Functional and Constructive Optimization of a Serial-Modular Industrial Robot Implemented within a Single Purpose Flexible Manufacturing Cell

Industrial serial robots can be classified according to several criteria, the most important being: the number of mobility degrees or independent movements, the number of independent kinematic axes, the shape of the workspace, the value of the useful load, the precision of touching a predetermined point, etc. Among these criteria, the number of degrees of mobility directly determines the structure of the kinematic chain corresponding to the robot and implicitly its construction, functionality and utility. In this paper, we define the three classes of industrial serial robots according to the degree of mobility: the class of industrial serial robots of minimum configuration, the class of redundant industrial serial robots and the class of hyper-redundant industrial serial robots. For each class of industrial serial robots the structural synthesis method is presented and representative examples of structures are given.

The possibilities of efficiency increse of working positions (WP) servicing by industrial robots (IR) in mechano-assembly Flexible Manufacturing Systems (FMS) by the workparts intermediate storage places (ISP) usage in Flexible Manufacturing Cells (FMC) are considered. The possible variants of WP service strategies in FMC with one-placed ISP usage are considered, the formal description of service strategies are given. The possible variant of classification of the WP service strategies by IR is proposed. The actuality of computer-aided search of optimal equipment service strategies in conditions of their multivariaty is determined.

PurposeThe purpose of this paper is to investigate the use of a laser tracker, a laser interferometer system and a telescopic ballbar for assessing the positioning performance of a six‐axis industrial serial robot. The paper also aims to illustrate the limitations of these three metrology instruments for the assessment of robot positioning performance and to demonstrate the inadequacy of simplistic performance tests.Design/methodology/approachSpecific test methods in the case of the laser interferometer system and the telescopic ballbar are proposed. Measurements are analyzed in accordance to the ISO 9283 norm.FindingsIt is found that, in static conditions and after a relatively short warm‐up, the unidirectional position repeatability of the non‐calibrated industrial robot under study (an ABB IRB 1600) is better than 37 μm, the unidirectional orientation repeatability is at worst 87 μrad, the linear position accuracy is better than 650 μm, and the rotation accuracy is at worst 2.8 mrad (mainly because of the sixth robot axis). It was also found that the dynamic (radial) errors due to vibrations can be up to approximately ±250 μm along a small circular path at TCP speed of 700 mm/s.Practical implicationsIt is pointed out that the use of a laser tracker (or any other large range portable 3D measurement system) is questionable for assessing – let alone analyzing in depth – the unidirectional position repeatability of some of today's industrial robots. It is also demonstrated that the laser interferometer system can be used for measuring linear errors along a linear path of motion as well as angular errors about axes orthogonal to the path of motion. Finally, it is shown that the telescopic ballbar is an excellent, comparably low‐cost, high‐precision tool for assessing the static and dynamic positioning performance of industrial robots and its use in robotics should be further developed.Originality/valueThis work is the first to detail the use of three metrology equipments for assessing the positioning performance of an industrial robot. Experimental results are presented and discussed. Some guidelines for optimizing the positioning performance of an industrial robot are provided.

SUMMARY The grouping of parts into families and machines into cells poses an important problem in the design and planning of the flexible manufacturing cells (FMC). This paper presents a new method of forming flexible manufacturing cells, based on branching from seed machine and bounding on a completed part. This method creates a number of alternative solutions based on the presence of a seed part which will enhance the flexibility of the manufacturing cells’ design, and which provides an opportunity to evaluate different options and to select the one which is the most cost effective.

PurposeThe purpose of this paper is to establish a model‐based framework allowing the simulation, analysis and optimization of friction stir welding (FSW) processes of metallic structures using industrial robots, with a particular emphasis on the assembly of aircraft components made of aerospace aluminum alloys.Design/methodology/approachAfter a first part of the work dedicated to the kinetostatic and dynamical identification of the robotic mechanical system, a complete analytical model of the robotized process is developed, incorporating a dynamic model of the industrial robot, a multi‐axes macroscopic visco‐elastic model of the FSW process and a force/position control unit of the system. These different modules are subsequently implemented in a high‐fidelity multi‐rate dynamical simulation.FindingsThe developed simulation infrastructure allowed the research team to analyze and understand the dynamic interaction between the industrial robot, the control architecture and the manufacturing process involving heavy load cases in different process configurations. Several critical process‐induced perturbations such as tool oscillations and lateral/rotational deviations are observed, analyzed, and quantified during the simulated operations.Practical implicationsThe presented simulation platform will constitute one of the key technology enablers in the major research initiative carried out by NRC Aerospace in their endeavor to develop a robust robotic FSW platform, allowing both the development of optimal workcell layouts/process parameters and the validation of advanced real‐time control laws for robust handling of critical process‐induced perturbations. These deliverables will be incorporated in the resulting robotic FSW technology packaged for deployment in production environments.Originality/valueThe paper establishes the first model‐based framework allowing the high‐fidelity simulation, analysis and optimization of FSW processes using serial industrial robots.

This paper discusses STARsCELL, a PC-based simulator for the design and evaluation of flexible manufacturing cell (FMC) flow line systems. As a design tool, STARsCELL aids in determining the ideal number of machines, number and assignment of operators, and the size of inter-workstation buffers. The menu-driven simulator also assists in evaluating the impact on cell performance of Just-in-Time (JIT) factors, changes in product mix and demands, and different user-specified job input sequences. The paper provides numerical results for a gear workcell example to illustrate the effects of various design variables on cell performance. A brief discussion of the development, applications, advantages, and limitations of STARsCELL is also presented.

SUMMARYThis paper presents a new methodology for the joint stiffness identification of industrial serial robots and as consequence for the evaluation of both translational and rotational displacements of the robot's end-effector subject to an external wrench (force and torque). In this paper, the robot's links are supposed to be quite stiffer than the actuated joints as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors, and the number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example throughout the paper.

PurposeThis paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.Design/methodology/approachRobot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.FindingsLaguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.Originality/valueThe results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.

In this thesis we present the design and implementation of a novel self-reconfiguring modular (SR-MR) robotic system: Roombots. We are aiming at three main applications with Roombots; locomotion through self-reconfiguration in the regular cubic 3D-lattice on structured surfaces, locomotion in non-structured environments applying central pattern generators (CPG) as the locomotion controller, and self-assembly and reconfiguration of static objects of the day-to-day environment, such as furniture. Robot assemblies from self-reconfigurable modular robots have the ability to adapt to a given task and working environment by altering their shape through a series of reconfiguration moves, and attachments and detachments between the modules. We are interested in self-reconfiguring modular robots for their shape-changing capabilities, and their distributed characteristics. We envision the following applications for Roombots: First, self-reconfiguration in a structured 3D lattice, i.e. a floor and walls equipped with connectors. Embedded connectors can provide pivot points for locomotion of SR-MR assemblies, and docking and recharging places for our adaptive furniture pieces. Second, our proposed concept for locomotion control of modular robots on non-structured ground are central pattern generators. Third, we would like to build adaptive and versatile furniture from modular robots and light-weight elements. In the following we are able to count more than 60 modular robotic systems, developed over the last two decades. However we were unable to identify an existing system which could provide us with all desired kinematic and geometric capabilities. This led us to design and implement a novel self-reconfiguring modular robotic system: Roombots. To tackle the module design we attempt to identify both meaningful design parameters from existing modular robots, and essential features for our applications. The combination of both leads to the kinematic and geometric description of the Roombots modules, and eventually to its implementation. In order to be able to assemble furniture from our Roombots units in the future, we need a reconfiguration framework which supports the specific requirements of Roombots. Metamodules made of two units attached in-series are attracted and guided by a virtual force-field, they use broadcast signals, look-up tables of collision clouds and simple assumptions about their near environment to reach their seeding positions, which are currently hand coded. For the task of locomotion in non-structured environments we propose a framework for learning to move with modular robots using central pattern generators and online optimization. The distributed implementation of CPGs offers an ideal substrate for producing locomotion patterns and for online learning, and an optimization framework for fast learning.

The rapid growth of robotics and automation, especially during the last few years, its current positive impact and future projections for impact on the United States economy are very promising. This rapid growth of robotic automation in all sectors of industry will require an enormous number of technically sound specialists with the skills in industrial robotics and automation to maintain and monitor existing robots, enhance development of future technologies, and educate users on implementation and applications. It is critical, therefore, that educational institutions adequately respond to this high demand for robotics specialists by developing and offering appropriate courses geared towards professional certification in robotics and automation. In order to effectively teach concepts of industrial robotics, the curriculum needs to be supported by the hands on activities utilizing industrial robots or providing training on robotic simulation software. Nowadays, there is no robotic simulation software available to the academic institution at no cost which limits educational opportunities. As part of the NSF sponsored project, team of faculty members and students from Michigan Tech are developing new, open source RobotRun robotic simulation software which will be available at no cost for adaptation by the other institutions. This will allow current concepts related to industrial robotics to be taught even in locations without access to current robotics hardware. In addition, to teach emerging concepts of robotics, automation, and controls, authors present the design and development the state-of-the-art robotic workcell consisting of 3 FANUC industrial robots equipped with robotic vision system, programmable logic controller, a conveyer and various sensors. The workcell enables the development and programing of various industry-oriented scenerious and therefore provide students with the opportunity of gaining skills that are relevant to current industry needs.

In this chapter, effective learning approach of inverse kinematics using neural networks with efficient weights update ability has been presented for a serial link structure and industrial robot. Generally, in making neural networks learn a relation among multi inputs and outputs, a desired training data set prepared in advance is used. The training data set consists of multiple pairs of input and output vectors. The input layer receives each input vector for forward computation, and it is compared with the yielded vector from the output layer. The time required for the learning process of the neural networks depends on the number of total weights in the neural networks and that of the input-output pairs in the training data set.

Machine tools and robots have both evolved fundamentally and we can now question the abilities of new industrial robots concerning accurate task realization under high constraints. Requirements in terms of kinematic and dynamic capabilities in High Speed Machining (HSM) are increasingly demanding. To face the challenge of performance improvement, parallel and hybrid robotic architectures have emerged and a new generation of industrial serial robots with the ability to perform machining tasks has been designed. In this paper, we propose to evaluate the performance criteria of an industrial robot included in a kinematically redundant robotic cell dedicated to a machining task. Firstly, we present the constraints of the machining process (speed, accuracy etc.). We then detail the direct geometrical model and the kinematic model of a robot with closed chain in the arm and we propose a procedure for managing kinematic redundancy whilst integrating various criteria. Finally, we present the evolution of the criteria for a given trajectory in order to define the best location for a rotary table and to analyze the manipulators stiffness.

Starting in the 1970s with robots that were physically isolated from contact with their human co-workers, robots now collaborate with human workers towards a common task goal in a shared workspace. This type of robotic device represents a new era of workplace automation. Industrial robotics is rapidly evolving due to advances in sensor technology, artificial intelligence (AI), wireless communications, mechanical engineering, and materials science. While these new robotic devices are used mainly in manufacturing and warehousing, human-robot collaboration is now seen across multiple goods-producing and service-delivery industry sectors. Assessing and controlling the risks of human-robot collaboration is a critical challenge for occupational safety and health research and practice as industrial robotics becomes a pervasive feature of the future of work. Understanding the physical, psychosocial, work organization, and cybersecurity risks associated with the increasing use of robotic technologies is critical to ensuring the safe development and implementation of industrial robotics. This commentary provides a brief review of the uses of robotic technologies across selected industry sectors; the risks of current and future industrial robotic applications for worker and employer alike; strategies for integrating human-robot collaboration into a health and safety management system; and the role of robotic safety standards in the future of work.

In modern machine-building production, there are many parts that have both significant overall dimensions and complex hard-to-reach surfaces for processing. The manufacture of such parts is carried out on specialized equipment, which has the same significant overall dimensions. However, the complexity of the design of a number of parts, such as the body of a rocket engine, large volume tanks, non-separable metal structures, etc., as well as their inaccessibility, level the technological capabilities of this equipment. Currently, industrial robots equipped with tool spindles are used to process such parts. The presence of a large number of degrees of freedom of this equipment, the relatively small overall dimensions and the vastness of the working area allow them to be effectively used in this field of mechanical engineering. However, the insufficiently studied rigidity of this equipment, the lack of specific recommendations for their use significantly limit the scope of their application. Thus, the issues related to the mutual influence of the rigidity of the technological system, cutting forces and cutting conditions in the manufacture of large parts using industrial robots are relevant and require a comprehensive study. In order to study dynamic processes in the manufacture of large-sized parts using an industrial robot, experiments were carried out to determine the amplitude-frequency characteristics of vibrations that occur during processing. An experimental study made it possible to establish that the rigidity of the technological system varies over a wide range. At the same time, the rigidity of the part under an impulse load difIn modern machine-building production, there are many parts that have both significant overall dimensions and complex hard-to-reach surfaces for processing. The manufacture of such parts is carried out on specialized equipment, which has the same significant overall dimensions. However, the complexity of the design of a number of parts, such as the body of a rocket engine, large volume tanks, non-separable metal structures, etc., as well as their inaccessibility, level the technological capabilities of this equipment. Currently, industrial robots equipped with tool spindles are used to process such parts. The presence of a large number of degrees of freedom of this equipment, the relatively small overall dimensions and the vastness of the working area allow them to be effectively used in this field of mechanical engineering. However, the insufficiently studied rigidity of this equipment, the lack of specific recommendations for their use significantly limit the scope of their application. Thus, the issues related to the mutual influence of the rigidity of the technological system, cutting forces and cutting conditions in the manufacture of large parts using industrial robots are relevant and require a comprehensive study. In order to study dynamic processes in the manufacture of large-sized parts using an industrial robot, experiments were carried out to determine the amplitude-frequency characteristics of vibrations that occur during processing. An experimental study made it possible to establish that the rigidity of the technological system varies over a wide range. At the same time, the rigidity of the part under an impulse load differs from the rigidity during milling by at least an order of magnitude, and the rigidity of the spindle during milling differs from the rigidity of the part by at least 2 orders of magnitude. Based on this, in the process of designing the machining of large-sized non-rigid parts using industrial robots, it is necessary to take into account the worst conditions for rigidity. It is advisable to base further recommendations on the appointment of cutting conditions under changing processing conditions on the basis of mathematical modeling of the rigidity of the elements of the technological system. Also, to automate the process of removing the parameters of the rigidity of the technological system, an urgent task is to determine by test determination of vibrations on the spindle of an industrial robot and indirect assessment of microdisplacements on the part

In order to realize motion simulations and collision detections of serial industrial robots before actual operation, key technologies in virtual assembly, motion simulation and collision detection are presented in this paper. First, to build up virtual industrial robots which are in any form in virtual environment, a method is presented based on component-model structure. After that general kinematic model is analyzed and detail method is presented about how to calculate motion process. At last, based on OBB and BVH tree, a new algorithm is presented which partially renews BVH tree nodes. Based on algorithms mentioned in this paper, a software is wrote and several experiments are done with it. The experiment results shows that algorithms in this paper are effective for motion simulation and rapid collision detection of serial industrial robot in arbitrary form.