Automation Technology Research Articles

The Application of Artificial Intelligence Technology in Mechanical Manufacturing and Automation

In order to achieve intelligent production and quality control, improve production efficiency and accuracy, the author proposes an application method of artificial intelligence technology in mechanical manufacturing and automation. The author aims to explore the specific application of artificial intelligence technology in the mechanical manufacturing industry and summarize the main advantages of automation technology. By analyzing these advantages, the aim is to provide targeted recommendations for future technological development. Meanwhile, the author aims to provide theoretical support for promoting the application of modern artificial intelligence technology and automation technology in the field of mechanical manufacturing. In the manufacturing process, intelligent production and quality control can be achieved, improving production efficiency and accuracy; In the field of automation, artificial intelligence technology can achieve intelligent control systems and autonomous decision-making, improving the flexibility and adaptability of production lines. Overall, the application of artificial intelligence technology has brought revolutionary changes to mechanical manufacturing, promoting the upgrading and development of the industry.

Drilling Automation Serves as Engine of Change for Risk Prevention Offshore

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 35137, “Drilling Automation: An Engine of Change for Risk Prevention Offshore,” by Brennan Goodkey, SPE, Andrew Fabo, and Francois Le Buhan, SLB, et al. The paper has not been peer reviewed. Copyright 2024 Offshore Technology Conference. _ This paper delves into the evolving landscape of drilling automation, emphasizing the imperative for these systems to go beyond novelty and deliver quantifiable financial value. The complete paper presents an examination of several offshore drilling operations that exemplify the successful implementation of a closed-loop drilling-automation solution and the positive effect these technologies can have on the bottom line. Introduction In the dynamic landscape of drilling technologies, the conventional discourse on rig mechanization, robotics, and drilling automation is no longer a new topic, having nearly a decade of active discussion, development, and deployment. However, these systems, despite their longstanding presence, are still working toward substantiating their anticipated value. To navigate this challenge successfully, a clear understanding of where and how exactly the deployed solution will deliver value is required. The criteria of success inevitably will vary based on the customer, region, and objective. One of the clearest examples is obvious in the dichotomy between the priorities of high-volume drilling in onshore operations compared with offshore drilling. While the overarching goal of automation remains consistent—maintain safety while maximizing production and minimizing operational expenditures—the path to delivery in these spaces looks quite different. Offshore drilling introduces a myriad of complexities and must prioritize not only efficiency but also risk reduction and the minimization of nonproductive time. The complete paper examines the collaborative journey of several oil and gas organizations to deploy and improve a drilling-automation system aimed at the priorities and challenges of offshore drilling. Definitions The authors offer the following definitions to delineate scope as they describe an integrated system that combines domain drilling automation, rig-floor mechanization, and directional-drilling automation into a cohesive and comprehensive solution: - Domain Drilling Automation—This refers to the process of leveraging sensor data to interpret downhole conditions and react with the appropriate domain response, mimicking an experienced driller’s expertise with high accuracy and precision. - Rig-Floor Mechanization—This is the implementation of automated technologies and robotic systems on the rig floor to limit manual human involvement in tasks situated within the hazardous red zone. - Directional-Drilling Automation—This term refers to the use of automated systems and technologies to control and navigate precisely the trajectory of a drilling borehole, enhancing accuracy and efficiency in achieving specific wellbore paths and target zones. - Planning Drilling Automation—The use of advanced technologies and automated systems during office-based well planning is leveraged to optimize resources, enabling precise and efficient decision-making for the entire drilling process. - Real-Time-Monitoring Drilling Automation—The use of advanced automation technologies can monitor and analyze drilling operations continuously in real time, providing instantaneous feedback and adjustments to optimize performance, efficiency, and safety.

A study on improving the international regulations for preventing collisions at sea (COLREG) for the introduction of maritime autonomous surface ships (MASS)

ABSTRACT Maritime Autonomous Surface Ships (MASS) have emerged with the advancements in information and communication technology (ICT), artificial intelligence (AI), and automation technology. MASS offers several advantages, such as reducing maritime accidents, increasing operational efficiency, lowering labour costs, and minimizing human errors. However, there are numerous challenges to address for the practical operation of MASS. In particular, the International Regulations for Preventing Collisions at Sea (COLREG), which governs the navigation rules for vessels, is a crucial international convention for the safety of navigation of MASS at sea. Therefore, this study examines the amendments to COLREG considering the characteristics of MASS. The International Maritime Organization (IMO) has defined various degrees of autonomy for MASS, ranging from full autonomy to remote control, and through the Regulatory Scoping Exercise (RSE), it has identified the need to amend certain provisions of COLREG to ensure the safe operation of MASS. Accordingly, this paper analyzes the results of the RSE conducted by IMO and proposes measures for improving COLREG to ensure the safe navigation of MASS.

Developing the Right Skills for Future Success in a Digital World

This article discusses how organizations can develop skills in their employees that cannot be replicated by artificial intelligence (AI) and automation technologies. It explores three categories of skills that are likely to withstand the rise of AI: creative and design skills, social and emotional skills, and adaptability and lifelong learning. Practical guidance is provided for cultivating these skills through targeted training and developing a learning culture. Case studies of companies in the technology, healthcare and manufacturing industries are examined. The role of leadership in prioritizing skills development is also covered. The article argues that by committing resources to systematically building these human skills sets and fostering continuous learning, companies can ensure their workforce is prepared for the impacts of technological change on work. Total commitment from organizational leaders is seen as key to inspiring a culture where people feel empowered to learn and improve.

IEEE Transactions on Automation Science and Engineering Information for Authors

IEEE Transactions on Automation Science and Engineering Information for Authors

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Artificial Intelligence Security for Autonomous Systems

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Artificial Intelligence Security for Autonomous Systems

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Artificial Intelligence Generated Content (AIGC) for Industrial Manufacturing

Call for Papers: IEEE Transactions on Automation Science and Engineering Special Issue on Artificial Intelligence Generated Content (AIGC) for Industrial Manufacturing

IEEE Transactions on Automation Science and Engineering Information for Authors

IEEE Transactions on Automation Science and Engineering Information for Authors

Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications

The continuous innovation of automation technology is expanding its application in the workplace, with wide-ranging implications for the economy and society. However, it is not yet clear how workplace automation changes people’s consumption behavior. This paper conducts an empirical analysis in this regard based on the Chinese General Social Survey. The main results are shown as follows: (1) One standard deviation increase in automation contributes to an average reduction of 7.073 % in family consumption. This finding is validated by conducting several robustness and endogeneity checks using various measures of automation and consumption, instrumental variable approach, placebo analysis, etc. (2) The mechanism is that automation decreases family income and work-related social capital, resulting in a decline in families’ socioeconomic status and increased financial precarities. In addition, financial uncertainties brought about by automation decrease people’s subjective well-being, expectations for future life and risk appetite, thus prompting them to lower consumption as a precautionary measure to prepare for potential risks caused by the technological change. (3) Automation has greater negative effects on hedonic and developmental consumption, which are about three times the impact on non-hedonic and basic living expenses respectively, thus leading to a downgrade in families’ consumption structure. In addition, its effect is more pronounced for families with lower economic status, having no houses and living in urban areas. This study also highlights the importance of demand-side policies in the application of automation technology by finding that better labor protection is needed to mitigate automation’s adverse consequences for family consumption. In the context of automation’s increasingly profound impact on the society, this research has important policy implications.

Economic growth by catch‐up nations in an age of neo‐protectionism and smart automation

AbstractThe global economic landscape has recently undergone significant changes, marked by the rise of neo‐protectionist policies and the emergence of a new techno‐economic paradigm driven by smart automation technologies such as artificial intelligence and robots. Advanced nations have increasingly used neo‐protectionism and smart automation technologies to address their structural problems. These policies will inevitably trigger changes in global supply chains and trade networks. This could undermine the competitive advantages of catch‐up nations, and an economic growth strategy centred on foreign direct investments. While these changes in the global economy may have negative impacts on the economic progress of some catch‐up countries, they may open new windows of opportunity for others. This article examines the challenges and opportunities for catch‐up nations in an era of neo‐protectionism and smart automation technologies.

Balancing plant safety and efficiency through innovative engineering practices in oil and gas operations

In the oil and gas industry, balancing plant safety with operational efficiency is a critical challenge that requires innovative engineering practices. This paper explores how advanced engineering techniques can enhance both safety and efficiency in oil and gas operations. By integrating cutting-edge technologies and methodologies, companies can achieve a harmonious balance between protecting personnel, equipment, and the environment, while also optimizing productivity and resource utilization. Key innovative engineering practices discussed include the implementation of real-time monitoring systems and predictive analytics to enhance safety and operational efficiency. Real-time monitoring, powered by Internet of Things (IoT) sensors, allows for continuous tracking of plant conditions, detecting anomalies before they escalate into significant issues. Predictive analytics, utilizing machine learning algorithms, further aids in forecasting potential failures and scheduling maintenance proactively, thereby minimizing downtime and operational disruptions. The paper also examines the role of risk-based approaches and safety management systems in improving plant safety. Techniques such as quantitative risk assessment (QRA) and safety integrity level (SIL) analysis are pivotal in identifying potential hazards and designing mitigation strategies. These practices ensure that safety measures are proportionate to the actual risk, avoiding over-engineering while addressing critical safety concerns. Moreover, the integration of automation and digital twin technology is discussed as a means to enhance both safety and efficiency. Automation reduces human error and improves precision in operations, while digital twins provide a virtual replica of physical assets, enabling simulation and optimization of plant operations in a risk-free environment. Case studies illustrate successful implementations of these practices, highlighting their impact on reducing incidents and improving operational performance. The paper concludes by emphasizing the need for ongoing innovation and collaboration between engineers, safety experts, and operational managers to continuously advance safety standards and operational efficiency in oil and gas operations.

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The prospects of the food and agro-food sector in the structure of the economic management system are related to global and national trends in the development of agriculture, food industry and effective management of these industries. The growing demand for environmentally friendly products forces companies and farmers to implement sustainable production methods. This includes reducing greenhouse gas emissions, using water and resources efficiently, and moving to organic agriculture. Environmental standards are becoming important in ensuring the competitiveness of products on the domestic and international markets. Automation and digital technologies are rapidly penetrating the agri-food sector. Precision farming technologies, artificial intelligence, drones and satellite systems allow for increased production efficiency, improved resource management and reduced costs.In addition, digital platforms help to optimize supply chains and improve interaction between market participants. There is an increasing focus on food safety due to increased regulation by governments and international organizations. This requires agri-food businesses to invest in quality control systems and meet international standards such as HACCP. The increase in the export of food and agricultural products is an important factor in the economic development of many countries. This requires diversification of sales markets, improvement of logistics infrastructure and adaptation to the requirements of foreign markets.In addition, supporting local producers through government subsidy programs can strengthen the domestic market. The concept of a closed-cycle economy involves minimizing waste and maximizing the use of resources at each stage of production. In the food sector, this may include using waste as raw material for fertilizer or energy production. Small and medium-sized businesses in the agri-food sector can play an important role in ensuring food security and sustainable development of rural areas. Government support programs, access to finance and educational programs can help strengthen this sector. Climate change directly affects the food sector, causing unpredictable weather conditions that can reduce harvests and increase the risk of production losses. Adapting to these changes requires the introduction of new technologies, genetically modified crops, and risk management programs. At the global level, more and more attention is being paid to food security - ensuring a stable food supply. This includes the development of the agro-industrial complex to reduce dependence on imports, increase food reserves, and develop infrastructure for storage and transportation

Thermal Cameras and Their Safety Implications for Pedestrian Protection: A Mixed Empirical and Simulation-Based Characterization

Multiple sensing technologies exist for advanced driver support and driving automation systems. Car manufacturers combine different solutions to increase the robustness and operational capabilities of driving automation technology perception systems. One sensing method that did not achieve high market penetration with respect to other solutions is the thermal camera. Thermal cameras can operate in low-light and high-contrast conditions as they do not need external sources of illumination. Instead, they are sensitive to the infrared radiation emitted by any surface above 0 K. Thus, thermal cameras can be a suitable candidate to compensate for the weaknesses of visible cameras. To establish the potential benefit of thermal cameras for pedestrian protection, this paper reports on an experiment using state-of-the-art thermal imaging sensors. The authors’ scientific effort includes a characterization of the infrared sensor capability to identify pedestrians when coupled with a detection algorithm and provides a simulation-based investigation of the potential safety benefits of thermal camera adoption. The analysis additionally includes a heuristic characterization of the detection capabilities of a passenger car equipped with visible cameras to provide a baseline comparison. Ultimately, the thermal sensors return noteworthy detection capability that could lead to a potentially significant improvement in road safety on rural roads provided that the sensor has sufficient resolution.

Advanced test automation techniques for DevOps: Bridging the gap between test-driven development and continuous deployment in agile environments

As software development continues to change, it becomes more important to incorporate modern test automation approaches in DevOps to support efficient deployment. This work investigates TDD and CD in Agile to critically appraise advanced automation technologies and practices to fill existing deficits. This research demonstrates that the brighter Test Automation Framework approaches could improve code quality and deployment time, along with the culture of embracing best practices. The results can help practitioners who want to make their DevOps practices even more efficient and focused on quickly delivering high-quality products.

Reducing the risk of social engineering attacks using SOAR measures in a real world environment: A case study

The global cost of successful cyberattacks is increasing annually, with there being a shift towards social engineering threats in recent years. Cybercriminals are increasingly targeting humans rather than technical systems, recognizing data as a critical resource, especially in the finance industry where breaches can lead to substantial losses and reputational damage. The present case study proposes measures to reduce human susceptibility to social engineering attacks, leveraging SOAR (Security Automation, Orchestration, and Response) technology for incident response automation. The study covers various issues in cybersecurity, SOAR, and social engineering, through analyzing interviews with expert practitioners in the field, addressing cybersecurity skills shortages and current cyber threats. Four social engineering vignettes were developed, representing real threats, along with specific SOAR measures implemented using Microsoft Sentinel. These measures were simulated to demonstrate their effectiveness by reducing the employee's vulnerability to social engineering attacks. The risk of social engineering attacks was successfully reduced by implementing a responsive approach through the developed SOAR measures. Some of the measures reduced the risk by locking user accounts or forcing password changes after a detected cyber incident while another measure was developed for awareness enhancements. Given the current shortage of cybersecurity professionals, technologies like SOAR are becoming increasingly relevant for security teams. However, SOAR alone cannot address all challenges posed by social engineering and should be viewed as a complementary measure rather than a standalone solution.

Application of artificial intelligence in business management and financial market forecasting

In today's business world, artificial intelligence as a new technology has provided dynamic and flexible capabilities in organizational decision-making processes, considering that organizational decision-making often faces challenges due to the complexity and multiplicity of factors affecting it. The application of artificial intelligence as A powerful tool can be effective in improving the organizational decision-making process and improving the performance of organizational managers. Artificial intelligence is one of the popular and widely used new sciences in almost all aspects of life and can do things faster and more accurately. The numerous advantages of artificial intelligence and its wide applications today are not hidden from anyone. Financial services companies are constantly looking for ways to gain superiority in the capital market and surpass their competitors. To do this, companies are moving away from old systems and models They adopt a more agile business that includes artificial intelligence techniques in capital markets, artificial intelligence in financial markets and machine learning (ML). In capital markets, companies use artificial intelligence and ML projects in coordination with RPA robotic process automation technologies to meet customer requests, speed up financial market analysis, and more accurately identify risk in the business process.

Typification of Projects for the Transition to Cloud Services

Introduction. Digital solutions make the operation of the company clearer, reduce staff costs, and provide data security. Various aspects of automation, digitalization and cloud technologies are described in the literature. The question is raised about the quality of the methodological basis for such transformations. Global and narrow technical approaches are presented. As a rule, materials are presented from the perspective of experts in the implementation of digital technologies. In this paper, for the first time, the author's scheme is proposed that can allow not only providers, but also their customers to navigate the upcoming transition to the cloud. The latter will receive systematic information on how to select a contractor and the most economically feasible option of cooperation.Materials and Methods. The information model was based on the semantic network as a system of nodes, their characteristics and connections. Management of the cloud migration project and the migration itself were visualized. The contraction practice between providers and their customers was summarized. The specifics of the tasks of such projects were taken into account. The part of the subject area related to the implementation of a cloud service is algorithmic — a step-by-step transition to the cloud, a generalized scheme of the process taking into account the hierarchy of elements are presented.Results. For the first time, a method of self-preparation of a company for the implementation of cloud solutions is proposed. The algorithm systematizes the cloud migration processes. The activities related to goal setting, audit, selection of cloud environment and services, calculation of the economic efficiency of the project, planning and implementation of migration, technical support and scaling of processes are described. The possibilities of determining the economic feasibility of measures for the transition to the cloud are shown. The costs of equipment, data storage and processing, software licenses, salaries, information security, etc., are taken into account. The amount received is compared to the providers' offers. For the final decision, the costs of infrastructure support are taken into account — by the customer or the outsourcer. The best option is selected. As a result, the customer gets the opportunity to work with better profitability and scale the project. Feedback is provided, and processes are adjusted, starting with IT reaudit.Discussion and Conclusion. The proposed solution will give the customer's management a system view of the execution sequence when migrating to the cloud, the issues and tasks to discuss with a potential outsourcer. Providers can use the algorithm to typify and unify projects, which can eventually simplify the coordination of the list of services and the migration procedure with customers. In this way, the parties can free up significant resources in terms of time, labor and other costs. In addition, customers and providers can partially use the described semantic network to develop not only the organizational, but also the technical aspect of the project.

PEPR DIADEM: Priority equipment and research program on the development of innovative materials using artificial intelligence

IntroductionThe quest to develop efficient, sustainable materials from non-critical, non-toxic resources is one of today's most formidable challenges in the current context of energy, transport, digital or healthcare transitions. In response, France launched the pioneering Priority Equipment and Research Program (PEPR) DIADEM in 2022. This innovative initiative, focused on DIscovery Acceleration for the Deployment of Emerging Materials (DIADEM), leverages Artificial Intelligence (AI) to accelerate the innovation chain from conception to realization, revolutionizing Materials Science sustainably. With a strategic emphasis on scientific synergy, PEPR DIADEM aims to expedite the discovery and development of novel materials essential for contemporary and future societal challenges. To achieve this, the program seeks to catalyze breakthroughs in areas ranging from energy efficiency to transportation, digitalization, and healthcare, covering a broad spectrum of materials from metallic alloys to functional nanostructures. Aligned with the Green Deal framework's ambitious targets, PEPR DIADEM addresses the urgent need for accelerated sustainable materials research. By utilizing cutting-edge technologies like rapid synthesis and characterization tools, automation, digital simulations, data management, AI, additive manufacturing, and thin film engineering, the program is set to significantly reshape the materials science landscape. As PEPR DIADEM embarks on its journey of innovation, it not only advances scientific knowledge but also holds the promise of addressing current global challenges and paving the way for a more sustainable and prosperous future.

Study on the Model of Integrated Education of Vocational Electrical Automation Technology “Post-course Competition Certificate” Under the Integration of School and Enterprise

Based on the perspective of university-enterprise integration, this paper first analyzes the post ability demand of electrical automation technology and reconstructs the course system and multi-dimensional evaluation system of the deep integration of post, competition, certificate and creation course. Then, according to the curriculum settings, from the aspects of teaching resource allocation, school-enterprise cooperation mechanism reform, teachers, teaching methods, and teaching materials reform, enable the implementation of “post-course competition certificate creation” integrated education mode, effectively improve the quality of talent training and better serve the new quality productivity.

Ironies of automation and their implications for public service automation

Automation of public service provision has gained renewed attention as emerging technologies are said to enable automation of tasks that were previously seen as requiring human involvement. However, the merits of these automation technologies are often exaggerated. More knowledge is needed on public service automation, and much can be learned from adjacent research fields studying human-automation interaction. To lead by example, this work applies Bainbridge's (1983) concept of ironies of automation. The purpose is to (1) present ironies of automation, (2) explicate how these ironies can come into play when implementing automated systems in the public service context, and (3) outline implications that follow for public service automation. This is achieved by relating ironies of automation to contemporary studies on Robotic Process Automation (RPA) developments in Swedish local government. The analysis results in five ironies and a set of implications for public service automation. The ironies and implications for public service automation direct attention to key challenges that must be acknowledged in future automation implementations and show that further investigations and theoretical developments are needed on e.g., problems introduced by automation; tasks, roles, and responsibilities that follow on automation; how to design the interface between humans and automated systems in a way that facilitates monitoring, take-over, and maintenance; and, tools and methods for assessing the impact and quality of automated systems. This paper thus provides a foundation for future empirical investigations and further theoretical development on public service automation.