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This study aims to obtained the failure probability distributions of subsystems for industrial robot and filtrate its fault data considering the complicated influencing factors of failure rate for industrial robot and numerous epistemic uncertainties.

A fault data screening method and failure rate prediction framework are proposed to investigate industrial robot. First, the failure rate model of the industrial robot with different subsystems is established and then the surrogate model is used to fit bathtub curve of the original industrial robot to obtain the early fault time point. Furthermore, the distribution parameters of the original industrial robot are solved by maximum-likelihood function. Second, the influencing factors of the new industrial robot are quantified, and the epistemic uncertainties are refined using interval analytic hierarchy process method to obtain the correction coefficient of the failure rate.

The failure rate and mean time between failure (MTBF) of predicted new industrial robot are obtained, and the MTBF of predicted new industrial robot is improved compared with that of the original industrial robot.

Failure data of industrial robots is the basis of this prediction method, but it cannot be used for new or similar products, which is the limitation of this method. At the same time, based on the series characteristics of the industrial robot, it is not suitable for parallel or series-parallel systems.

This investigation has important guiding significance to maintenance strategy and spare parts quantity of industrial robot. In addition, this study is of great help to engineers and of great significance to increase the service life and reliability of industrial robots.

This investigation can improve MTBF and extend the service life of industrial robots; furthermore, this method can be applied to predict other mechanical products.

This method can complete the process of fitting, screening and refitting the fault data of the industrial robot, which provides a theoretic basis for reliability growth of the predicted new industrial robot. This investigation has significance to maintenance strategy and spare parts quantity of the industrial robot. Moreover, this method can also be applied to the prediction of other mechanical products.

In this report, accounts will be presented on the experience obtained from approximately 100 practical applications of industrial robots. The industrial robots used derive partly from the company's own production as well as from other domestic and foreign robot manufacturers.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

The purpose of this paper is to present a technique for assessing and comparing the static and dynamic performance of three different models of small six-axis industrial robots using a Renishaw XL80 laser interferometer system, a FARO ION laser tracker and a Renishaw QC20-W telescoping ballbar.

Specific test methods are proposed in this work, and each robot has been measured in a similar area of its working envelope. The laser interferometer measurement instrument is used to assess the static positioning performance along three linear and orthogonal paths. The laser tracker is used to assess the contouring performance at different tool center point (TCP) speeds along a triangular tool path, whereas the telescoping ballbar is used to assess the dynamic positioning performance for circular paths at different TCP speeds and trajectory radii.

It is found that the tested robots behave differently, and that the static accuracy of these non-calibrated robots varies between 0.5 and 2.3 mm. On the other hand, results show that these three robots can provide acceptable corner tracking at low TCP speeds. However, a significant overshoot at the corner is observed at high TCP speed for all the robots tested. It was also found that the smallest increment of Cartesian displacement (Cartesian resolution) that can be taken by the tested robots is approximately 50 μm.

The technique used in this paper allows extremely accurate diagnosis of the robot performance, which makes it possible for the robot user to determine whether the robot is in good or bad condition. It can also help the decision-maker to select the most suitable industrial robot to achieve the desired task with minimum cost and specific application ability.

This paper proposed a new method based on the performance verification approach for solving the robot selection problem for flexible manufacturing systems. Furthermore, despite their importance, bidirectional repeatability and Cartesian resolution are never specified by the manufacturers of industrial robots nor are they described in the ISO 9283:1998 guide, and they are rarely the object of performance assessments. In this work, specific tests are performed to check and quantify the bidirectional repeatability and the Cartesian resolution of each robot.

The 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.

Specific 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.

It 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.

It 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.

This 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.

The purpose of this paper is to propose a robot-assisted assembly system (RAAS) for the installation of a variety of small components in the aircraft assembly system. The RAAS is designed to improve the assembly accuracy and increase the productive efficiency.

The RAAS is a closed-loop feedback system, which is integrated with a laser tracking system and an industrial robot system. The laser tracking system is used to evaluate the deviations of the position and orientation of the small component and the industrial robot system is used to locate and re-align the small component according to the deviations.

The RAAS has exhibited considerable accuracy improvement and acceptable assembly efficiency in aircraft assembly project. With the RAAS, the maximum position deviation of the component is reduced to 0.069 mm and the maximum orientation deviation is reduced to 0.013°.

The RAAS is applied successfully in one of the aircraft final assembly projects in southwest China.

By integrating the laser tracking system, the RAAS is constructed as a closed-loop feedback system of both the position and orientation of the component. With the RAAS, the installation a variety of small components can be dealt with by a single industrial robot.

In 1970 only two manufacturers existed in the United States, namely the American Machine and Foundry (AMF) Versatran and the Unimation, Inc. Unimate. These robots, still in the forefront today, were just emerging and gaining acceptance in 1970, with approximately 200 industrial robots at work in the U.S., and an amassed 600,000 hours on the job, a negligible amount considering that the total U.S.blue collar work force puts in 200 million hours each day. However more than seventeen types of robots are now available in the U.S. at least twelve of which are manufactured in this country. They range from minirobots with payloads of only a few ounces and reaches of less than a foot to the larger universal robots which can handle payloads of up to 150 lbs., reach 3 ½ ft., and move at speeds up to 3 ft./sec. Recent additions to the U.S. arsenal are the Burch Control robot with a payload capacity of 6000 lbs. Industrial robots are easily reprogrammable, operatorless handling devices that can perform simple, repetitive jobs that require few alternative actions and minimum communications with the work environment. They are well suited to handling parts that are red hot or feezing cold, and they can function in corrosive, noxious or extremely dusty atmospheres that would be injurious to human beings. Passage in the United States of the Occupational Safety and Health Act of 1970 has provided strong impetus for the use of industrial robots. As discussed in a recent article in Assembly Engineering Magazine (Ref.1), the Act currently states that a human being cannot place his hands within punch press dies to load or remove parts, and it is imminent that OSHA standards will be extended to cover other fabricating and assembly machines, such as staking presses, spot welding machines, riveting machines, holding and clamping equipment, electron component Inserting equipment, and automatic screwdriving machines. In many cases the cost and time to retool an existing operation to conform to the standards will be prohibitive compared to the cost and time required to purchase and program an industrial robot to perform the potentially dangerous operations.

The purpose of the chapter is to focus on the global industrial robotics market and trends of its development. In the framework of this chapter, the authors made the forecast of industrial robots' market future values in this chapter with the linear regression method and an econometric model. This analysis has provided a conclusive answer to the question about the prospects of the industrial robotics market and the leading countries. The completed forecast showed that the global robotics market will continue to grow, thanks to the wider adoption of industrial robots, which will be used in new industries, the development of contactless user interfaces, which, among other things, will be implemented in the automotive applications, the focus on predictive maintenance and remote monitoring of equipment, as well as the transition of a large number of enterprises to digital management and full automation of existing equipment to improve the quality and productivity of processes. The authors show that in 2020 the global robotics market volume decreased due to the COVID-19 pandemic and major shift in production value chains, but in 2021 the indicator will grow again, but not so rapidly, at a more moderate pace. By 2025, the global industrial robotics market may exceed $61.4 billion, with a growth rate of 8.5%.

The purpose of this paper is to provide a review of the interdisciplinary research field, autonomous industrial mobile manipulation (AIMM), with an emphasis on physical implementations and applications.

Following an introduction to AIMM, this paper investigates the missing links and gaps between the research and developments efforts and the real‐world application requirements, in order to bring the AIMM technology from laboratories to manufacturing environments. The investigation is based on 12 general application requirements for robotics: sustainability, configuration, adaptation, autonomy, positioning, manipulation and grasping, robot‐robot interaction, human‐robot interaction, process quality, dependability, and physical properties.

The concise yet comprehensive review provides both researchers (academia) and practitioners (industry) with a quick and gentle overview of AIMM. Furthermore, the paper identifies key open issues and promising research directions to realize real‐world integration and maturation of the AIMM technology.

This paper reviews the interdisciplinary research field, autonomous industrial mobile manipulation (AIMM).

This paper proposes a simple technique for assessing the effect of gear transmission errors in a six‐axis industrial serial robot, as these errors can vitally affect the industrial robot's positioning accuracy.

The experimental procedure is developed using a laser interferometer system to measure bidirectional linear position errors for an ABB IRB 1600 industrial robot. A simple technique based on fast Fourier transformation (FFT) analysis is devised and implemented for the characterization, evaluation, and quantification of gear transmission errors. Structural deformation and backlash error are also discussed.

The authors found that the major sources of error affecting the performance of the robot come from joints two and three. They also found that eccentricity errors, structural deformations, and backlash are the most important sources of error affecting the accuracy and the repeatability of the industrial robot studied. Additional tests show that the robot's first joint has relatively poor bidirectional repeatability.

The usefulness of a laser tracker (or any other large range portable 3D measurement system) is questionable for assessing – let alone analyzing in depth – the gear transmission errors of some of today's industrial robots. The authors demonstrate in this paper that a laser interferometer system can successfully measure gear transmission errors very accurately. The proposed methodology is simple, efficient, and easy to use for the characterization and quantification of the errors.

This work is the first to detail the use of the laser interferometer system for the characterization of the gear transmission errors of an industrial robot. A methodology has been developed and implemented for very accurately quantifying the effects of gear transmission errors, structural deformations, and backlash. The proposed methodology greatly simplifies the measurement set‐up and accelerates error quantification.