Showing papers in "Robotics and Computer-integrated Manufacturing in 2015"

A multi-bead overlapping model for robotic wire and arc additive manufacturing (WAAM)

Abstract: Wire and arc additive manufacturing (WAAM) is a promising alternative to traditional subtractive manufacturing for fabricating large aerospace components that feature high buy-to-fly ratio. Since the WAAM process builds up a part with complex geometry through the deposition of weld beads on a layer-by-layer basis, it is important to model the geometry of a single weld bead as well as the multi-bead overlapping process in order to achieve high surface quality and dimensional accuracy of the fabricated parts. This study firstly builds models for a single weld bead through various curve fitting methods. The experimental results show that both parabola and cosine functions accurately represent the bead profile. The overlapping principle is then detailed to model the geometry of multiple beads overlapping together. The tangent overlapping model (TOM) is established and the concept of the critical centre distance for stable multi-bead overlapping processes is presented. The proposed TOM is shown to provide a much better approximation to the experimental measurements when compared with the traditional flat-top overlapping model (FOM). This is critical in process planning to achieve better geometry accuracy and material efficiency in additive manufacturing. Single weld bead models are built through various curve fitting methods.A novel multi-bead overlapping model is established.The concept of the critical centre distance for stable multi-bead overlapping processes is presented.

A practical path planning methodology for wire and arc additive manufacturing of thin-walled structures

Abstract: This paper presents a novel methodology to generate deposition paths for wire and arc additive manufacturing (WAAM). The medial axis transformation (MAT), which represents the skeleton of a given geometry, is firstly extracted to understand the geometry. Then a deposition path that is based on the MAT is efficiently generated. The resulting MAT-based path is able to entirely fill any given cross-sectional geometry without gaps. With the variation of step-over distance, material efficiency alters accordingly for both solid and thin-walled structures. It is found that thin-walled structures are more sensitive to step-over distance in terms of material efficiency. The optimal step-over distance corresponding to the maximum material efficiency can be achieved for various geometries, allowing the optimization of the deposition parameters. Five case studies of complex models including solid and thin-walled structures are used to test the developed methodology. Experimental comparison between the proposed MAT-based path patterns and the traditional contour path patterns demonstrate significant improved performance in terms of gap-free cross-sections. The proposed path planning strategy is shown to be particularly beneficial for WAAM of thin-walled structures. A novel path planning methodology based on the Medial Axis Transformation (MAT) of the geometry is proposed.Gap-free paths can be obtained for any arbitrarily shaped geometry.Relationships between step-over distance and material efficiency are analysed.Optimal step-over distances for different Additive Manufacturing (AM) systems are discussed.The proposed path planning strategy is particularly useful for wire and arc additive manufacturing of thin-walled structures.

Stiffness-oriented posture optimization in robotic machining applications

Abstract: Industrial robots have been used in machining applications for their advantages such as their high flexibility and low cost. However, the relatively low stiffness of the robot can seriously affect its positioning accuracy and its machining quality. In this paper, a posture optimization method is presented, aiming at increasing the stiffness of the robot in machining applications. First, a performance index is proposed to evaluate the stiffness of the robot with a given posture after an in-depth study of the relationship between the translational displacement of the robot end effector and the force applied on it. The index is then demonstrated to be a frame invariant. By maximizing the index, a robot posture optimization model is further established and solved by a novel solution method based on the Jacobian matrix. Finally, experimental results achieved on a KUKA KR360-2 robot verify the correctness of the stiffness performance index, and the application of the posture optimization method in a robotic drilling system shows its effectiveness. We propose a performance index to evaluate the stiffness of a robot at a given posture.The performance index is demonstrated to be a frame invariant.We establish a robot posture optimization model by maximizing the performance index.The posture optimization model is solved by a novel method based on the Jacobian matrix.

Performance of state space and ARIMA models for consumer retail sales forecasting

Abstract: Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts. HighlightsWe compare the forecasting performance of state space models and ARIMA models.The forecasting performance is demonstrated through a case study of retail sales of women footwear.The model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample.The overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts.Both state space and ARIMA produce coverage probabilities that are very close to the nominal rates.

Geometric calibration of industrial robots using enhanced partial pose measurements and design of experiments

Abstract: The paper deals with geometric calibration of industrial robots and focuses on reduction of the measurement noise impact by means of proper selection of the manipulator configurations in calibration experiments. Particular attention is paid to the enhancement of measurement and optimization techniques employed in geometric parameter identification. The developed method implements a complete and irreducible geometric model for serial manipulator, which takes into account different sources of errors (link lengths, joint offsets, etc). In contrast to other works, a new industry-oriented performance measure is proposed for optimal measurement configuration selection that improves the existing techniques via using the direct measurement data only. This new approach is aimed at finding the calibration configurations that ensure the best robot positioning accuracy after geometric error compensation. Experimental study of heavy industrial robot KUKA KR-270 illustrates the benefits of the developed pose strategy technique and the corresponding accuracy improvement. Geometric calibration of industrial robotsReduction of the measurement noise impact by means of proper selection of the manipulator configurations in calibration experimentsA new industry-oriented performance measure for optimal measurement configuration selectionExperimental study of heavy industrial robot KUKA KR-270

Parameter identification for industrial robots with a fast and robust trajectory design approach

Abstract: Model-based, torque-level control can offer precision and speed advantages over velocity-level or position-level robot control. However, the dynamic parameters of the robot must be identified accurately. Several steps are involved in dynamic parameter identification, including modeling the system dynamics, joint position/torque data acquisition and filtering, experimental design, dynamic parameters estimation and validation. In this paper, we propose a novel, computationally efficient and intuitive optimality criterion to design the excitation trajectory for the robot to follow. Experiments are carried out for a 6 degree of freedom (DOF) Staubli TX-90 robot. We validate the dynamics parameters using torque prediction accuracy and compare to existing methods. The RMS errors of the prediction were small, and the computation time for the new, optimal objective function is an order of magnitude less than for existing approaches. HighlightsWe propose a fast, robust trajectory design for use in parameter identification.Computation time for our design is approximately 1/20 the time for prominent, existing methods.We estimate the dynamic parameters for a 6 DOF robot, the Staubli Tx-90, which has not previously been identified, to our knowledge.The RMS errors of the torque prediction were small (< 24 Nm).

Computer vision technology for seam tracking in robotic GTAW and GMAW

Abstract: Due to ever increasing demand in precision in robotic welding automation and its inherent technical difficulties, seam tracking has become the research hotspot. This paper introduces the research in application of computer vision technology for real-time seam tracking in robotic gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW). The key aspect in using vision techniques to track welding seams is to acquire clear real-time weld images and to process them accurately. This is directly related to the precision of seam tracking. In order to further improve the accuracy of seam tracking, in this paper, a set of special vision system has been designed firstly, which can acquire clear and steady real-time weld images. By analyzing the features of weld images, a new and improved edge detection algorithm was proposed to detect the edges in weld images, and more accurately extract the seam and pool characteristic parameters. The image processing precision was verified through the experiments. Results showed that the precision of this vision based tracking technology can be controlled to be within ?0.17mm and ?0.3mm in robotic GTAW and GMAW, respectively. Using computer vision technology, we have solved some problems of seam tracking in robotic welding automation.We have designed a set of special vision sensor system for seam tracking and it has worked very well.A new improved Canny edge detection algorithm was proposed to detect the edges of weld image.We have further improved the precision of image processing in seam tracking.This paper systematically studied the application of computer vision technology in robotic GTAW and GMAW.

Knowledge-based instruction of manipulation tasks for industrial robotics

Abstract: When robots are working in dynamic environments, close to humans lacking extensive knowledge of robotics, there is a strong need to simplify the user interaction and make the system execute as autonomously as possible, as long as it is feasible. For industrial robots working side-by-side with humans in manufacturing industry, AI systems are necessary to lower the demand on programming time and system integration expertise. Only by building a system with appropriate knowledge and reasoning services can one simplify the robot programming sufficiently to meet those demands while still getting a robust and efficient task execution.In this paper, we present a system we have realized that aims at fulfilling the above demands. The paper focuses on the knowledge put into ontologies created for robotic devices and manufacturing tasks, and presents examples of AI-related services that use the semantic descriptions of skills to help users instruct the robot adequately. HighlightsWe present a system for knowledge-based task specification in assembly.Robotic skills are described in ontologies and used as building blocks for task specification and synthesis.Robotic skills are declarative, compositional, and reusable.An architecture to maintain and use industrial robotics knowledge is provided.

Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

Abstract: A 3-DOF (X-Y-?Z) planar flexure-based mechanism is designed and monolithically manufactured using Wire Electro-Discharge Machining (WEDM) technology. The compact flexure-based mechanism is directly driven by three piezoelectric actuators (PZTs) through decoupling mechanisms. The orthogonal configuration in the x and y directions can guarantee the decoupling translational motion in these axes. The rotational motion and translational displacement in the x direction can be decoupled by controlling the piezoelectric actuators in the x axis with the same displacement values in same and opposite motion directions, respectively. The static and dynamic models of the developed flexure-based mechanism have been developed based on the pseudo-rigid-body model methodology. The mechanical design optimization is conducted to improve the static and dynamic characteristics of the flexure-based mechanism. Finite Element Analyses (FEA) are also carried out to verify the established models and optimization results. A novel hybrid feedforward/feedback controller has been provided to eliminate/reduce the nonlinear hysteresis and external disturbance of the flexure-based mechanism. Experimental testing has been performed to examine the dynamic performance of the developed flexure-based mechanism. The mechanical design methodology for a compact 3-DOF planar flexure-based mechanism has been developed.Influences of the Hertzian contact stiffness on the dynamic performance of the developed mechanism have been explored.A novel hybrid feedforward/feedback controller has been proposed to reduce/eliminate the hysteresis.

Localization, obstacle avoidance planning and control of a cooperative cable parallel robot for multiple mobile cranes

Abstract: This paper addresses the cooperative problems in terms of localization, obstacle avoidance planning and automatic leveling control for a cable parallel robot for multiple mobile cranes (CPRMCs). The design model of the CPRMCs is elaborated on. The three-dimensional grid map method is utilized to plot the environment map based on the operation environment model. By combining the relative localization method with the absolute localization method, a cooperative localization scheme of the CPRMCs is developed, and an improved localization algorithm is designed on the basis of multilateration method. Then, according to the grid-based artificial potential field method, a global path planning of the CPRMCs is performed. Considering the possible collision of the single mobile crane, the sensor technology is applied to the cooperative obstacle avoidance. In addition, a four-point collaborative leveling method is adopted for automatic leveling control of the platform of the CPRMCs. Finally, the effectiveness of the CPRMCs system is verified through simulations. Cable parallel robots for multiple mobile cranes are designed.Localization analysis of the robots are reported.Obstacle avoidance planning and automatic leveling control are performed.Illustrative simulation studies highlight the performance of the robots.

Customer segmentation in a large database of an online customized fashion business

Abstract: Data mining (DM) techniques have been used to solve marketing and manufacturing problems in the fashion industry. These approaches are expected to be particularly important for highly customized industries because the diversity of products sold makes it harder to find clear patterns of customer preferences. The goal of this project was to investigate two different data mining approaches for customer segmentation: clustering and subgroup discovery. The models obtained produced six market segments and 49 rules that allowed a better understanding of customer preferences in a highly customized fashion manufacturer/e-tailor. The scope and limitations of these clustering DM techniques will lead to further methodological refinements. We investigate customer segmentation in highly customized fashion industries.Two data mining methods are used, clustering and subgroup discovery.The segments obtained enabled a better understanding of customer preferences.Different approaches provide complementary perspectives.Lines for further methodological refinements were identified.

Feedforward nonlinear PID control of a novel micromanipulator using Preisach hysteresis compensator

Abstract: Recently, flexure-based micromanipulators with a large workspace, high motion precision, and high positioning bandwidth are really attractive for performing practical micro/nano manipulation tasks. Thus, a piezo-actuated flexible two-degrees-of-freedom (2-DOF) micromanipulator integrated with a pair of modified differential lever displacement amplifiers (MDLDA) is developed. To enhance the practical positioning performance of the micromanipulator, a novel feedforward nonlinear Proportion-Integration-Differentiation (FNPID) control strategy combining a nonlinear PID controller with an inverted hysteresis compensator is first proposed and implemented in detail. With the consideration of hysteresis effect inherent in piezoelectric ceramics (PZT) actuators, the hysteresis nonlinearity modeling is conducted by using the Preisach theory. Finally, a series of precision motion trajectory tracking experiments are successfully conducted by using the proposed closed-loop control strategy. The experimental results indicate that the mechanism has achieved a satisfactory performance for performing robotic biomanipulations. HighlightsA novel FNPID controller for the improvement of the practical working frequency of the flexure-based nanopositioning system is proposed.A new concept named "area efficiency" is proposed to make a quantitative evaluation for the designed nanomanipulator.Preisach method is adopted to model and compensate the complicated hysteresis nonlinearity.A series of trajectory tracking experiments are conducted to make comparisons between the proposed FNPID and PID controller.

A complete CAD/CAM/CNC solution for STEP-compliant manufacturing

Abstract: STEP-NC or ISO 14649 is the next generation of data models between CAD/CAM and CNC systems. After a decade of investigation, the STEP-NC technology is still under developed. The lack of a complete CAD/CAM/CNC prototype system with full bidirectional data flow hinders the improvement of STEP-NC. This paper proposes a complete CAD/CAM/CNC solution for STEP-compliant manufacturing, so as to explore the functionalities and emphases of STEP-NC technologies. Frameworks of individual CAD/CAM and CNC systems are illustrated in detail. Architectures of STEP-compliant CAD/CAM and CNC systems are studied and several criteria are summarized. Finally, this paper proposes a complete prototype STEP-compliant solution, which consists of a secondary developed STEP-compliant CAD/CAM system on the CATIA platform and an open structured STEP-compliant CNC system. HighlightsThe architectures and frameworks of STEP-compliant CAD/CAM/CNC systems are discussed and summarized.Some practical technical routes for STEP-NC implementation and realization are discussed.A STEP-compliant CAD/CAM prototyping system on the CATIA platform is developed.A STEP-CNC prototyping system which accepts STEP-NC code as input is developed to realize the real STEP-NC capability.A virtual manufacturing system is developed to verify the STEP-NC technologies.

Design, programming and orchestration of heterogeneous manufacturing systems through VR-powered remote collaboration

Abstract: Modern manufacturing systems are often composed of a variety of highly customized units and specifically designed manufacturing cells. Optimization of assembly and training of staff requires a series of demo installations and excessive use of costly operational resources. In some cases, components are located at different sites, making the orchestration of the whole system even more difficult.Virtual Reality (VR) collaboration environments offer a solution by enabling high fidelity testing and training of complex manufacturing systems. On the other hand, such platforms are difficult to implement in an engineering perspective, as they are required to provide reliable, standard interfaces towards both robotic components and human operators.The VirCA (Virtual Collaboration Arena) platform is a software framework that supports various means of collaboration through the use of 3D augmented/virtual reality as a communication medium. VirCA offers functions for the high-level interoperability of heterogeneous components in a wide range of domains, spanning from research & development, through remote education to orchestration and management of industrial processes in manufacturing applications. This paper provides an overview of the industrial requirements behind high-fidelity virtual collaboration and demonstrates how the VirCA platform meets these requirements. Use cases are provided to illustrate the usability of the platform. HighlightsThe paper identifies the synergies of recent advances in Future Internet and ICT.Surveys the need of high-fidelity virtual collaboration for industrial robotics.Introduces the VirCA platform as a remote collaboration and orchestration framework.Shows the integration of ontologies and CogInfoCom methods into industrial setups.Presents use case examples of knowledge-driven automation scenarios based on VirCA.

Extensions to the core ontology for robotics and automation

Abstract: The working group Ontologies for Robotics and Automation, sponsored by the IEEE Robotics & Automation Society, recently proposed a Core Ontology for Robotics and Automation (CORA). This ontology was developed to provide an unambiguous definition of core notions of robotics and related topics. It is based on SUMO, a top-level ontology of general concepts, and on ISO 8373:2012 standard, developed by the ISO/TC184/SC2 Working Group, which defines-in natural language-important terms in the domain of Robotics and Automation (R&A). In this paper, we introduce a set of ontologies that complement CORA with notions such as industrial design and positioning. We also introduce updates to CORA in order to provide more ontologically sound representations of autonomy and of robot parts. HighlightsWe discuss extensions to a core ontology for the robotics and automation field.The ontology aims to specify the main notions across robotics subdomains.We define robot, robotic system, robotic environment, and related notions.We discuss concepts regarding the notion of design, in industrial contexts.We discuss notions regarding the modes of operation of a robot.We discuss notions regarding the position, orientation and pose of a robot.

On generating the motion of industrial robot manipulators

Abstract: In this study, an intelligent search algorithm is proposed to define the path that leads to the desired position and orientation of an industrial robot's manipulator end effector. The search algorithm gradually approaches the desired configuration by selecting and evaluating a number of alternative robot's configurations. A grid of the robot's alternative configurations is constructed using a set of parameters which are reducing the search space to minimize the computational time. In the evaluation of the alternatives, multiple criteria are used in order for the different requirements to be fulfilled. The alternative configurations are generated with emphasis being given to the robot's joints that mainly affect the position of the end effector. Grid resolution and size parameters are set on the basis of the desired output. High resolution is used for a smooth path and lower for a rough estimation, by providing only a number of the intermediate points to the goal position. The path derived is a series of robot configurations. This method provides an inexperienced robot programmer with flexibility to generate automatically a robotic path that would fulfill the desired criteria without having to record intermediate points to the goal position. Intelligent, grid based search algorithm for generating motion of industrial robot manipulators.The robot path is produced as the result of combining the joints values. The large search space is reduced by applying a set of parameters.The alternative configurations of the robot are generated giving emphasis to the robot's joints that mainly affect the desired target.Multiple-criteria are taken into account for evaluating the generated robot path towards the desired position and orientation.

A multi-agent architecture for outsourcing SMEs manufacturing supply chain

Abstract: In the present, global and competitive market customer's demands are very volatile. It is very difficult for small and medium size enterprises (SMEs) to satisfy their customer with quality product in reasonable price. Large firms are spending huge amount of their budget in generating technology development. To cope with this competitive market, usually, SMEs concentrate on their core expertise and outsource some non-core items or activities. The outsourcing decision (when, what, whom) is very crucial for small-scale industries. Realizing this scenario, in this article, an automated self-adaptive multi-agent system has been proposed. The proposed system will help SMEs to take an appropriate decision to mitigate the uncertainty in supply chain. The developed system exploits the "Outsourcing of operations" feature by its agents to conclude the manufacturing processes faster and reduce the idle time of certain machines with less human intervention. The communication protocol for agents has been described to give an insight of their communication. It was explained how various agents like outsourcing, material planning and supplier selection will come into action at different stages and take appropriate outsourcing decisions. Therefore, this multi-agent architecture will facilitate small scale manufacturing industries to execute their manufacturing processes and complex logistics issues efficiently. The execution of proposed architecture has been described in the simulated case study. In this article an automated self-adaptive multi-agent system has been proposed.The system can help to mitigate the uncertainty in SMEs' supply chains.The system reduces the idle time of certain machines with less human intervention.It facilitates SMEs to execute their manufacturing process and complex logistics issues efficiently.

Learning and revision in cognitive robotics disassembly automation

Abstract: Disassembly is a key step for an efficient treatment of end-of-life (EOL) products. A principle of cognitive robotics is implemented to address the problem regarding uncertainties and variations in the automatic disassembly process. In this article, advanced behaviour control based on two cognitive abilities, namely learning and revision, are proposed. The knowledge related to the disassembly process of a particular model of product is learned by the cognitive robotic agent (CRA) and will be implemented when the same model has been seen again. This knowledge is able to be used as a disassembly sequence plan (DSP) and disassembly process plan (DPP). The agent autonomously learns by reasoning throughout the process. In case of an unresolved condition, human assistance is given and the corresponding knowledge will be learned by demonstration. The process can be performed more efficiently by applying a revision strategy that optimises the operation plans. As a result, the performance of the process regarding time and level of autonomy are improved. The validation was done on various models of a case-study product, Liquid Crystal Display (LCD) screen. Actual implication of the learning and revision strategy in cognitive robotic disassembly operation.Improvement of the process performance using learning and revision strategy.Disassembly sequence and process plans can be automatically generated by the CRA during the disassembly.

Energy efficiency benchmarking for injection moulding processes

Abstract: Energy and resource efficiency is becoming an important strategy in manufacturing. In the automotive industry, the assessment of the environmental impact of a product in use-phase is common practice. In contrast, the manufacturing phase often lacks detailed data; potential for improvement gets lost. Analysis and comparative evaluation of how the production factor energy is used in manufacturing can be an impulse for parallel improvements regarding energy, material and process time efficiency. The paper presents a systematic approach to energy efficiency benchmarking in injection moulding, specifically addressing the impact of the mould. A knowledge base serves as a baseline for the process of data collection and evaluation. Additionally, energy efficiency benchmarking of single processes give insight into the effectiveness of improvement measures and allow to identify best practice process and product designs. The concept can be extended to predict energy consumption of production plants. An energy label for moulds is introduced. A method to forecast the energy consumption of injection moulding processes is developed and validated via energy measurements.Furthermore, a method for an energy controlling of entire injection moulding cost centres is presented.Examples are shown how to use the methods to identify process weaknesses and select suitable energy efficiency measures.Verification and validation of the methods is based on real data from an industrial injection moulding plant for automotive parts.For the first time an energy label concept for injection moulds is introduced.

Online robot calibration based on hybrid sensors using Kalman Filters

Abstract: This paper presents an online robot self-calibration method based on an inertial measurement unit (IMU) and a position sensor. In this method, a position marker and an IMU are required to rigidly attach to the robot tool, which makes it possible to obtain the position of the manipulator from the position sensor and the orientation from the IMU in real time. An efficient approach which incorporates Kalman Filters (KFs) to estimate the position and the orientation of the manipulator is proposed in this paper. Using these pose (orientation and position) estimation methods will result in improving the reliability and accuracy of pose measurements. Finally, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Compared with the existing self-calibration methods, the greatest advantage of this method is that it does not need any complex steps, such as camera calibration, corner detection and laser tracking, which makes the proposed robot calibration procedure more autonomy in a dynamic manufacturing environment. What's more, reduction in complex steps leads to improving the accuracy of calibration. Experimental studies on a GOOGOL GRB3016 robot show that this proposed method has better accuracy, convenience and effectiveness. ?We propose a online robot calibration method, which only requires hybrid sensors to measure the position and the orientation.?An efficient approach which incorporates Kalman Filters (KFs) to estimate the position and the orientation of the manipulator.?The proposed approach is particularly suitable for the unknown environments, such as deep sea or outer space.

Time scheduling and optimization of industrial robotized tasks based on genetic algorithms

Abstract: Today's industrial manipulators are more and more demanding in terms of productivity. This goal could be achieved by increasing speed of the robot manipulator and/or by optimizing the trajectories followed by manipulators while performing manufacturing, assembling, welding or similar tasks. Focusing on the second aspect, this research proposes a method based on genetic algorithms by exploiting CAD (computer aided design) capabilities to optimize and simulate cycle time in performing classical manufacturing tasks. The goal is to determine the shortest distance traveled by the robot manipulator in the coordinate space for every pair of successive points. In addition, our optimization procedure considers supplementary factors such as inverse kinematic model (IKM) and relative position/orientation of the manipulator w.r.t task points. All these factors were statistically assessed to determine both individual and cross influences in finding the optimal solution. The proposed approach has been validated on a real life setup, involving a 6-DOFs (degrees of freedom) industrial robot manipulator when performing a spot welding task on a car body. The obtained results are promising and show the effectiveness of the proposed strategy. HighlightsThis paper proposes a strategy for planning and scheduling of the industrial robotic manipulators.The multi-objective optimization strategy is based on Genetic Algorithms (GAs).A statistical study to investigate influence of various factors on optimization is detailed.The proposed strategy is validated by considering an industrial task of spot welding on a car body.The obtained results are promising and show the efficacy of the proposed strategy.

Towards robust assembly with knowledge representation for the planning domain definition language (PDDL)

Abstract: The effort described in this paper attempts to integrate agility aspects in the "Agility Performance of Robotic Systems" (APRS) project, developed at the National Institute of Standards and Technology (NIST). The new technical idea for the APRS project is to develop the measurement science in the form of an integrated agility framework enabling manufacturers to assess and assure the agility performance of their robot systems. This framework includes robot agility performance metrics, information models, test methods, and protocols. This paper presents models for the Planning Domain Definition Language (PDDL), used within the APRS project. PDDL is an attempt to standardize Artificial Intelligence planning languages. The described models have been fully defined in the XML Schema Definition Language (XSDL) and in the Web Ontology Language (OWL) for kit building applications. Kit building or kitting is a process that brings parts that will be used in assembly operations together in a kit and then moves the kit to the area where the parts are used in the final assembly. Furthermore, the paper discusses a tool that is capable of automatically and dynamically generating PDDL files from the models in order to generate a plan or to replan from scratch. Finally, the ability of the tool to update a PDDL problem file from a relational database for replanning to recover from failures is presented. HighlightsModels for PDDL structure.Tool for automatic and dynamic generation of PDDL files.Tool for update of PDDL problem file from a dynamic relational database.Knowledge methodology/model allows agility, flexibility, and rapid re-tasking during failures.

Nonparametric statistical learning control of robot manipulators for trajectory or contour tracking

Abstract: This paper presents a method of precision tracking control for industrial robot manipulators. For robotic laser and plasma cutting tasks, the required tracking performance is much more demanding than that for material handling, spot welding, and machine tending tasks. Challenges in control come from the nonlinear coupled multi-body dynamics of robot manipulators, as well as the transmission error in the geared joints. The proposed method features data-driven iterative compensation of torque and motor reference. Motor side tracking and transmission error are handled by separate learning modules in a two-part compensation structure. Depending on the specific setup of end-effector sensing, the method can utilize either timed trajectory measurement or untimed two-dimensional contour inspection. Nonparametric statistical learning is used for the compensation. Considerations on incorporating analytical models and selecting data subsets for more efficient learning are discussed. The method is validated using a six-axis industrial robot. HighlightsA control method of robot manipulators for precision trajectory or contour tracking is presented.Nonparametric statistical learning is used for data-driven compensation of both torque and motor reference.A two-part compensation structure is adopted to handle motor side tracking and transmission error.The compensation can be done using either timed trajectory measurement or untimed contour inspection.

Dynamic modeling and redundant force optimization of a 2-DOF parallel kinematic machine with kinematic redundancy

Abstract: High precision is still one of the challenges when parallel kinematic machines are applied to advanced equipment. In this paper, a novel planar 2-DOF parallel kinematic machine with kinematic redundancy is proposed and a method for redundant force optimization is presented to improve the precision of the machine. The inverse kinematics is derived, and the dynamic model is modeled with the Newton–Euler method. The deformations of the kinematic chains are calculated and their relationship with kinematic error of the machine is established. Then the size and direction of the redundant force acting on the platform are optimized to minimize the position error of the machine. The dynamic performance of the kinematically redundant machine is simulated and compared with its two corresponding counterparts, one is redundantly actuated and the other is non-redundant. The proposed kinematically redundant machine possesses the highest position precision during the motion process and is applied to develop a precision planar mobile platform as an application example. The method is general and suitable for the dynamic modeling and redundant force optimization of other redundant parallel kinematic machines.

Inverse dynamics and control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator

Abstract: This paper addresses the inverse dynamics of three degrees of freedom (DOF) U-shaped planar parallel manipulator having three legs consisting of prismatic-prismatic-revolute (PPR) joint arrangement in which each leg has one active prismatic joint. This paper also proposes a proportional-derivative (PD) like adaptive sliding mode control combined with a disturbance observer for the motion control of the proposed manipulator. Using this control scheme, the controlled robotic manipulator is transformed into decoupled dynamics, and thus the motion performance is very convenient to quantify. Based on Lyapunov like argument the global asymptotic stability of the proposed closed loop system is proved. Real time experiments performed on the in-house fabricated prototype of the proposed manipulator are provided to substantiate the effectiveness and the improved performance of the proposed controller. The proposed controller performances are also compared with traditional controllers such as proportional integral derivative (PID) controller, sliding mode controller (SMC) and computed torque controller (CTC) Inverse dynamics of a 3-DOF planar parallel robot (3-PPR) is presented.A robust tracking controller with disturbance compensation has been introduced.Effectiveness of the controller has been demonstrated with prototype experiments.A comparative study of the proposed and existing controllers has been performed.

A framework for optimising product performance through feedback and reuse of in-service experience

Abstract: Optimising performance of complex engineering artefacts, which are typically designed to have a useful life of several decades, becomes very difficult during in-service if lessons learnt are not used properly. The authors argue that performance of long-lived complex artefacts can be improved if adequate product in-service data is fed back to the early stages of the product life cycle. This paper discusses an inclusive life cycle approach to optimising product performance by using knowledge and experience gained during in-service. The problem is presented alongside a review of literature of relevant subject areas. A framework for in-service knowledge management is then presented and operationalised through an industrial case study. The framework is developed from the point of view of an integrated product and service provider. The findings from the case study demonstrate how in-service knowledge can be captured, fed back and reused for the design and manufacture stages of the product lifecycle. This enables designers to learn from in-service product performance by informing subsequent designs with in-service knowledge, and consequently improving the through-life product performance. Development of a framework for knowledge management and in-service data feedback to product development.Demonstrating how field data is captured, fed back and reused for product development.The shift of OEM product development paradigms from traditional linear steps to more integrated product and service business models was discussed.The key in-service information OEMs require from in-service for new product development were identified.

Calculation of the robot trajectory for the optimum directional orientation of fibre placement in the manufacture of composite profile frames

Abstract: This article deals with theissue of calculating the trajectory of the end-effector of an industrial robot in the manufacture of composites. In the introduction to the article we describe the basic approaches used in the manufacture of composites. Robots are used to define the winding orientation of carbon fibre strands on an uneven polyurethane 3D core. The core is attached to the robot-end-effector and is led through a fibre-processing head according to a suitably defined robot trajectory during dry carbon fibre winding on the core. The model of a passage of the polyurethane core through a fibre-processing head is described in the article. The placement of the fibre-processing head is defined in the basic Euclidean coordinate system E3 of the robot. The core is specified in the local coordinates of the Euclidean coordinate system E3, the origin of this local system is in the robot-end-effector. The positioning of the local system in the basic system of the robot is entered using the "tool centre point" of the robot. A matrix calculus is used when calculating the trajectory robot-end-effector to determine the desired passage of the core through the fibre-processing head. Gradually, the required rotation and translation matrices of the local coordinate system of the robot-end-effector relative to the basic system are calculated and subsequently the Euler angles of rotation are determined corresponding to the transformation matrices. This is used to determine the sequence of values of the "tool centre point" for defining the desired trajectory of the robot-end-effector. The calculation for the trajectory was programmed in the Delphi development environment. The article also solves practical tasks of the polyurethane core passage through the fibre-processing head. The calculations of the trajectory of the robot-end-effector were used as input values for the graphic software simulator and at the same time winding of carbon strands on the polyurethane core was verified for the calculated trajectory of the robot-end-effector in the experimental laboratory. The described algorithm allows us to calculate and determine the accurate 3D trajectory of the end-effector of an industrial robot during the manufacture of composite profiles using a dry fibre winding technology on a polyurethane core with a circular cross-section.The algorithm can be applied to any manufacturing process where it is necessary to determine the 3D trajectory of a robot end-effector.Suppliers of industrial robots currently offer specific software tools facilitating control of the robot end-effector when programming specific tasks (machining, welding, cutting, grinding or painting) but none of them are suitable for use for the described task.In engineering and manufacturing practice, there are specific activities that require the determination of an industrial robot trajectory but it often occurs that a suitable commercial software product does not exist or is not available for the technician.The algorithm allows us to determine the exact trajectory of the robot end-effector, which provides a significant advantage over manually entered robot trajectory. It requires practical experience of technician and this technique is time-consuming.Use of the described algorithm is completely independent of the type of production robot and software tools.Possibility to accurately determine the desired trajectory of the robot end-effector using the algorithm can be beneficial for optimizing the robot trajectory in the production cycle.The procedure for determining the trajectory of the robot end-effector is at virtually no additional cost to the manufacturer and can significantly speed up the determination of the desired trajectory of the end-effector.The described algorithm in article can be successfully utilized by the technicians of manufacturing robotic workplaces and also by developers of specific software tools for controlling of manufacture robots.

Analysis of dynamic thermal characteristic of register of roll-to-roll multi-layer printing systems

Abstract: Register control is essential in the roll-to-roll printing of organic thin-film transistors. Specifically, microscale accuracy is required in the control of the overlay printing register. To achieve such precise control, the characteristics of the substrate under the operating conditions, such as the drying temperature and the tension applied to the substrate, should be considered. In this study, the variations of the elastic modulus and thermal deformation with the drying temperature were investigated, and the correlations among the change in the thermal characteristic of the substrate, the tension, and register error were also analyzed. The results of the analyses showed that the thermal deformation produced by the temperature change generated tension and register error, with the effect increasing with increasing drying temperature. System identification techniques were further used to develop a register model for estimating the register error due to thermal and elastic strains. The maximum estimation ability of 86.27% of the developed model is higher than that of a conventional register model. Display Omitted The thermal characteristics of register were studied in roll-to-roll printing process.Elastic modulus and CTE of plastic substrate were changed by drying temperature.Thermal strain of substrate by temperature fluctuations is dominant in register error.A model was developed to estimate the register error generated by thermal deformations.The developed model has superior performance than the conventional register model.

Simulation based iterative post-optimization of paths of robot guided thermal spraying

Abstract: Robot-based thermal spraying is a production process in which an industrial robot guides a spray gun along a path in order to spray molten material onto a workpiece surface to form a coating of desired thickness This paper is concerned with optimizing a given path of this sort by post-processing Reasons for doing so are to reduce the thickness error caused by a not sufficiently precise design of the given path, to adapt the path to a changed spray gun or spray technology, to adapt the path to slight incremental changes of the workpiece geometry, or to smooth the path in order to improve its execution by the robot An approach to post-optimization using the nonlinear conjugate gradient method is presented which employs a high-quality GPGPU-based simulation of the spray process for the evaluation of the coating thickness error and additionally taking care of the kinematic path quality The number of computationally time-consuming calls of the simulation is kept low by analytically calculating estimates of gradients from a simplified material deposition model A rigorous experimental evaluation on case studies of the mentioned applications shows that the method efficiently delivers improved paths which reduce the coating error on real free form surfaces considerably, ie the squared coating error is below 35% of the original value in every case study

Realtime performance analysis of different combinations of fuzzy-PID and bias controllers for a two degree of freedom electrohydraulic parallel manipulator

Abstract: A two degree of freedom (2 DOF) parallel manipulator in the form of an electrohydraulic motion simulator platform is developed. Pose (heave and pitch) of the platform is achieved by means of two double acting single rod industrial grade hydraulic cylinders. The cylinders are actuated by low cost proportional valves having 15% deadband and 15Hz natural frequency. The heave motion and the combination of heave and pitch motion of the platform are controlled by a real time controller. Different types of controller, namely proportional integral derivative (PID), hybrid fuzzy-PID, self-tuning fuzzy-PID and self-tuning fuzzy-PID with bias are designed. The real time control performances of the controllers are studied for step and sinusoidal demands of the piston. In order to achieve the required performance of the controller, suitable values for the control parameters are tuned for each controller. It is found that the self-tuning fuzzy-PID with bias controller shows the best control response compared to other controllers for control of the heave, pitch and combined heave and pitch motion. Development of a 2 DOF electrohydraulic motion simulator as a parallel manipulator.Control of heave, pitch and combined heave and pitch motion of the parallel manipulator.Design of PID, fuzzy-PID, self-tuning fuzzy-PID and self-tuning fuzzy-PID with bias controllers.Use of different combinations of fuzzy-PID and bias controllers for study of real time control performance.Best control response found for the self-tuning fuzzy-PID with bias controller.