Robot Installations Research Articles

Technological anxiety: Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood. Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an “icing on the cake” or “adding fuel to the fire” needs further study. This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy. First, from the theoretical logic and the economic development law, this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs. Then, based on the panel data of 269 cities in China from 2006 to 2021, we use the two-way fixed effect model, dynamic threshold model, and two-stage intermediary effect model. The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism. Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the “creation effect”. In other words, advanced digital technology has created additional jobs, and the overall supply of employment in the labor market has increased. The conclusion is still valid after the endogeneity identification and robustness test. In addition, the positive effect has a nonlinear effect on the network scale. When the installation density of industrial robots exceeds a particular threshold value, the division of labor continues to deepen under the combined action of the production efficiency and compensation effects, which will cause enterprises to increase labor demand further. Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions. This study concludes that in the digital China era, the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market. This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

Robot-assisted laparoscopic ureteroureterostomy in a child with upper urinary tract duplication

Upper urinary tract duplication remains one of the most challenging pediatric urology conditions. Various operative methods are used in the treatment of children with this pathology; however, reoperation rate remains high. This study aimed to investigate a case of successful robot-assisted laparoscopic ureteroureterostomy and discuss the technical aspects of this procedure and review known series of robotic ureteroureterostomy. The authors retrospectively reviewed the medical history of a child with duplication of the right kidney, accompanied by reflux of urine into the lower segment collecting system. Surgical intervention was performed using robot-assisted technology. Using computed tomography and voiding cystourethrography, duplex kidney with vesicorenal reflux into the lower segment was diagnosed. The surgical technique used was ureteroureterostomy. The donor ureter was divided in the area of the intended anastomosis. Then, a surgical incision was made in the recipient ureter, the length of which was equal to the diameter of the donor ureter. After preparation of the ureters, an end-to-side anastomosis was performed. The operation was successfully performed without intraoperative difficulties or complications and lasted for 140 minutes. The robot installation time (docking time) was 20 minutes, and the main console time was thus 120 minutes. The patient started feeding on the same day after the operation. The drainage tube was removed after a control ultrasound examination on postoperative day 2. The stent remained in the recipient ureter until its removal 6 weeks after surgery. The duration of follow-up was 6 months. The patient was asymptomatic throughout the control period. Repeated ultrasound examination performed after surgery showed a decrease in the anteroposterior diameter of the lower segment pelvis to 5 mm. Blood flow in the upper and lower segments of the right kidney was not impaired. The advantages of the robotic approach, including improved instrument dexterity and 3D visualization, make it a safe and effective alternative to open or laparoscopic surgery in children.

A scheme of installing ALC wall panels based on autonomous mobile robot

Autoclaved lightweight concrete (ALC) wall panels are widely used in building envelope structures. Due to the limitations of their sizes and architectural environment, installing ALC wall panels is very complex, requiring significant labor and time costs. Construction robots provide enhanced efficiency, yet current façade installation robots lack comprehensive on-site automation. In this study, an on-site wallboard installation robot with sensors, a mobile base, and a mechanical gripper was self-designed. Based on this robot, an automated installation scheme with integrated functions was proposed for the multiple steps from grasping to installing the wall panel. The robot could recognize and judge the posture of the wall panel through a robot vision algorithm and was able to navigate according to the simultaneous localization and mapping (SLAM). The proposed scheme achieved good results in both simulation and field testing. The robot automatically completed multiple tasks, from grasping to placing ALC wall panels, significantly reducing the difficulty of manually installing ALC wall panels and avoiding construction hazards.

Impact of Robot Installations on Employment and Labour Productivity in Automotive Industry

Impact of Robot Installations on Employment and Labour Productivity in Automotive Industry

Robot-assisted distal pancreatectomy with spleen preservation in the treatment of a child with a solid pseudopapillary tumor

The use of robots in pancreatic surgery offers several advantages as an adjunct to laparoscopic surgery, including increased maneuverability of robotic instruments and three-dimensional (3D) visualization. To our knowledge, only two cases of robot-assisted distal pancreatectomy with spleen preservation in children have been reported worldwide. In this study, the patient was an 11-year-old boy who was admitted to a children’s hospital with complaints of recurrent upper abdominal pain. He was diagnosed with pancreatic tumor based on ultrasound findings. It was confirmed by magnetic resonance imaging, which revealed a well-defined heterogeneous formation at the border of the body and tail of the pancreas, measuring 2.28 × 2.73 × 2.62 cm with compression of the Wirsung duct. The surgical intervention was performed using a surgical robot VERSIUS (CMR, (UK). Splenic vessels were mobilized carefully, a tourniquet was placed around the body of the pancreas, and it was intersected using a stapler at the border of healthy tissue. The surgical intervention took 340 min, including robot installation time (docking time) of 15 min and a main console time of 325 min. No serious intraoperative complications, such as bleeding or damage to the vascular structures adjacent to the pancreas (branches of the celiac trunk and portal vein), were noted. Histological examination of the tumor confirmed the diagnosis of a solid pseudopapillary tumor. After surgery, the patient’s condition was stable. Recovery proceeded without complications. Magnetic resonance imaging of the abdominal cavity, which was performed 6 months after surgery, revealed no signs of disease recurrence. Robot-assisted surgery is an acceptable alternative to laparoscopic and open surgery for patients with solid pseudopapillary pancreatic tumors because robots offer additional connections, enable closure in improved 3D imaging, increase dexterity when handling instruments, and eliminate of hand tremors.

ИСПОЛЬЗОВАНИЕ РОБОТ-АССИСТИРОВАННОЙ ТОРАКОСКОПИЧЕСКОЙ ХИРУРГИИ У РЕБЕНКА 9 ЛЕТ С КИСТОЗНОЙ ФОРМОЙ УДВОЕНИЯ ПИЩЕВОДА

Purpose of this research was to share the Russia’s first clinical experience in the use of robot for thoracoscopic removal of cystic esophageal duplication and to explore whether robot could be involved in further thoracic esophageal surgeries. Authors represent a report of a clinical case of robot-assisted surgical treatment of a cystic tumor of the esophagus in a patient aged 9 y/o using the Versius Surgical Robot. The procedure was performed using three robotic modules - optical (10 mm, 3D visualization) and the two instrumental (5 mm each). An additional 5 mm port was used to deliver suture material and non-robotic instruments. Two-lung traditional ventilation was used during the surgical intervention. Aspiration of the cyst before final resection facilitated thoracoscopic visualization and removal of the specimen without the need for a mini-thoracotomy. The surgical intervention consisted of a longitudinal dissection of the muscular layer of the esophagus and enucleation of the cystic formation followed by covering of the muscular defect of the esophagus in order to ensure the integrity of its lumen. The total intervention duration was 155 minutes, of which the duration of robot installation (docking time) was 15 minutes and the duration of the main stage of the procedure was 140 minutes. No intraoperative or postoperative complications were recorded. Histological examination demonstrated the signs of the cystic form of duplication of the esophagus with the presence of ectopic gastric mucosa in its structure. The patient stayed in the hospital for seven days; there was no relapse of the disease observed during the entire observation period and therefore no repeated interventions were required. The subsequent control fibroesophagogastroscopy demonstrated a smooth profile of the esophageal mucosa without signs of a tumor mass. Conclusion: the use of robot-assisted thoracoscopic surgical access is a safe and effective method for treating cystic duplication of the thoracic esophagus.

Proposal of a human-in-the-loop-based framework for advancing maintenance applications for collaborative robots

Manufacturing companies are improving shop floor tasks, especially related to assembly, thanks to the installation of collaborative robots, shortly cobots. Despite their reliability, they experience intrinsic difficulties in extending the CBM (condition-based maintenance) solutions from traditional machinery. The inherent challenges are due to the cobot flexibility, on-the-job training from operator, and internal control for trajectory optimization in cobot operations. Therefore, this research work tackles the issue of developing CBM by leveraging on the human-machine collaborative setting, proposing a human-in-the-loop (HIL)-based framework. The framework is demonstrated via a laboratory-scale application through induced functional failures. The demonstration shows that, via entropy-controlled prompting, the operator can provide feedback about CBM algorithms’ prediction accuracy. Based on the current outcomes, a roadmap for further improving the HIL-based solution for cobot maintenance is proposed, with the end purpose of promoting complete monitoring of all the equipment on the companies’ shop floor fostering the smart manufacturing paradigm.

A Study on Improving Efficiency and Reliability of Automated Connector Testing for Aerospace Applications

Automation is crucial for the future of the industry as it enhances efficiency, quality, and accuracy while reducing operating time and the occurrence of human errors. Establishing an automated factory requires significant resources, including robot installation, worker training, program development, and ensuring quality and safety measures. This paper presents a study on automating the testing process for an aerospace company aiming to enhance productivity and minimise errors. The study aimed to achieve full task automation using a Universal Robotics Arm (UR5), which undertook the tasks of retrieving, inserting, securely locking, and removing the six connectors into the equipment, effectively executing the entire process. In initial trials, wireless connectors exceeded expectations, achieving 16 cycles in 2 hours. The inclusion of cables brought about significant challenges, particularly in terms of cable entanglement and concerns regarding the durability of connectors. Proposed solutions include improving the rack system and refining the gripper’s functionalities. This highlights the project’s potential for transformative advancements in aerospace manufacturing.

Employing artificial intelligence and enhancing resource efficiency to achieve carbon neutrality

This study collected annual data from 2000 to 2020 for ten polluting industries in China, investigating the impact of energy efficiency and artificial intelligence on carbon neutralization. The findings indicate that increased industrial robot installation facilitates short-term and long-term carbon neutralization. In addition, an increase in energy efficiency facilitates short-term and long-term carbon neutralization. Investing in artificial intelligence (AI) and robotic technologies to boost carbon neutralization is recommended. Key practical recommendations from this research include promoting sustainable AI, investing in green technologies, and hiring a green-minded, skilled workforce.

A Novel Sampling-Based Optimal Motion Planning Algorithm for Energy-Efficient Robotic Pick and Place

Energy usage in robotic applications is rapidly increasing as industrial robot installations grow. This research introduces a novel approach, using the rapidly exploring random tree (RRT)-based scheme for optimizing the robot’s motion planning and minimizing energy consumption. Sampling-based algorithms for path planning, such as RRT and its many other variants, are widely used in robotic motion planning due to their efficiency in solving complex high-dimensional problems efficiently. However, standard versions of these algorithms cannot guarantee that the generated trajectories are always optimum and mostly ignore the energy consumption in robotic applications. This paper proposes an energy-efficient industrial robotics motion planning approach using the novel flight cost-based RRT (FC-RRT*) algorithm in pick-and-place operation to generate nodes in a predetermined direction and then calculate energy consumption using the circle point method. After optimizing the motion trajectory, power consumption is computed for the rotary axes of a six degree of freedom (6DOF) serial type of industrial robot using the work–energy hypothesis for the rotational motion of a rigid body. The results are compared to the traditional RRT and RRT* (RRT-star) algorithm as well as the kinematic solutions. The experimental results of axis indexing tests indicate that by employing the sampling-based FC-RRT* algorithm, the robot joints consume less energy (1.6% to 16.5% less) compared to both the kinematic solution and the conventional RRT* algorithm.

Research on the impact of industrial robot application on the status of countries in manufacturing global value chains.

The fast growth in the installation of industrial robots has had a major impact on the comparative advantage of nations and the division of labor in global value chains in the era of smart manufacturing. Using various econometric models and panel data from 18 industries in 38 countries from 2000 to 2014, this paper empirically examines the impact of industrial robot applications on the status of countries in manufacturing global value chains and its mechanisms. The study demonstrates that industrial robot application can effectively improve the status of countries in manufacturing global value chains, and this improving effect is more obvious for developing countries and labor-intensive and technology-intensive industries. Mechanism testing shows that industrial robot application can effectively enhance the development level of highly skilled human capital and productive service industries, thereby improving the status of the manufacturing global value chain. This study provides a theoretical basis and policy reference for countries to enhance their status in the global value chain through industrial robot applications in the future.

Development of an Earthworm-Type Electrical Wire Installation Assistance Robot Using Artificial Muscles

In this study, an earthworm-type electrical wire installation assistance robot is proposed using pneumatic artificial muscles. This paper contributes to describing the design and experiments regarding a robot that can safely and automatically install electrical wires in complex conduits within a limited installation deadline. In this study, we aim to develop a robot to assist in the installation of electrical wires in conduits. This study contributes to the development of a robot for electrical wire installation assistance and the results from field experiments. Based on previous studies, a robot to install wires in long and narrow conduits has not been developed. In this study, the applicability of the robot to electrical wire installation assistance is presented. The results showed that the robot can assist in the installation of electrical wires at average speeds of 9.6 mm/s in straight conduits and 8.4 mm/s in multi-conduits. The results show the potential that the proposed robot can significantly reduce the workload in wire installation. Furthermore, the model of the wire installation robot enables estimation of the duration of the wire installation. Therefore, in this study, insights into the development of an in-pipe wire installation assistance robot are provided.

Sustainable growth through industrial robot diffusion: Quasi‐experimental evidence from a Bartik shift‐share design

AbstractWhile the diffusion of industrial robots has had a significant impact on the economy and society, more research is needed to understand how robots contribute to sustainable growth. This study uses paired data on China's county‐level carbon emissions and industrial robot installations from 2008 to 2017, employing a Bartik shift‐share instrumental variable design to estimate the economic and sustainable effects of industrial robot diffusion. The study finds that industrial robots significantly promote economic growth and contribute to carbon emission reduction as confirmed by robust IV 2SLS and general PSM‐DID methods. Additionally, a heterogeneity analysis shows that industrial robots have a stronger impact on sustainable growth in underdeveloped and small‐medium cities, especially in low‐skilled industries. Finally, the study identifies industrial structural change, clean energy use, and improved productivity and innovation as key factors that mediate the impact of industrial robots on sustainable development.

Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms

The coordinated promotion of pollution control and carbon reduction is intended to build a more beautiful China. Intelligent industrial technology plays an important role in the fight against climate change and in improving the ecological environment. Based on panel data from 30 provinces in China from 2006 to 2020, we used a two-way fixed effects model to evaluate the synergistic effects of industrial intelligent transformation on pollution control and carbon reduction and its mechanisms. The results showed that the introduction and installation of industrial robots by enterprises significantly reduced carbon emissions and the concentration of fine particles in the air, as well as having the synergistic effect of reducing pollution and carbon. This conclusion was still robust after using instrumental variable methods to perform endogenous tests. The study also showed that industrial intelligence reduced pollution and carbon through mechanisms that promoted green technological innovation and improved energy efficiency. The conclusions of this study could provide evidence for the use of digital technologies to promote environmental protection and achieve the goal of carbon neutrality, as well as play a significant role in the promotion of economic and societal green transformation.

The Impact of Industrial Intelligence on Carbon Emissions: Evidence from the Three Largest Economies

Many studies are exploring the generated factors of carbon emissions to make a contribution to environmentally sustainable development as carbon emissions have increased by more than 5% in the past ten years. However, few investigations have considered the effects of industrial intelligence on carbon emissions. In order to discover whether the development of industrial robots will influence the environment, this paper employs the IFR data of industrial robots from 2006 to 2021 to investigate their impacts on carbon emissions in the three largest economies by using the classical linear regression model, OLS (Ordinary Least Squares), from the factors of robot installations and robot density, which are measured by ownership per thousand manufacturing people, respectively. The positive correlation coefficients of robot installation and density in the USA are 0.010 and 0.011; they are 0.185 and 0.204 in China; and 0.156 and 0.142 in Japan. To ensure the reliability of the results, we also do a robustness test and an endogeneity test by using the two-way fixed effect model, and they show the same results. The main findings of our study show that industrial intelligence can have significant positive impacts on carbon emissions in the three economies and this means that the application of industrial intelligence not only accelerates economic growth, but also causes the pressure on the environment. Moreover, the verification results also indicate that the impacts of industrial intelligence on carbon emissions are dominated by driving effects, and the higher the robot density, the stronger the driving effects on carbon emissions. Based on the findings, corresponding policy suggestions are proposed to guide governments in trimming their environment protection policies more efficiently.

25 Years Ago March 1998

Wire EDM proving beneficial at top racing car builders; Mollart Cox expanding fast; continued success at T S Harrison & Sons and Colchester Lathe Company; machine tools produced globally down 4.2% in 1997; and UK robot installations rise

Strategies for the development of industry 4.0 and the formation of effective demand

The article is devoted to the development of industry 4.0 and the formation of effective demand. The authors are convinced that industry 4.0 is essentially a strategy of intelligent factories, i.e. the process of managing the production chain is carried out in real time using information and communication technologies, as well as the installation of robots. Effective demand for goods depends not only on the income of the buyer, but also on the prices of innovative products that are structurally formed by industry 4.0. It is proved that the main reason for the economic constraints of the development of industry 4.0 is the low effective demand for high-tech products. Therefore, the Russian industry must move to new types of economic activity and ensure the growth of productivity potential through the use of smart technologies, collaborative space, the formation of intelligent operational units and the digitalization process. Achieving sustainable long-term growth will depend on the ability to build a stronger domestic demand base and a balancing strategy: customer satisfaction and cost savings. The authors, based on international experience, prove the feasibility of forming a differentiated core, i.e. an effective combination of products and services formed by industry 4.0 while simultaneously integrating cyber-physical systems and the Internet of Things, as well as services. The analysis shows the huge growth potential of industry 4.0 as the revenue growth of leading international companies is estimated in the range of 8.1–13.6 % in the next five years. At the same time, an annual increase in customer spending on products is projected by 2.4 %. The conducted research shows that industry 4.0 allows for an annual increase in efficiency by an average of 3.3 % due to increased productivity, energy efficiency and resource efficiency. The authors are convinced that such a setup is impossible without the accumulation of capital and investments, which are the main factors contributing to economic growth and sustainable solvency of customers.

Development of the system of energy and resource saving during the operation of the gas pumping unit

The object of research is the fuel gas system of a gas turbine engine. The study of the use of secondary energy resources of the gas-pumping unit at the compressor station of the main pipeline has been carried out. The work of a gas turbine engine, including the work of the fuel gas system, is considered. The main drawback of the fuel gas system is revealed – ineffective use of excess gas pressure. An informational analysis of the options that eliminate the identified drawback is carried out. It is shown that in order to eliminate the disadvantage, it is advisable to use a turbo-expander at the compressor station to utilize the excess pressure of the fuel gas. It is also shown that the operation of a fuel gas turboexpander to drive an additional air compressor as part of a gas turbine engine is impractical. An expander-generator set with the generation of additional electricity at the compressor station is recommended for use. Modeling the operation of the utilization system made it possible to recommend constructive proposals for its improvement. A schematic diagram of a system for the complex utilization of excess pressure of fuel gas and heat of combustion products from the operation of a gas turbine engine is proposed. The system of complex utilization includes parts-generator unit, heat exchanger for cooling process gas and heat exchanger for firing gas. Regenerative heating of fuel gas up to 250 °С reduces energy consumption for heating it up to the ignition temperature. A model of a robot installation of the type GPU 16/56-1.44 (Ukraine) is carried out. It is determined that when a component engine of the J-59 (Ukraine) type with a shaft power of 16 MW operates, it is possible to additionally receive 102 kW of electricity and save 64 m3/h of fuel gas. It is revealed that the subcooling of the process gas does not play a significant role in reducing energy consumption during its transportation. It is recommended to use the process gas to heat the cold fuel gas stream downstream of the turboexpander to positive temperatures. The integrated utilization system is not a simple connection of an expander-generator set and two heat exchangers along the flow of the fuel gas. As a result of its operation, a significant reduction in the consumption of fuel gas and electricity is achieved. The disadvantages that hinder the implementation of a comprehensive disposal system are identified. This is the use of equipment for generating electricity at a compressor station. It is uncharacteristic for the operation of the station and requires additional qualifications in service. It is also required that the characteristics of industrial expander-generator sets correspond to the fuel gas consumption of a gas turbine engine.

A transfer-learning based energy consumption modeling method for industrial robots

Industrial robots have been widely utilized in factories to replace or help employees performing tasks such as handling, welding, and assembly. With the increasing breadth of installation and deployment of industrial robots, it is critical to predict and optimize their energy consumption in order to assure their environmentally friendly characteristics. While the data-driven modeling method based on multi-layer perception has been demonstrated to be a viable way for revealing quantitative relationships between operating parameters and energy consumption for industrial robots regardless of physical process or case-specific information, there are still some limitations in terms of prediction range, modeling efficiency, and sample size requirement. To accelerate model rebuilding and improve model accuracy without collecting a large number of samples simultaneously, this paper proposes a transfer-learning-based model creation method for energy consumption of industrial robots, where the associated operating parameters are analyzed, and structure adjustment strategies for multi-layer perception are planned for various industrial robot systems, then, schemes for the reuse of parameters in well-trained networks on source domain and the fine-tunning of multi-layer perception model are formulated to efficiently build the accurate energy consumption model on target domains. Experiments are conducted on two distinct robot systems, the Epson C4 and the Siasun SR10C, with nonidentical operating parameter structures and sample sizes. The results demonstrate that transfer learning models with fine-tuning strategy outperform previous data-driven modeling methods in terms of model accuracy and modeling efficiency in both of these situations.

Проект федерального закона «Об обороте роботов, их составных частей (модулей)»

Objective: to develop a draft of a federal law aimed at regulating relations arising in the field of use (application), acquisition, sale, development, production, testing, installation, maintenance, repair, disposal, accounting, storage, transportation, withdrawal, and destruction of robots and their components (modules), importing robots and their components (modules) to the Russian Federation and exporting them from the Russian Federation.Methods: the methodological basis of the draft federal law consists of general and specific scientific methods of scientific cognition, including analysis, synthesis, deduction, induction, classification, analogy and comparison. Results: the first draft law on robotics in the Russian Federation - the draft federal law “On the turnover of robots and their components (modules)” - has been proposed to the attention of representatives of law-making bodies, government agencies, scientific and business community, and public organizations.Scientific novelty: the draft law forms the legal basis and principles of legal regulation of relations in the sphere of turnover of robots and their components (modules), describes the types and classes of danger of robots, stipulates the restrictions imposed on robots and their components (modules), defines the general and special requirements for them, establishes the basis for state registration and accounting of entities engaged in the sphere of turnover of robots and their components (modules), introduces the criteria for acquiring the status of a subject, the procedure for publishing and maintaining the state cadastre of robot models and their components (modules), and the guarantees provided to legal entities and individual entrepreneurs - the subjects engaged in certain types of activities in the sphere of turnover of robots and their components (modules), and proposes the measures of their state support.Practical significance: the draft law is based on a systematic and comprehensive approach to the legal regulation of robotics and is aimed at creating a regulatory environment providing a favorable legal regime for the robotics development and for the implementation of economic activities related to its use.