Industrial robots and export growth: a cross-country analysis

Industrial robots play a vital role in transforming and upgrading the manufacturing industry. They harness automation technologies to drive industrial production and enhance their value through innovations in production tools and knowledge. This paper analyzes annual data from China's A‐share nonfinancial manufacturing listed companies during the period from 2007 to 2019, examining the impact of industrial robot applications on corporate cash holdings. The study discovers that the application of industrial robots notably reduces corporate cash holdings, thereby confirming the effect of capital allocation. The analysis rules out the possibility that this reduction occurs through alleviating agency problems. Mechanism analysis reveals that the application of industrial robots reduces cash holdings for precautionary motives by reducing labor leverage and enhancing labor productivity and operational efficiency. Additional tests reveal that the reduction in corporate cash holdings due to industrial robot applications is more pronounced in enterprises with intense market competition, labor‐intensive and nonstate‐owned enterprises. This study deepens the research focus on industrial robot applications and corporate cash holdings, providing a theoretical basis for policymakers to promote technological innovation and industrial advancement.

Intelligent manufacturing is the theme and main direction of the “Made in China 2025” development strategy, and the application of industrial robots is an important direction of intelligent manufacturing. In the next few years, industrial robots will be widely used in various enterprises, which will inevitably require a large number of high-tech industries. Industrial robots are high-tech products of modern society and play an important role in the process of economic development, especially in the manufacturing industry. Industrial robot technology is widely used in automated production lines, so that industrial production efficiency can be greatly improved. Instead of manual labor to carry out various complex production and operations, to achieve industrial production automation. Analyze the application of industrial robots in automated production lines at this stage, and explore their future development directions, so that they can better serve the manufacturing industry. This article takes the industrial robots and PLCs in the industrial automation production line as the research object, and takes the automated production line for mass production of a product as an example. It explains the joint control scheme of the PLC controller and the industrial robot controller, and provides for the construction of joint control of similar production lines in the future.

Industrial robot application technology is an important course for mechanical college students, and robot is a kind of relatively expensive equipment. So in the daily learning process of robots, there may not be so many objects for everyone to learn and train. In this paper, virtual reality technology is used to simulate the industrial robot and its scene. In this paper, three-dimensional modeling is completed by Solidworks software, and the industrial robot body is constructed. Then this paper uses 3DS Max software to model the application environment, assembly line and classroom which need industrial robot. Finally, this paper uses Unity3D software for virtual reality programming and simulation design. Through the design, this paper based on virtual reality technology for industrial robot technology and application courses teaching, building the basic line. This has laid a solid foundation for the later stage virtual reality technology to perfect the aspect of teaching.

With the rapid development of industrial automation, the traditional manual operation is no longer suitable for the development of modern enterprises, because the industrial robot control system dynamic response is fast, high position accuracy, strong overload capacity, so it is very suitable for t he production of mechanical parts and processing line automation transformation. In this paper, an air conditioning compressor company to the pump body production line for the theme of automation, the application of industrial robots instead of artificial automation production. Aiming at the transformation of the L2 series pump body assembly line in the assembly plant of the company, the industrial robot was used to transform the production line, and the program debugging was carried out on the site. The robot was able to run stably and work as required. At last, the actual working beat of the robot is calculated to be 13.7 seconds, which is 2.3 seconds less than 16 seconds in manual operation. Experimental results show that the actual working tempo of the robot can meet the requirements, and can improve the assembly efficiency and save manpower.

Green Total Factor Productivity (GTFP) is critical to the global green transformation and ESG strategy. In this study, we investigate the impact of industrial robot application on enterprises’ green total factor productivity based on the automation-augmentation perspective. The results of the study show that industrial robot application greatly promotes GTFP. Mechanism analysis shows that industrial robot application further enhances GTFP by increasing the degree of green transformation and asset specificity. Heterogeneity test shows that firms with green investors, higher level of regional intellectual property rights protection, and higher degree of regional openness to the outside world have a more significant role in promoting GTFP by industrial robot application. This study enriches the literature on technological progress on green performance growth and provides valuable insights for practical applications.

Does industrial robot application promote green technology innovation in the manufacturing industry?

Although many algorithms perform very well on certain datasets, existing stereo matching algorithms still fail to obtain ideal disparity images with high precision in practical robotic applications with weak or untextured objects. This greatly limits the application of binocular vision for robotic arm guidance. Traditional stereo matching algorithms suffer from disparity loss, dilation and other problems, and deep learning algorithms have weakly generalization ability, making high‐accuracy results impossible with non‐training images. We propose an algorithm that uses segments and edges as matching units. We find the mapping relationship between two‐dimensional images and three‐dimensional scenes using segments. The algorithm obtains highly accurate results in industrial robotic applications with mainly planar facets. We combine it with a deep learning algorithm to obtain very good high‐accuracy results in both general scenes and applications of industrial robots. The algorithm effectively improves the non‐linear optimization ability of traditional algorithms and generalization ability of deep learning, and provides an effective method for the binocular vision guidance of industrial robotic scenes. We used the algorithm to guide the robot arm for threading with a success rate of 70%.

Industrial robot population has been growing at a fast pace during the last decade. With the impending technological breakthroughs, the number of industrial robots is expected to grow at a much higher rate. This paper addresses certain human factors issues that must be considered before and during the installation and operation of a robot work system.

In this study, we aim to explain the large disparities among countries and regions on industrial robot application in terms of robot density and robot growth. Based on the premise that people in all cultures have the same potential for innovation, we propose a cross-level lens of cultural tightness-looseness to predict that, in the nascent robotics industry where rules and regulations are underdeveloped (i.e., a loose domain), people in tight cultures (e.g., Singapore, Japan, China) are more likely to innovate than those in loose cultures (e.g., the UK, U.S., the Netherlands) because their creativity is permitted in this or a few other loose domains only. We test this theoretical lens using multi-source longitudinal archival data on robot applications. Several significant findings emerge. First, there is a significant positive relationship between cultural tightness and robot application across 32 countries and territories from 1993 to 2022 (Study 1). Second, such a positive relationship also appears across 50 states in the United States from 1998 to 2022 (Study 2a), and across 31 provinces in China from 2008 to 2022 (Study 2b). Finally, the interaction effect between country- and region-level cultural tightness on robot application is significant (Study 3). These findings provide strong empirical support for our cross-level lens of cultural tightness and shed light on how cultural tightness at different levels interacts to affect incremental innovation (i.e., robot application) in a loose domain (i.e., the robotics industry). Moreover, these findings suggest that loosening tight control on certain domains of a tight culture would remarkably boost creativity and incremental innovation in these domains.

This paper proposes a novel force-sensor-less contact motion control for quick and smooth industrial robot motion. Industrial robots serve important functions in modern industrial society. However, their general application is limited because they employ only position based high-stiffness control methods. The proposed method achieves smooth contact motion for new applications of industrial robots, and it solves two of the problems of contact motion control. First, impulsive force is reduced through active braking motion control. Second, wasted motion is decreased by applying integral-proportional(I-P) force control after contact. Experimental results show the validity of the proposed method with a three-degree-of-freedom(DOF) robot. The proposed method achieves a 78.7% decrease in settling time and a 6% reduction in impulsive force. The proposed method has the potential to improve fast contact motion through a profile control application.

Much of the technology that makes robots reliable, human friendly, and industrial robotics adaptable for numerous applications has emerged from manufacturers of industrial robots. With an estimated installation base in 2014 of about 1.5 million units, some 171000 new installations in that year and an annual turnover of the robotics industry estimated to be US$ 32 billion, industrial robots are by far the largest commercial application of robotics technology today. The foundations for robot motion planning and control were initially developed with industrial applications in mind. These applications deserve special attention in order to understand the origin of robotics science and to appreciate the many unsolved problems that still prevent the wider use of robots in today’s agile manufacturing agile manufacturing environments. In this chapter, we present a brief history and descriptions of typical industrial robotics applications and at the same time we address current critical state-of-the-art technological developments. We show how robots with different mechanisms fit different applications and how applications are further enabled by latest technologies, often adopted from technological fields outside manufacturing automation. We will first present a brief historical introduction to industrial robotics with a selection of contemporary application examples which at the same time refer to a critical key technology. Then, the basic principles that are used in industrial robotics and a review of programming methods will be outlined. We will also introduce the topic of system integration particularly from a data integration point of view. The chapter will be closed with an outlook based on a presentation of some unsolved problems that currently inhibit wider use of industrial robots.

In the past few decades, robots have played a significant role in both industrial and technological advancements. Cloud-integrated industrial robotics provide a vast network of machines to industries. The integration of robotics with cloud computing offers increased computational power for various applications of industrial, communication, healthcare, disaster management, defence systems, and space exploration missions. It also provides reliable and extensive accessibility across a network of devices. In this chapter, the authors delve into the fundamentals of robotics and cloud computing. They introduce the core concepts of robotics and cloud computing, followed by their integration. Subsequently, they explore communication in cloud robotics, encompassing machine-to-machine (M2M) and machine-to-cloud (M2C) communication. They then examine the major applications in industrial robotics and types of robots that leverage cloud robotics technology. They conclude by addressing security issues and challenges in cloud robotics.

With the wide application of mobile robots in industry, path planning has always been a difficult problem for mobile robots. Reinforcement learning algorithms such as Q-learning play a huge role in path planning. Traditional Q-learning algorithm mainly uses - greedy search policy. But for a fixed search factor -greedy. For example, the problems of slow convergence speed, time-consuming and many continuous action transformations (such as the number of turns during robot movement) are not conducive to the stability requirements of mobile robots in industrial transportation. Especially for the transportation of dangerous chemicals, continuous transformation of turns will increase the risk of objects toppling. This paper proposes a new method based on - greedy 's improved dynamic search strategy is used to improve the stability of mobile robots in motion planning. The experiment shows that the dynamic search strategy converges faster, consumes less time, has less continuous transformation times of action, and has higher motion stability in the test environment.

SUMMARY Milling is one of the most widely used metal removal processes. The number of decision parameters involved in the milling operation makes the experimental estimation of tool life equations very dimcult. Optimal metal removal rate has been modelled independently of the cutter path selected for the operation. However, the choosing of the proper cutter path might significantly reduce the total tool travel and therefore also reduce the tool wear due to the reduction in the tool engagement with the job With the widespread application of robotics in industry, robots are also being used to automate the grinding process. Robotized grinding of flat polygonal surfaces is one such application where the tool path is similar to face milling of like surfaces. Thus optimizing the total tool path during NC face milling/robotized grinding remains an important problem A mathematical model representing the total tool path on an N-sided convex polygonal surface has been developed. The stair-case type of tool path has been considered. The resulting formulation is complex and cannot be solved using standard analytic or numeric methods. An algorithm has been proposed to find an optimal solution using the above model, by enumerating over tool sweep angles between 0° and 180°. This algorithm can be easily coded and run on a PC. Finally a detailed example is given explaining the application of this algorithm.

The production process of any type of product today is difficult to imagine without the use of industrial robots. Their versatility, production flexibility and wide technological capabilities make them an indispensable tool in modern manufacturing, including in such economically and strategically important industry as shipbuilding. In this regard, according to the authors, it is advisable to analyze the current situation and prospects for the use of robotization in industry, in particular, shipbuilding in Russia and abroad. The article presents statistical data on indicators of the level of robotization of domestic and foreign industry; describes the trends in the development of industry during its robotization, indicates the scope of application of industrial robots, etc. The factors of expediency of using robots in industry are analyzed. The inevitability of the general growth of industrial robotization and, as a result, a change in the economic structure in developed countries and, possibly with a certain lag in Russia has been substantiated. Identified problematic issues associated with the introduction and use of industrial robots in the domestic industry, in particular, shipbuilding.