Showing papers in "Robotics and Computer-integrated Manufacturing in 2016"

Collaborative manufacturing with physical human–robot interaction

Abstract: Although the concept of industrial cobots dates back to 1999, most present day hybrid human-machine assembly systems are merely weight compensators. Here, we present results on the development of a collaborative human-robot manufacturing cell for homokinetic joint assembly. The robot alternates active and passive behaviours during assembly, to lighten the burden on the operator in the first case, and to comply to his/her needs in the latter. Our approach can successfully manage direct physical contact between robot and human, and between robot and environment. Furthermore, it can be applied to standard position (and not torque) controlled robots, common in the industry. The approach is validated in a series of assembly experiments. The human workload is reduced, diminishing the risk of strain injuries. Besides, a complete risk analysis indicates that the proposed setup is compatible with the safety standards, and could be certified.

Robot skills for manufacturing

Abstract: Due to a general shift in manufacturing paradigm from mass production towards mass customization, reconfigurable automation technologies, such as robots, are required. However, current industrial robot solutions are notoriously difficult to program, leading to high changeover times when new products are introduced by manufacturers. In order to compete on global markets, the factories of tomorrow need complete production lines, including automation technologies that can effortlessly be reconfigured or repurposed, when the need arises. In this paper we present the concept of general, self-asserting robot skills for manufacturing. We show how a relatively small set of skills are derived from current factory worker instructions, and how these can be transferred to industrial mobile manipulators. General robot skills can not only be implemented on these robots, but also be intuitively concatenated to program the robots to perform a variety of tasks, through the use of simple task-level programming methods. We demonstrate various approaches to this, extensively tested with several people inexperienced in robotics. We validate our findings through several deployments of the complete robot system in running production facilities at an industrial partner. It follows from these experiments that the use of robot skills, and associated task-level programming framework, is a viable solution to introducing robots that can intuitively and on the fly be programmed to perform new tasks by factory workers. HighlightsWe propose a conceptual model of robot skills and show how this differs from macros.We show how this approach can enable non-experts to utilize advanced robotic systems.Concrete industrial applications of the approach are presented, on advanced robot systems.

Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing

Abstract: Wire and arc additive manufacturing (WAAM) is a promising alternative to traditional subtractive methods for fabricating large aerospace metal components that feature high buy-to-fly ratios. This study focuses on the development of an automated manufacturing system in order to free the operator from intervening in the analysis of the CAD model, planning the deposition path, and then manually setting the welding process parameters. Firstly, the relationship between single bead geometry and welding process parameters is established through an artificial neural network (ANN) model. Then, the adaptive medial axis transformation (MAT) algorithm for void-free deposition with high geometrical accuracy is introduced. The adaptive MAT path is implemented by using the single bead ANN model together with a previously developed multi-bead overlapping model. Finally, the adaptive MAT path planning strategy and the established bead models are tested through experimental deposition of two metal components. The results show that the developed bead model and adaptive MAT-based path are capable of producing depositions with high quality (void-free) and geometrical accuracy through automated selection of process variables for the WAAM process. This study developed an automated wire arc additive manufacturing system.An artificial neural network (ANN) bead model is established.An innovative path planning strategy is introduced.Practical implementation of an automated deposition system is reported.Experiments are conducted through automated selection of process variables.

Finishing of Fused Deposition Modeling parts by CNC machining

Abstract: Fused Deposition Modeling is a filament extrusion-base Additive Manufacturing process that integrates Computer Aided Design system, material science, Computer Numerical Control and the extrusion process to fabricate physical parts without geometrical limitations. Notwithstanding the wide industrial diffusion, one of the most limiting aspects of this technology is the obtainable surface roughness. This limitation implies that secondary finishing operations are necessary in order to comply with the design requirements. Several efforts have been done in this field but a lack exists about Computer Numerical Control machining: the Fused Deposition Modeling mesostructure and the anisotropic surface morphology, which strongly depends upon the deposition angle, make very difficult the determination of the cutting process parameters. The aim of this work is to develop a methodology able to unlock the possibility to finish Fused Deposition Modeling parts by Computer Numerical Control machining. A variable cutting depth has been considered to avoid inner defects arising and to eliminate initial surface morphology. An experimental campaign allowed to determine how cutting depth should be set as a function of deposition angle. A particular virtual model offset permitted to generate in Computer Aided Manufacturing the machine code. A case study characterized by functional surfaces confirmed the applicability of the method to complex geometry: a great reduction of average roughness and a reliable uniformity of finished surfaces have been obtained. A methodology to improve Fused Deposition Modeling roughness has been developed.The finishing has been performed by Computer Numerical Control machining.A variable cutting depth as a function of the deposition angle has been determined.The surface inside a Pelton bucket has been successfully finished.

Effect of technical parameters on porous structure and strength of 3D printed calcium sulfate prototypes

Abstract: Additive manufacturing methods such as three-dimensional printing (3DP) show a great potential for production of porous structure with complex internal and external structures for bone tissue engineering applications. To optimize the 3DP manufacturing process and to produce 3D printed parts with the requisite architecture and strength, there was a need to fine-tune the printing parameters. The purpose of this study was to develop optimal processing parameters based on a design of the experiments approach to evaluate the ability of 3DP for making calcium sulfate-based scaffold prototypes. The major printing parameters examined in this study were layer thickness, delay time of spreading the next layer, and build orientation of the specimens. Scaffold dimensional accuracy, porosity, and mechanical stiffness were systematically investigated using a design of experiment approach. Resulting macro-porous structures were also studied to evaluate the potential of 3DP technology for meeting the small-scale geometric requirements of bone scaffolds. Signal-to-noise ratio and analysis of variance (ANOVA) were employed to identify the important factors that influence optimal 3D printed part characteristics. The results showed that samples built using the minimum layer thickness (89?m) and x-direction of build bed with 300ms delay time between spreading each layer yielded the highest quality scaffold prototypes; thus, these parameters are suggested for fabrication of an engineered bone tissue scaffold. Furthermore, this study identified orientation and new layer spreading delay time as the most important factors influencing the dimensional accuracy, compressive strength, and porosity of the samples. Display Omitted Cylindrical calcium sulfate-based prototypes were designed, printed, and characterized.3DP process was optimized by a design of experiment approach and statistical analysis.Dimensional accuracy, porosity, and mechanical stiffness were evaluated.x-direction built samples with 89 ?m layer thickness and 300 ms delay time were optimal prototypes.Orientation and delay time were the most important factors influencing the quality of the samples.

Automatic multi-direction slicing algorithms for wire based additive manufacturing

Abstract: One of the key challenges in Additive Manufacturing is to develop a robust algorithm to slice CAD models into a set of layers which requires minimal support structures. This paper reports the concept and implementation of a new strategy for multi-direction slicing of CAD models represented in STL format. Differing from the existing multi-direction slicing approaches that are mainly focused on finding an optimal volume decomposition strategy, this study presents a decomposition-regrouping method. The CAD model is firstly decomposed into sub-volumes using a simple curvature-based volume decomposition method. Then a depth-tree structure based on topology information is introduced to merge them into ordered groups for slicing. In addition, a model simplification step is introduced before CAD model decomposition to significantly enhance the capability of the proposed multi-direction strategy. The proposed strategy is shown to be simple and efficient on various tests parts especially for geometries with large number of holes. Multi-direction slicing algorithms are developed for wire based additive manufacturing.A new strategy of volume decomposition-regrouping is reported.Model simplification (hole-filling) is performed to simplify CAD models.The proposed strategy is simple and efficient.

Developing an MCDM method for robot selection with interval type-2 fuzzy sets

Abstract: Industrial robots have been increasingly used by many manufacturing firms in different industries. The selection of robots for a particular application and manufacturing environment is a difficult task for decision makers. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. The decision maker needs to identify and select the best-suited robot in order to achieve the desired output with respect to many criteria. In the decision-making process, we usually confront with ambiguity and uncertainty for evaluating the criteria weights and alternatives of the problem. Interval type-2 fuzzy sets which are characterized by an interval membership function can provide us with more degrees of freedom to represent the uncertainty of the real-world problems. This paper presents a multi-criteria group decision-making approach for robot selection in the context of type-2 fuzzy sets. We propose a method based on Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method with interval type-2 fuzzy numbers to handle this problem. The best alternative (robot) is selected in the developed method according to both the ideal and the nadir solutions without defuzzification. An example with eight alternatives (robots) and seven commonly used criteria is used to illustrate the proposed method. We compare the results with some existing methods to show the validity of the extended method. Seven sets of criteria weights and the Spearman correlation coefficient are also utilized for analyzing the stability of the proposed method. It is observed that the obtained rankings of the proposed method are relatively consistent with the other methods and have good stability in different criteria weights. We focus on fuzzy multi-criteria group decision-making for robot selection.Interval type-2 fuzzy sets are considered in this research.An extended version of VIKOR method is developed for group decision-making.An example is utilized for showing the application of the proposed method in robot selection.We compare and analyze the results of the proposed method to represent the validity of it.

Design for manufacturing of surfaces to improve accuracy in Fused Deposition Modeling

Abstract: Fused Deposition Modeling is an Additive Manufacturing technology able to fabricate prototypes, tooling and functional parts without geometrical complexity limitations Despite of the potential advantages of this technology, a limiting aspect of its industrial diffusion is the obtainable accuracy The literature highlighted that significant deviations from the nominal values are observed: these deviations are not constant over all the part surfaces but strictly depend upon the process parameters, ie the layer thickness and the deposition angle This involves poor surface quality: the parts could not satisfy the design specifications nor assure the functionality and the assembly fit with other components The aim of this work is the development of a design for manufacturing methodology able to improve the dimensional accuracy obtainable by this technology It operates in the design model step performing a virtual model preprocessing: an anisotropic offset is applied to the surfaces, defined by a mathematical formulation, in order to compensate for the abovementioned dimensional deviations This way, without to eliminate the physical sources of the errors, it is possible to obtain a part with dimensional values very close to nominal ones This method does not require any additional resources for its application such as preliminary artifact construction and measurements A design for manufacturing to improve FDM part accuracy is proposedA redesign of the solid allows compensating for the dimensional deviationThe model surfaces are modified by means of an anisotropic offsetThe proposed method is applied to parts defined by a mathematical formulationThe method is validated through the application to three mechanical components

Towards industrial internet of things

Abstract: The large number of requirements and opportunities for automatic identification in manufacturing domains such as automotive and electronics has accelerated the demand for item-level tracking using radio-frequency identification technology. End-users are interested in implementing automatic identification systems, which are capable of ensuring full component process history, traceability and tracking preventing costly downtime to rectify processing defects and product recalls. The research outlined in this paper investigates the feasibility of implementing an RFID system for the manufacturing and assembly of crankshafts. The proposed solution involves the attachment of bolts with embedded RFID functionality by fitting a reader antenna reader to an overhead gantry that spans the production line and reads and writes production data to the tags. The manufacturing, assembly and service data captured through RFID tags and stored on a local server, could further be integrated with higher-level business applications facilitating seamless integration within the factory. An RFID implementation for the manufacturing and assembly processes of crankshafts in the automotive industry is studied.A reader antenna on an overhead gantry that spans the production line can read/write data to the reusable RFID bolts' IC.The proposed RFID system enables full part genealogy and process history of crankshafts throughout production operations.

Kinematic calibration of a 3-DoF rotational parallel manipulator using laser tracker

Abstract: This paper proposes a laser tracker based kinematic calibration of a 3-degree-of-freedom (DoF) rotational parallel manipulator that would be applied in tracking and positioning fields. The process is implemented in this paper by four steps: 1) formulation of the geometric error model of this manipulator by means of screw theory considering all possible geometric source errors, which is followed by the verification of this error model employing SolidWorksź software. 2) sensitivity analysis of all geometric source errors based upon Monte Carlo method and remove some errors that have little influence on the pose accuracy of the moving platform in order to decrease the difficulty and complexity of the kinematic calibration. 3) error parameter identification and kinematic calibration experiment using laser tracker. 4) error compensation by amending controller model. Kinematic calibration experiment results of this 3-DoF rotational parallel manipulator show that three angular deviations are improved from 1.97°, 0.24° and 1.75° to 0.53°, 0.10° and 0.19° respectively within the prescribed workspace. Geometric error modeling based on screw theory is presented.The geometric error model is verified based upon the software method.Calibration includes sensitivity analysis, measurement plan and error identification.Software simulation and experiment are given to verify kinematic calibration flow.

Robotic path planning for non-destructive testing – A custom MATLAB toolbox approach

Abstract: The requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides motivation for the use of 6 axis robots in these inspections. The purpose of this paper is to present work undertaken for the development of a KUKA robot manipulator based automated NDT system. A new software solution is presented that enables flexible trajectory planning to be accomplished for the inspection of complex curved surfaces often encountered in engineering production. The techniques and issues associated with conventional manual inspection techniques and automated systems for the inspection of large complex surfaces were reviewed. This approach has directly influenced the development of a MATLAB toolbox targeted to NDT automation, capable of complex path planning, obstacle avoidance, and external synchronization between robots and associated external NDT systems. This paper highlights the advantages of this software over conventional off-line-programming approaches when applied to NDT measurements. An experimental validation of path trajectory generation, on a large and curved composite aerofoil component, is presented. Comparative metrology experiments were undertaken to evaluate the real path accuracy of the toolbox when inspecting a curved 0.5 m2 and a 1.6 m2 surface using a KUKA KR16 L6-2 robot. The results have shown that the deviation of the distance between the commanded TCPs and the feedback positions were within 2.7 mm. The variance of the standoff between the probe and the scanned surfaces was smaller than the variance obtainable via commercial path-planning software. Tool paths were generated directly on the triangular mesh imported from the CAD models of the inspected components without need for an approximating analytical surface. By implementing full external control of the robotic hardware, it has been possible to synchronise the NDT data collection with positions at all points along the path, and our approach allows for the future development of additional functionality that is specific to NDT inspection problems. For the current NDT application, the deviations from CAD design and the requirements for both coarse and fine inspections, dependent on measured NDT data, demand flexibility in path planning beyond what is currently available from existing off-line robot programming software.

A cost-effective and automatic surface defect inspection system for hot-rolled flat steel

Abstract: Defective steel brings economic and commercial reputation losses to the hot-strip manufacturers, and one of the main difficulties in using machine-vision-based technique for steel surface inspection is time taken to process the massive images suffering from uneven illumination. This paper develops a modular and cost-effective AOI system for hot-rolled flat steel in real time. Firstly, a detailed system topology is constructed according to the design goals covering the vast majority of steel mills, lighting setup and typical defect patterns are presented as well. Secondly, the image enhancement method is designed to overcome the uneven-lighting, over- or under-exposure. Thirdly, the defect detection algorithm is developed based on variance, entropy and average gradient derived from non-overlapping 32×32 pixel blocks of steel surface images. Fourthly, the proposed algorithms are implemented on FPGA in parallel to improve the inspection speed. Finally, 18,071 contiguous images (4096×1024 pixel) acquired from 7 defective steel rolls have been inspected by the realized AOI system to evaluate the performance. The experimental results show that the proposed method is speedy and effective enough for real applications in the hot-rolled steel manufacturing, with 92.11% average accuracy while 5.54% false-negative rate. HighlightsDetailed system topology is constructed according to the design goals covering the vast majority of steel mills.A new dynamic image enhancement method is designed to overcome the uneven-lighting, over- or under-exposure.A defect detection algorithm with adaptive thresholding mechanism is developed based on image block variance, entropy and average gradient.The inspection speed of the proposed algorithms running on FPGA is evaluated.Testing procedures and evaluation results from the applied hot-rolling mill are discussed.

Real-time smooth trajectory generation for nonholonomic mobile robots using Bézier curves

Abstract: This paper focuses on generating smooth trajectories for a wheeled nonholonomic mobile robot using piecewise Bezier curves with properties ideally suited for this purpose. The developed algorithm generates smooth motion trajectories with C2 continuous curvature. We consider a teleoperated wheeled mobile robot in an indoor environment with ceiling cameras for operator visibility. The motion trajectory is constrained by the operator-specified via points and path width. A method to automatically generate a trajectory based on only these two inputs is proposed and demonstrated. To improve the trackability of the mobile robot, we adopted a Bezier subdivision method and inserted a quintic Bezier segment into high-curvature areas. The proposed algorithm can be used for real-time obstacle-avoidance trajectory generation because it allows trajectory subdivision and arbitrarily setting of the second derivative at the start point. Simulation and experimental results demonstrate the effectiveness of the proposed method. HighlightsNew algorithm to generate smooth trajectories for a wheeled mobile robot.Trajectory generation satisfying operator-specified via points and path width.Trackability enhancement to high-curvature trajectory by Bezier subdivision method.Design of a trajectory tracking controller based on the Lyapunov stability theorem.

Positional error similarity analysis for error compensation of industrial robots

Abstract: The purpose of this paper is to propose an error compensation method with error similarity analysis to improve the absolute positional accuracy of industrial robots. The positional error similarity is proposed with the analysis of the error model established by robot kinematic parameters, and is quantified with semivariogram function. Then an error compensation method is proposed base-on positional error similarity. The ordinary Kriging method is used to calculate the positional errors of the robot TCP. The error compensation is performed by modifying the position coordinates in the robot controlling commands. Experimental verification showed that the maximum positional error of the robot TCP was reduced by 75.36% from 1.2912mm to 0.3182mm. HighlightsThe positional errors of the industrial robot has similarity in the working space.The error similarity decreases as the distance between two positions increases.The proposed method doesn't need to identify or modify the kinematic parameters.The proposed method can effectively reduce the maximum positional errors of the robot.

Computationally efficient and robust kinematic calibration methodologies and their application to industrial robots

Abstract: In this paper, we present new computationally efficient and robust kinematic calibration algorithms for industrial robots that make use of partial measurements. These include a calibration method that requires the supply of Cartesian coordinates of the calibration points (3DCAL) and another calibration technique that only requires the radial measurements from the calibration points to some reference (1DCAL). Neither method requires orientation measurements nor the explicit knowledge of the whereabout of a reference frame. Contrary to most other similar works, both methods make use of a simplified version of the original Denavit-Hartenberg (DH) kinematic model. The simplified DH(-) model has not only proven to be robust and effective in calibrating industrial manipulators but it is also favored from a computational efficiency viewpoint since it consists of comparatively fewer error parameters. We present an analytical approach to develop a set of guidelines that need to be considered in order to properly construct the DH(-) model such that it is parameterically continuous and non-redundant. We also propose an automated method to provide a characterization of the error parameters that is insightful so as to correctly deduce the DH(-) error model of a manipulator. The method makes use of a novel hybrid optimization scheme to conduct a statistical analysis of the error parameters that is indicative of their relevance. We made note that, for the industrial robots used in this paper and similar ones, calibrating the home position only is sufficient to attain adequate results for most robotic applications. Hence, we put forward for consideration a yet simpler calibration model; the DH(-)(-) model. We employ the Trust Region (TR) method to minimize the objective functions of both frameworks (3DCAL and 1DCAL). The performance of the proposed methods is compared to that of a state-of-the-art commercial system (MotoCal) using the same materials, data and internationally recognized performance standards. Our experimental results suggest that our methods yield improved results compared to that of MotoCal. Graphical abstractDisplay Omitted HighlightsNovel calibration frameworks that make use of 1D and 3D pose information.Frameworks that are competitive with or outperform the state-of-the-art commercial tool.Methodologies to deduce non-redundant and computationally efficient error models.Novel hybrid optimization scheme that combines Simulated Annealing and Trust Region.

Impact & improvement of tool deviation in friction stir welding

Abstract: The present study proposes the use of an industrial serial robot to reduce the investment cost and to increase the process flexibility of Friction Stir Welding (FSW). The first part of the study characterizes the impact of pin axis position on FS Weld (FSWed) quality. The second part shows a method to compensate the lateral pin deviation in real-time during Robotic Friction Stir Welding (RFSW). This paper shows that a robot with an embedded real-time algorithm for the compensation of the lateral tool deviation can reproduce the same FSWed quality as a gantry-type CNC system. The elastostatic model of an industrial robot is carried out by the classical identification technique and this is embedded in the robot controller. Based on force measurements along the welding process, the corrected path is calculated in real-time. We use the compensation algorithm in order to do a lot of industrial project on real parts (confidential parts).The algorithm which is presented in the paper increase the precision of the robot.The algorithm which is presented could be used for other process like incremental sheet forming or deburring.

Towards a griddable distributed manufacturing system with augmented reality interfaces

Abstract: Rapidly changing demand and mass customization require highly flexible and adaptive manufacturing systems. Manufacturing operations have evolved in order to keep up by organizing themselves into smaller units of specialized production processes that are combined in different ways to create different products. Human workers are integral in the manufacturing systems and they too must be flexible and adaptive. This paper describes an augmented reality manufacturing system that aims to greatly improve the information perception of the different types of workers in a manufacturing facility and to make interaction with manufacturing software natural and efficient. In this approach, traditionally paper-based and computer-based tasks are augmented to the workers' interactions in the environment. The system is distributed and modular as the different functions of CAD/CAM software are provided by individual physical or virtual objects in the environment or by a combination of them working cooperatively. This modularity allows the individual resources and facilities to be linked via internet onto a manufacturing grid with universally-accessible augmented reality interfaces to their services. Framework for ubiquitous AR environments.Application of the framework to a local manufacturing environment.Application of the framework to manufacturing grid.

Development of a piezo-driven 3-DOF stage with T-shape flexible hinge mechanism

Abstract: This paper presents a 3-DOF (Degree of freedom) stage with T-shape flexible hinge mechanism for the applications in the precision measurement equipments and micro/nano manipulation systems. The stage is driven by three piezoelectric actuators (PEAs) and guided by a flexible hinge based mechanism with three symmetric T-shape hinges. The proposed T-shape flexible hinge mechanism can provide excellent planar motion capability with high stability, and thus guarantee the outstanding dynamics characteristics. The theoretical modeling of the stage was carried out and the stiffness and the dynamic resonance frequency have been obtained. The kinematic model of the 3-DOF stage was established and the workspace has been analyzed. The characteristics of the stage were investigated using finite element analysis (FEA). Experiments were conducted to examine the performance of the stage, through this stage, X-axis translational motion stroke of 6.9?m, Y-axis translational motion stroke of 8.5?m and rotational motion stroke along Z-axis of 289?rad can be achieved. A hybrid feedforward/feedback control methodology has been proposed to eliminate the nonlinear hysteresis, the trajectory tracking performances and to reduce external disturbance of the 3-DOF stage. The stage is driven by three piezoelectric actuators (PEAs) and guided by a flexible hinge based mechanism with three symmetric T-shape hinges. The T-shape flexure hinge is composed of three leaf-spring hinge subsections connected at the together like a T-joint. Thus, the T-shape flexure hinge can provide the in plane motion with relatively large out-of-plane stiffness. It is demonstrated from the computational analyses that the proposed T-shape flexure hinge can provide high natural frequency, large working range and high motion dexterity. The experiments results showed that the stage can provide for good performance.

Stiffness analysis of parallelogram-type parallel manipulators using a strain energy method

Abstract: Although stiffness analyses of specific parallelogram-type parallel manipulators (PTPMs) have been presented by several researchers, an algebraic expression is still needed to obtain the stiffness of a general PTPM. To address this issue, this paper uses a strain energy method considering the compliances of the mobile platform, the limb and the actuator of a PTPM. In this method, the deformation of the mobile platform, which has typically been ignored by many researchers, is integrated in the total deformation of the PTPM. After comparison with a FEA method, it is found that the proposed algebraic method is a comparable alternative to the FEA method to be used in the pre-design stage. Additionally, a new stiffness index is proposed to evaluate the stiffness property. Compared with other stiffness indices, the new index uses virtual work to unify the units of translation and orientation and relates the index value to the direction of the wrench experienced by a parallel manipulator in a task. With this index, the resistance of a PTPM to deformation under a given wrench can be measured easily. Stiffness analysis of a general PTPM using an algebraic method.Result comparison between the proposed method and a finite element analysis method.A new stiffness index relating the stiffness property to the wrench experienced in a task.

Manufacturing of composite parts reinforced through-thickness by tufting

Abstract: The paper aims at providing practical guidelines for the manufacture of composite parts reinforced by tufting. The need for through-thickness reinforcement of high performance carbon fibre composite structures is reviewed and various options are presented. The tufting process is described in detail and relevant aspects of the technology are analysed such as: equipment configuration and setup, latest advances in tooling, thread selection, preform supporting systems and choice of ancillary materials. Effects of the process parameters on the preform fibre architecture and on the meso-structure of the reinforced component are discussed. Special emphasis is given to the different options available in terms of tuft insertion and loops management.Potential fields of application of the technology are investigated as well as the limitations of its applicability in relation to preform nature and geometry. Critical issues which may arise during the manufacturing process concerning thread insertion, loops formation, alteration to the fabric fibres layout or local volume fraction are identified. Tufting, as a process to manufacture reinforced composite structures, is described.Relevant aspects of the tufting technology are presented and analysed.Critical issues which may arise during the tufting process are identified/addressed.The effect of process parameters on the meso-structure of the component is discussed.Current and potential fields of application of the technology are investigated.The limitations of the applicability of tufting are discussed.

An on-line shape-matching weld seam tracking system

Abstract: Automatic welding technology continues to find a broader application in diverse industries due to its high efficiency and accuracy. In this work, an on-line laser-based machine vision system for seam tracking was developed. To achieve a reliable and accurate seam tracking process that is adaptive to different groove types, a shape-matching algorithm was proposed and implemented. The algorithm uses the previous groove shape as the template to locate the next groove shape. Tests on U-groove, tap-groove and free form groove have verified its adaptability and robustness to different groove types with noise. The shape-matching algorithm also enables the seam tracking system to automatically localize the starting and finishing point of the weld seam. A FIFO based queue was defined and implemented to tackle the lag distance problem between the heat source and the vision sensor. The tracking algorithm, along with the FIFO queue was successfully verified on a sine-shaped seam. A tracking accuracy ofźź0.5mm was achieved in this test, which is acceptable in most of the arc welding applications. A seam tracking system with high adaptability to groove types was developed.The system is able to localize the starting/finishing point of the weld seam.A FIFO based queue was implemented to tackle the lag distance problem.The system was verified on a sine-shaped seam with an accuracy of ź0.5mm.

Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model

Abstract: Automatic multi-pass route planning is one of key technologies for thick plate in robotic metal active gas (MAG) arc welding. In this research, a scheme for the extracting feature points of the weld seam profile to implement automatic multi-pass route planning, and guidance of the initial welding position in each layer during MAG arc welding, is presented. It consists of two steps: first a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously within the same frame, and the laser stripe, forming the weld seam profile is detected by a visual attention model based on saliency. Then a methodology of polynomial fitting plus derivatives for feature point extraction of the weld seam profile is suggested. With respect to the effectiveness of highlighting the laser stripe, the proposed model is much better than the classic ones in this field, whereas the feature point extraction methodology in this paper outperforms typical template matching. Finally, the performance of the proposed scheme is demonstrated on different weld seam images captured in different layers and different welding experiments. New vision sensor captures laser stripes and molten pools simultaneously.A visual attention model for detecting weld seam profiles is proposed.Three kinds of feature points of weld seam profiles can be extracted.Different images captured in different layers validate the proposed methods.The extracted feature points can be used for multi-pass route planning.

Non-linear model predictive control schemes with application on a 2 link vertical robot manipulator

Abstract: The industrial requirements for controllers able to perform tasks in the presence of plant nonlinearities are growing. In addition, an increase in industrial computation power is allowing the implementation of more complex control algorithms in the fast processing industry. In this investigation three different nonlinear model predictive control algorithms are tested and evaluated in simulation and experimentally. The methodologies are adaptive nonlinear model predictive control (nMPC), PID based nMPC (PIDnMPC), and a novel simplified nMPC (SnMPC). These are tested in simulation with an inverted pendulum, a Van der Pol oscillator, and a planar 2-link vertical robotic arm. The controllers are tested experimentally using a fabricated planar 2-link vertical robotic arm apparatus. A comparison of the different algorithms is made with special attention to trajectory tracking, computational complexity and transient response dynamics. HighlightsThree non-linear MPC Algorithms are developed to control fast systems, nMPC, PIDnMPC and SnMPC.The algorithms are tested in simulation using three non-linear models.The controller features are discussed and future directions of study are suggested.

High-accuracy vehicle localization for autonomous warehousing

Abstract: The research presented in this paper aims to bridge the gap between the latest scientific advances in autonomous vehicle localization and the industrial state of the art in autonomous warehousing. Notwithstanding great scientific progress in the past decades, industrial autonomous warehousing systems still rely on external infrastructure for obtaining their precise location. This approach increases warehouse installation costs and decreases system reliability, as it is sensitive to measurement outliers and the external localization infrastructure can get dirty or damaged. Several approaches, well studied in scientific literature, are capable of determining vehicle position based only on information provided by on board sensors, most commonly wheel encoders and laser scanners. However, scientific results published to date either do not provide sufficient accuracy for industrial applications, or have not been extensively tested in realistic, industrial-like operating conditions. In this paper, we combine several well established algorithms into a high-precision localization pipeline, capable of computing the pose of an autonomous forklift to sub-centimeter precision. The algorithms use only odometry information from wheel encoders and range readings from an on board laser scanner. The effectiveness of the proposed solution is evaluated by an extensive experiment that lasted for several days, and was performed in a realistic industrial-like environment. HighlightsWe describe an algorithm stack for high-precision autonomous vehicle localization.Localization accuracy satisfies industrial requirements of 1.5cm and 0.5°.The proposed methodology has been verified by extensive experiments.Experiments were performed in realistic industrial conditions.

Real-virtual components interaction for assembly simulation and planning

Abstract: Assembly motion simulation is crucial during conceptual product design to identify potential assembly issues and enhance assembly efficiency. This paper presents a novel assembly simulation system incorporating real-virtual components interaction in an augmented-reality based environment. With this system, users can manipulate and assemble virtual components to real components during assembly simulation using natural gestures through an enhanced bare-hand interface. Accurate and realistic movements of virtual components can be obtained based on constraints analysis, determination of resultant forces from contacts with real components and manipulation from the user's hands (forces and torques applied, etc.) during assembly simulation. A prototype system has been developed, and a case study of an automobile clutch was conducted to validate the effectiveness and intuitiveness of the system. Enable real-virtual components interaction during augmented reality assembly.Facilitate intuitive manipulation of virtual components with bare-hand interface.An industrial case is conducted to validate the effectiveness of the system.

Real-time enhancement of tracking performances for cable-conduit mechanisms-driven flexible robots

Abstract: Natural Orifice Transluminal Endoscopic Surgery (NOTES) is a method that allows for performing complex operations via natural orifices without skin incisions. Its main tool is a flexible endoscope. Cable-conduit mechanism (CCM) or tendon-sheath Mechanism (TSM) is often used in NOTES because of its simplicity, safety in design, and easy transmission. Nonlinearities between the cable and the conduit pose challenges in the motion control of the NOTES system. It is very difficult to achieve the precise position of robotic arms when the system is inside a human's body. This paper presents new approaches to model and control a pair of CCMs (TSMs) used in NOTES system. To deal with the change of cable-conduit configurations during its operation, two control schemes are proposed: (i) an updated table with offline backlash hysteresis learning is constructed. In this case, a simple computation of the direct inverse backlash hysteresis model is introduced without using output feedback for compensation; and (ii) an online estimation of the backlash hysteresis profile under the assumption of availability of output feedback. In this case, adaptive control laws are used to deal with the change of the endoscope configuration. The proposed model and compensation control schemes are experimentally validated using a prototype of a single-DOF-Master-Slave system, which consists of a master console, a telesurgical workstation, and a slave manipulator. The results show that the proposed model and the control schemes improve the tracking performances of the system. Compensation control schemes for cable-conduit system are developed.Hysteresis model parameters are identified and optimized for feedforward.Compensation with feedforward scheme is used for control purpose.Compensation with nonlinear adaptive scheme is developed for control purpose.The proposed models and control structure are validated satisfactorily.

Two-dimensional placement optimization for multi-parts production in additive manufacturing

Abstract: Additive Manufacturing (AM) processes build parts in a layer by layer manner. This unique characteristic enables AM machines to fabricate different parts simultaneously without using tools or fixtures. However, how to optimally place multi-parts (with same or different geometries) into a specified build space or onto the build platform with respect to user-defined objectives is a complex NP-hard problem. This problem is a special variant of classical nesting or packing problems. Moreover it owns specific constraints from AM. In this paper, the multi-parts placement problem in AM is analyzed and an integrated strategy is proposed to solve one category of the problem, two-dimensional placement of multi-parts. The proposed strategy is composed of two main steps, Applying an "AM feature-based orientation optimization method" to optimize each part's build orientation to guarantee the production quality and Applying a designed "parallel nesting" algorithm for increasing the compactness of placement by using the parts' projection profiles so as to decrease the total build time and cost. Computational examples are presented in the end for demonstration. Multi-parts placement problem in AM is analyzed.An integrated strategy is proposed for the two-dimensional placement problem.High nesting compactness and production quality can both be guaranteed.Practical specific 2D nesting tools can be developed based on this strategy.

Investigation of part distortions as a result of hybrid manufacturing

Abstract: In today's society, the customer driven markets has led to the rapid developments and continuous evolution of manufacturing technologies. The ability to accurately produce complex parts, and to reuse and remanufacture used parts is becoming more prevalent, requiring more efficient and rapid methods to be developed. One such method being currently developed is the hybrid process combining additive, subtractive and inspection processes for the manufacture of complex part geometries from any given raw material in terms of shape and size. A major element of the hybrid process is decomposition of a part into a number of subparts, which are additively manufactured and machined in sequence. However, the residual stresses resulting from the temperature difference between the solidified material (i.e. already manufactured subparts) and the material being deposited (i.e. new subparts being built) leads to part distortions, which significantly reduces the dimensional accuracy of finished parts. This study investigates part distortions that take place in the additive manufacturing process under the context of hybrid manufacturing. A method for conducting this investigation was first proposed. A mathematical model was developed, identifying the influential parameters that contribute to part distortions. These parameters were then incorporated in the experimental design by employing the Taguchi design of experiments strategy. Distortion behaviour arising from thermally induced stress was experimentally explored, indicating that part length, height, and layer thickness have significant effects on part distortions. Investigating part distortion behaviour in a hybrid manufacturing process.The hybrid process consists of additive, subtractive and inspection techniques.Proposing an experimental approach to investigating part distortions.Developing a mathematical model to analyse influential factors in part distortions.Conducting experiments to identify the significance of hybrid process parameters.

Kinetostatic-model-based stiffness analysis of Exechon PKM

Abstract: As a comparative newly-invented PKM with over-constraints in kinematic chains, the Exechon has attracted extensive attention from the research society Different from the well-recognized kinematics analysis, the research on the stiffness characteristics of the Exechon still remains as a challenge due to the structural complexity In order to achieve a thorough understanding of the stiffness characteristics of the Exechon PKM, this paper proposed an analytical kinetostatic model by using the substructure synthesis technique The whole PKM system is decomposed into a moving platform subsystem, three limb subsystems and a fixed base subsystem, which are connected to each other sequentially through corresponding joints Each limb body is modeled as a spatial beam with a uniform cross-section constrained by two sets of lumped springs The equilibrium equation of each individual limb assemblage is derived through finite element formulation and combined with that of the moving platform derived with Newtonian method to construct the governing kinetostatic equations of the system after introducing the deformation compatibility conditions between the moving platform and the limbs By extracting the 6×6 block matrix from the inversion of the governing compliance matrix, the stiffness of the moving platform is formulated The computation for the stiffness of the Exechon PKM at a typical configuration as well as throughout the workspace is carried out in a quick manner with a piece-by-piece partition algorithm The numerical simulations reveal a strong position-dependency of the PKM's stiffness in that it is symmetric relative to a work plane due to structural features At the last stage, the effects of some design variables such as structural, dimensional and stiffness parameters on system rigidity are investigated with the purpose of providing useful information for the structural optimization and performance enhancement of the Exechon PKM It is worthy mentioning that the proposed methodology of stiffness modeling in this paper can also be applied to other overconstrained PKMs and can evaluate the global rigidity over workplace efficiently with minor revisions An kinetostatic model for Exechon is established with substructure synthesisThe compliances of all joints and limb bodies are considered in the modelThe stiffness matrix of moving platform is formulated conciselyThe stiffness distributions throughout the workspace are predicted efficientlyThe effects of variables on stiffness are studied to provide design guidances

Adaptive control algorithm of flexible robotic gripper by extreme learning machine

Abstract: Adaptive grippers should be able to detect and recognize grasping objects. To be able to do it control algorithm need to be established to control gripper tasks. Since the gripper movements are highly nonlinear systems it is desirable to avoid using of conventional control strategies for robotic manipulators. Instead of the conventional control strategies more advances algorithms can be used. In this study several soft computing methods are analyzed for robotic gripper applications. The gripper structure is fully compliant with embedded sensors. The sensors could be used for grasping shape detection. As soft computing methods, extreme learning machine (ELM) and support vector regression (SVR) were established. Also other soft computing methods are analyzed like fuzzy, neuro-fuzzy and artificial neural network approach. The results show the highest accuracy with ELM approach than other soft computing methods. Controlling input displacement of a new adaptive compliant gripper.This design of the gripper with embedded sensors as part of its structure.To build an effective prediction model of input displacement of gripper.The impact of the variation in the input parameters.