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The robot has passed through a development period, and is now entering an era in which robots are being utilised by industry in production. In Japan, about 1500 robots are used on production lines and more than 50 robot makers are supplying their products to the market. Many users have completed trials with industrial robots, and have reached the situation in which repeat orders are being sent to robot manufacturers as a potential way of improving productivity. Many of the robot makers have completed the initial development of their products, and in future will be promoting their sales to reap the benefits of these developments.

Japan is the world's leading user of industrial robots and its industrial robot association is a most active robot trade association. They publish regular statistics, this article by JIRA's executive director presents the figures and outlines the impact of robots up to the end of 1980.

This study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.

The authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.

The authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.

The limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.

This study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.

This paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.

This study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

Japanese production of industrial robots amounted to US$34 million in 1973 (hereafter, calculate 1 US$ = Yens 270,‐). For the last couple of years, the demand stayed weak because of the slow down of industrial investment. However, the advancement of robot technology, the improvement cost‐performance of robots, and the active investment on the improvement of productivity and labour welfare in industries caused to increase the production of industrial robots up to $48 million in 1976 and will assure the future expansion of the robot market. (See Fig.1, Fig.2).

This paper aims to propose a reasonable method to evaluate uncertainty of measurement of industrial robots’ orientation repeatability and solve the non-linear problem existing in its evaluation procedure.

Firstly, a measurement model of orientation repeatability, based on laser tracker, is established. Secondly, some factors, influencing the measurement result of orientation repeatability, are identified, and their probability distribution functions are modelled. Thirdly, based on Monte Carlo method, an uncertainty evaluation model and algorithm of measurement of industrial robot’s orientation repeatability are built. Finally, an industrial robot is taken as the research object to validate the rationality of proposed method.

Results show that the measurement model of orientation repeatability of industrial robot is non-linear, and the proposed method can reasonably and objectively estimate uncertainty of measurement of industrial robots’ orientation repeatability.

This paper, based on Monte Carlo method and experimental work, proposes an uncertainty evaluation method of measurement of industrial robots’ orientation repeatability which can solve the non-linear problem and provide a reasonable and objective evaluation. And the stochastic ellipsoid approach is firstly taken to model the repeatability of laser tracker. Additionally, this research is beneficial to decide whether the orientation repeatability of the industrial robot meets its requirements.

This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error and measurement uncertainty.

A four-point measurement model is proposed for directly measuring poses of industrial robots. First, this model consists of a position measurement model and an orientation model gotten by the position of spherically mounted reflector (SMR). Second, an influence factor analysis, simulated by Monte Carlo simulation, is performed to investigate the influence of certain factors on the accuracy and uncertainty. Third, comparisons with the common method are carried out to verify the advantage of this model. Finally, a test is carried out for evaluating the repeatability of five poses of an industrial robot.

In this paper, results show that the proposed model is better than the three-SMRs model in measurement accuracy, measurement uncertainty and computational efficiency. Moreover, both measurement accuracy and measurement uncertainty can be improved by using the proposed influence laws of its key parameters on the proposed model.

The proposed model can measure poses of industrial robots directly, accurately and effectively. Additionally, influence laws of key factors on the accuracy and uncertainty of the proposed model are given to provide some guidelines for improving the performance of the proposed model.

This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (u_RP).

Firstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation of u_RP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of the u_RP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions to u_RP.

Results show that the proposed method can reasonably and objectively estimate the u_RP of the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, the u_RP of the selected industrial robot can be restricted by using the results of its key factors on u_RP.

This paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting the u_RP and thus useful in determining whether the RP of a tested industrial robot meets its requirements.

The study aims to investigate the impact of industrial robot application on corporate labor cost stickiness and labor investment efficiency in China.

Using the textual analysis to construct firm-level industrial robot application indicators in China, we implement the methodology in Anderson et al. (2003) and Banker and Byzalov (2014) to estimate cost stickiness.

We argue that the industrial robot uses in China would increase firms’ labor adjustment costs by increasing the employment scale and upgrading the employment structure (i.e. by employing more high-skilled and high-educated labor). Consistent with our expectation through the channel of labor adjustment costs, the use of robotics increases firms’ labor cost stickiness. We further find that the positive impact is more significant among labor-intensive industries, and among state-owned enterprises with lower labor adjustment flexibility. We also find that industrial robot uses do not decrease the labor cost stickiness even when robots are more likely to substitute labor. Finally, we find that industrial robot uses significantly facilitate more efficient hiring practices by mitigating overinvestment in labor (i.e. over-hiring).

Against the backdrop of intelligent manufacturing worldwide, our study sheds new insight into the effects of new technologies on corporate labor cost behavior in developing countries. We contribute to scant studies examining how robotics, AI adoption or other automation technologies (e.g. specialized machinery, software, etc.) affect corporate cost behavior.

In the USSR industrial robots (automatic manipulators) are considered to be one of the most important means of achieving complex industrial automation. They provide a means for human emancipation from dangerous, hard and boring labour and solution to the problem of the more efficient use of labour resources. At present the programs for development, production and application of industrial robots are being implemented in the Soviet Union on the basis of a state integrated 5‐year plan covering the key branches of industry and involving the Academy of Sciences and Higher Educational Institutions. A second similar program will be completed by 1980. It is based on the principle of central state unification of the major components of robots, a series of standard sizes and consequently the development of robot‐equipped standard technological complexes. Simultaneously, research is being carried on in the development of the next generation of robot devices. Some other aspects of the problem are also being investigated including the development of methods for evaluating the economic efficiency of robot application as well as social aspects and training of personnel.