method for 6-DoFs Automatic Spray Painting Robot

To reduce the labor effort in hazardous environments like spray painting, an automatic car part spray painting machine has been set up. This article presents an intelligent location procedure for this machine. The location procedure assumes that the car part is placed with a tiny arbitrary pose, furthermore some kinds of parts under inspection undergoes through the deformation and thus it contains a nonrigid model. To tackle this problem, a workpiece positioning system works though multicamera is established first. Subsequently, a novel modified iterative closest point (ICP) algorithm is proposed which registers the nonrigid shape to the undeformed source shape in the training library. The modified ICP combines the ideas from traditional ICP and deformation estimation from bounded biharmonic weights. It solves a nonlinear cost function by using Levenberg–Marquardt algorithm. As a result, it estimates the transformation of the target point cloud with regards to the source point cloud. Additionally, it improves the accuracy of traditional ICP and increases its scope to nonrigid shapes. By employing these results in our location procedure, it can estimate the 6-DOF pose of the car part to be painted in addition to that it also estimates the deformation compared to the source cloud in the training library. This information is subsequently used to modify the guidance trajectory of the spray gun. In this article, a test case of front bumper is given, as it is commonly made of soft plastic materials and undergoes deformation under the influence of the external force. All the stated results support the efficacy of our algorithm.

Investigation of the effect of temperature and other significant factors on systematic error and measurement uncertainty in CMM measurements by applying design of experiments

The design of experiments was used in this paper in order to determine the significance of particular factors for the parameters that indicate the quality of measurement results obtained by means of a coordinate measuring machine (CMM). Special emphasis was placed on the interaction of temperature and other factors. In accordance with the design of experiments, the diameter and roundness of a ring gauge were measured at the reference temperature and at the temperature of 26 °C. The ISO 15530-3:2011 standard for the assessment of measurement uncertainty of CMM measurements distinguishes systematic error from measurement uncertainty. Thus, separate analyses were done on how temperature, in the first place, but also workpiece position on the CMM table, coordinate system, stylus tip diameter, sampling size and interaction of temperature with other factors affect systematic error and measurement uncertainty. The experimental results showed an increase in systematic error at the higher temperature when the diameter was measured, whereas with roundness, systematic error was even smaller at the higher temperature. As for measurement uncertainty, measurements made at the higher temperature have a significantly greater uncertainty when the diameter is measured, unlike with roundness, where the effect of temperature is almost negligible.

Automatic “Ground Truth” Annotation and Industrial Workpiece Dataset Generation for Deep Learning

In industry, it is becoming common to detect and recognize industrial workpieces using deep learning methods. In this field, the lack of datasets is a big problem, and collecting and annotating datasets in this field is very labor intensive. The researchers need to perform dataset annotation if a dataset is generated by themselves. It is also one of the restrictive factors that the current method based on deep learning cannot expand well. At present, there are very few workpiece datasets for industrial fields, and the existing datasets are generated from ideal workpiece computer aided design (CAD) models, for which few actual workpiece images were collected and utilized. We propose an automatic industrial workpiece dataset generation method and an automatic ground truth annotation method. Included in our methods are three algorithms that we proposed: a point cloud based spatial plane segmentation algorithm to segment the workpieces in the real scene and to obtain the annotation information of the workpieces in the images captured in the real scene; a random multiple workpiece generation algorithm to generate abundant composition datasets with random rotation workpiece angles and positions; and a tangent vector based contour tracking and completion algorithm to get improved contour images. With our procedures, annotation information can be obtained using the algorithms proposed in this paper. Upon completion of the annotation process, a json format file is generated. Faster R-CNN (Faster R-convolutional neural network), SSD (single shot multibox detector) and YOLO (you only look once: unified, real-time object detection) are trained using the datasets proposed in this paper. The experimental results show the effectiveness and integrity of this dataset generation and annotation method.

Analytical modeling of material removal mechanism in dry whirling milling process considering geometry, kinematics and mechanics

Whirling milling is a promising machining process that couples the tools and workpiece motions while both conventional turning and milling are carried out, which is widely used for machining precision screw parts made of hard materials, such as titanium alloy, quenched steel, etc. The challenge is due to the complex kinematics can lead to the varying tool-workpiece engagement and undeformed chip geometries which affect significantly the mechanics, quality and productivity. The existing studies are mainly based on the simplification of process mechanism to study the mechanics and quality however, the material removal mechanism and influences of cutting parameters are still not well understood. This paper presents an analytical approach to investigate the material removal mechanism in whirling milling, thus to predict the undeformed chip geometry, material removal rate (MRR), cutting forces and form errors. The varying tool-workpiece engagement geometry along the cutting trajectory is identified to model the varying undeformed chip geometry including instantaneous chip thickness, cross-section area and tool-workpiece contact length. The form errors including circularity error, scallop height and surface roughness are defined and predicted as a function of tools and workpiece motion, position and dimension parameters. The whirling milling experiments were conducted to validate the analytical modeling approach with the largest error 11.3% and average error 13.0% for force and surface roughness prediction, respectively. The influences of cutting parameters on surface roughness and MRR are finally analyzed to explore the potential of productive cutting conditions for whirling milling.

Weld Quality Verification by Using Laser Triangulation Measurement

Adaptive welding parameter control and robotic workpiece positioning feedback control impose a strict requirement on the dimensional measurement of the workpieces and fittings. Laser triangulation-based vision systems are commonly used to measure and compensate for the workpiece positioning inaccuracies as well as the inconsistencies of the weld seam. In this study, the laser triangulation system’s accuracy and reliability for welding quality control, workpiece positioning and welding parameter control are analyzed. The combined accuracy of both applied laser sensor and robot are analyzed and compared with the welding requirements. The study shows that the measurement and positioning accuracy of the robot is sufficient on reliable welding torch positioning for reaching and fulfilling the requirements of ISO 5817 level B class weld consistently. The measurement accuracy of the presented system and repeatability of the robot is well within the suitable measurement window for achieving consistent weld quality.

Effect of defocused plane on entrance and exit hole geometry of high grade steel 18CrNi8 during percussion drilling by Nd:YAG millisecond laser system

Modern manufacturing industries prefer laser drilling processes owing to the adequate controlled drilling in comparison with existing alternatives. The presented experimental study mainly accounts defocusing impact along with other technical parameters and optimization of Nd:YAG millisecond pulsed laser drilling; and finally their influence on the entrance and exit holes profile. The key technical parameters such as pulse frequency, pulse width and assisting gas pressure with respect to different defocused focal plane are explored experimentally for the percussion laser drilling of high grade steel 18CrNi8. Experiment results revealed that increase in defocusing distance has caused an increment in hole entrance diameter; however, with different defocusing distance, the entrance diameter increasing rate keep changing. Different trends of increasing and decreasing diameter at entrance and exit are recorded and investigated with respect to work-piece defocusing positions. The defocusing variation of laser beam has been investigated with the hole profile, changing from straight hole to tapered blind hole. Which leads to conclusive and optimized results for obtaining optimal hole profile (at entrance and exit). The optimum parametric combinations for attaining lower heat treatment effects are also discussed for superior hole quality.

A study on seam tracking in robotic GMA welding process

Abstract In recent years, an image processing and sensor technology for welding automation, intelligence and information with rapid development of welding automation have become an inevitable trend. Owing to the features of mass information, high reliability and applicability in weld inspection for robotic arc welding, the sensor-based weld seam detection has been widely applied and gradually become a hot topic. Furthermore, the robotic arc welding can use its own machine vision system to obtain workpiece positioning information, weld space position, bead geometry and weld seam tracking. The most important task in the machine vision system is how to process the collected visual information to accurately locate the center of the weld and achieve weld tracking. During the welding process, the images taken are often unclear and the features are not obvious due to the interference of arc, splash and smoke. Therefore, it is necessary to carefully design the image acquisition process and the image processing algorithm to complete the weld inspection. In this study, the robotic GMA(Gas Metal Arc) welding has been applied to bead-on-plate welding with vertical position. Thermal images of two different angles (0°, 30°) based on infrared camera through experiments might be obtained for developing an optimal image processing algorithm which was applied in seam tracking. In image processing procedure, the first step is image pre-processing including noise removal, contrast enhancement and binarization. The obtained image adopts multi-scale edge detection method, which can extract complex image edges well, then segment the image, accurately locate the weld part, perform image size measurement and centerline extraction, and finally convert the image information of the weld into the world calibration. The calculated data is then fed to a controller which controls the welding electrode movement. Use of machine vision system has eliminated the requirement to pre-feed the workpiece data for the robot to detect the dimension and position of the workpieces. The developed algorithm can detect weld image effectively, and extract the edge and the center line of the weld successfully

Point Cloud Registration Method for Pipeline Workpieces Based On NDT and Improved ICP Algorithms

A new point cloud registration method based on NDT and improved ICP algorithm is proposed to solve the problem of point cloud registration of laser scanning workpiece position and pose data on industrial pipeline. Firstly, according to the FPFH algorithm, the feature points of point clouds are extracted to reduce the number of point clouds. Then, the normal distribution transformation (NDT) is used to achieve rough registration of point clouds, so that the two point clouds have relatively good initial position and posture. Finally, based on the traditional ICP algorithm, the k-d tree is used to accelerate the search speed of the corresponding point pairs and complete the accurate registration of the point clouds. The proposed algorithm and the NDT+ICP algorithm are tested respectively, and the results show that the proposed algorithm is faster, with lower error and fewer iterations, which provides a reference for similar problems.

Simulation-based compensation of deflection errors in helical flute grinding

Static deflections of cylindrical blanks in tool grinding processes lead to core diameter deviations that vary with the axial workpiece position. This paper presents an approach to compensate these errors automatically in process planning. Hybrid modelling is used to predict the current local load, the stiffness based on the moment of inertia and the resulting elastic deflection at each time step. Subsequently, the process is optimized by adapting the process parameters and the tool path in the NC-code. In an experimental study, the core diameter deviation after flute grinding has been reduced in a range from 68% up to 87% using the developed approach.

Investigation of the key process parameters in the hot forming of a shackle

To investigate the impact of the variations of different input parameters in the multi-stage hot forging process of a shackle, an analysis is carried out through numerical simulations of the whole manufacturing process. Due to the complexity of the process and the large number of factors influencing the thermo-mechanical forming process, the investigation is focused on the workpiece positioning, the temperature of the tools, the transportation time and the contact-friction conditions. The analysis is narrowed down to the key stages of the process that are closed-die forging and ram bending. Coupled with experimental measurements, a comparison of forging loads, functional dimensions and shackle geometry is presented. It is shown that the conformation of shackle geometry to the industrial specifications depends mainly on the workpiece positioning and the transportation time. The dispersion measured in the forging load and in the main dimensions can thus be explained and these observations can be used to improve the manufacturing process for shackles.

Point Cloud Registration Method for Pipeline Workpieces Based on 4PCS and Improved ICP Algorithms

A new point cloud registration method based on 4PCS and improved ICP algorithm is proposed to solve the problem of point cloud registration of laser scanning workpiece position and pose data on industrial pipeline. Firstly, feature points set of point cloud is extracted from normal vector. Then, the rough registration of point cloud is realized by using the registration algorithm based on feature points (4PCS), and the initial recognition of workpiece position and pose is completed. Finally, based on the traditional ICP algorithm, the k-d tree is used to accelerate the search speed of the corresponding point pairs and complete the accurate registration of the point clouds. The proposed algorithm and the 4PCS+ICP algorithm are tested respectively, and the results show that the algorithm is faster, with lower error and fewer iterations.

Pick-and-Place Task Implementation Using Visual Open-Loop Control

Abstract In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.

Investigation on deformation of single-sided stringer parts based on fluctuant initial residual stress

Deformation has a significant effect on the machining accuracy of the monolithic components. Fluctuant initial residual stress is one of the factors causing deformation. In this paper, initial residual stresses of six specimens of 7050-T7451 aluminum alloy plates with 65 mm thickness and 70 mm thickness are measured respectively. Fluctuant initial residual stresses are fitted by segmented polynomials of best uniform approximation. An analytical model in terms of the deformation and initial residual stress is established for single-sided stringer parts. The results show that the weight of web-induced deformation in the whole deformation of the part is about 74%–98.5% and the weight sidewall-induced deformation is about 1.5%–26%. Therefore, minimizing the web-induced deformation is the key to minimize the whole part deformation. The condition number calculated by coefficients matrix of initial residual stress inside the web is defined in the model. The value of condition number is determined by initial residual stress inside the web and its fluctuant degree, which is positively correlated with web-induced deformation when the structural stiffness is invariant. By selecting the blank with a small fluctuant amplitude of stress or changing the workpiece position, condition number will be decreased, and the deformation is minimized.

Effect of various factors influencing the generation of hemispherical micro features using non-conformal RMEDM

Non-conformal reverse micro electrical discharge machining (NC-RMEDM) is a variant of conventional RMEDM developed by the present authors wherein modification in the tool is carried out to generate different shapes of micro features. In this study, the effect of various factors like flat bottom and taper bottom hole, inversing the position of tool and workpiece and changing the hole depth have been experimentally investigated to determine the optimal combination required for generating hemispherical shaped micro features. It was found that hemispherical shaped micro feature can be generated by employing tapered bottom blind hole as tool. Buoyancy assisted machining (BAM) with traverse of workpiece (anode) downwards into the tool (cathode) and vice versa, i.e., buoyancy opposed machining (BOM) with traverse of tool downwards into the workpiece were carried out to study the generation of hemispherical micro feature based on inversion of electrode positions. Although both BAM and BOM generated hemispherical shaped feature, BAM is preferred due to reduced machining time as opposed to BOM. Also, increasing the hole depths led to altering the shape of micro feature from hemispherical to cylindrical with hemispherical end and coni-spherical end. An array of hemispherical micro features was fabricated based on the finding from this study, and surface roughness analysis was carried out which showed that irrespective of the position of micro feature on the array, surface roughness at the tip and base of the micro feature is lower as compared to side portion.

A Distributive Approach for Position Control of Clamps in a Reconfigurable Assembly Fixture

Hydraulic actuator is a type of clamp used in a reconfigurable assembly fixture for exact positioning and effective immobilisation of workpiece during the assembly process. However, due to their nonlinearity, there is a need to design a control system for their effective performance. This study presents a distributive approach to mathematical modelling and position control of multiple hydraulic actuators used as a clamping system in a reconfigurable assembly fixture. The electrohydraulic system is verified experimentally in order to observe the synchronisation of the hydraulic actuators. The mathematical model of the system is developed in the Simulink environment. A Simulink model of the system is developed from the mathematical model and simulated with a fuzzy-PID controller in order to obtain the response of all the actuators and other operating characteristics of the system. Simulation results are shown graphically in order to verify the theoretical development.

Automatic robot path integration using three-dimensional vision and offline programming

In manufacturing industries, offline programming (OLP) platforms provide an independent methodology for robot integration using 3D model simulation away from the actual robot cell and production process, reducing integration time and costs. However, traditional OLP platforms still require prior knowledge of the workpiece position in a predefined environment, which requires complex human operations and specific-purpose designs, highly reducing the autonomy of the systems. The presented approach proposes to overcome these problems by defining a novel automated offline programming system (AOLP), which integrates a flexible and intuitive OLP platform with a state-of-the-art autonomous object pose estimation method, to achieve an environment and model independent platform for automatic robotic manufacturing. The autonomous recognition capabilities of the three-dimensional vision system provide the relative position of the workpiece model in the OLP platform, with robustness against clutter, illumination, and object material. After that, the user-friendly OLP platform allows an efficient and automatic path generation, simulation, robot code generation, and robot execution. The proposed system precision and robustness are analyzed and validated in a real-world environment on four different sets of experiment. Finally, the proposed system’s features are discussed and compared with other available solutions for practical industrial manufacturing, showing the advantages of the proposed approach. Overall, despite sensor resolution limitations, the proposed system shows a remarkable precision and promising direction towards highly efficient and productive manufacturing solutions.

The study of spindle finishing with sand abrasive media

Abstract The unbound abrasive processing has several advantages compared with the abrasive wheels grinding. However, abrasive granules or traditional abrasive materials are used as an abrasive medium in this process. In this study, the performance of the spindle grinding process by the unbound sand abrasive and the processed surface quality while varying the work piece position and its relative movement were investigated. As a result of the study, further research directions were determined and recommendations on the process use in the machine parts production were given.

Research on Edge Detection Algorithm Based on Line Laser Scanning

With the aim of obtaining the precise position of workpiece, it is necessary to detect the base hole during the automated manufacturing process of robotic drilling systems. In this paper, a detection method based on the line laser is presented to detect the base hole of large aviation parts in manufacturing and assembly. The 3-D point cloud data processing plays an important role during the detection process with a line laser. To extract the point cloud data effectively, an edge detection algorithm which includes a gradient-based edge extraction algorithm and an edge parameterization method is proposed. Then, the correlation analysis of the proposed algorithm is conducted. Finally, an industrial case is presented to illustrate the applicability and effectiveness of the proposed edge detection algorithm. The effects of varying the scan line spacing of the line laser are studied so as to meet the practical need of engineering application. The results indicate that the edge detection algorithm is applicable to the robotic drilling system, and it is reasonable and practicable to use the elliptic curve to parameterize the hole’s edge.