Robotic Process Research Articles

Best practices for seamless integration of Robotic Process Automation (RPA) and cloud technologies

Transformative technology such as Robotic Process Automation (RPA) and Cloud Integration is the platform to achieve streamlining of operations, enhance employee productivity, and drive innovation for your business. While RPA automates repetitive, rule based work, cloud computing is the scalable, flexible and decentralized infrastructure for storing and processing of data, and collaboration. With RPA integrated with cloud platforms, organizations gain several advantages including accessibility, low cost and real time collaboration. Choosing the right cloud provider that supports RPA workloads, ensuring data flow seamlessly between RPA bots and cloud systems, and using cloud based RPA tools that can scale and that add flexibility, are the best practices for RPA and Cloud integration. It is also important to enforce robust security protocols, data governance as well as comply with risks. Integration is successful when RPA links with cloud native apps and services with as little disruption to work as possible and as much automation effect as possible. It is therefore recommended that performance monitoring, testing and continuous improvement of automation process should be given priority. Through the implementation of these best practices, organizations can attain near full potential RPA and cloud integration for operation efficiency, better customer experience and faster digital transformation. In this paper we explore the key strategies, challenges and solutions to ensure success with the integration of RPA into cloud technologies to help businesses looking to optimize the use of automation and cloud capabilities in unison.

Leveraging technology in internal audit processes for streamlined management and risk oversight

The integration of advanced technologies into internal audit processes has revolutionized organizational management and risk oversight, enabling streamlined, data-driven decision-making. As businesses face increasingly complex regulatory environments and operational risks, traditional audit methods often struggle to keep pace. This paper explores the transformative role of emerging technologies, including data analytics, artificial intelligence (AI), robotic process automation (RPA), and blockchain, in enhancing internal audit efficiency, accuracy, and transparency. By automating repetitive tasks, RPA reduces audit cycle times and minimizes human errors, allowing auditors to focus on value-adding activities. AI and machine learning algorithms enable predictive risk analysis, anomaly detection, and real-time monitoring, strengthening an organization’s ability to identify and mitigate risks proactively. Additionally, data analytics tools facilitate comprehensive assessments of large datasets, uncovering patterns and insights that would otherwise go undetected in manual audits. The paper also examines the role of blockchain technology in fostering transparency and accountability through secure, tamper-proof audit trails. Despite the benefits, the adoption of these technologies presents challenges, including integration costs, skill gaps, and data privacy concerns. Addressing these challenges requires strategic investment, workforce upskilling, and collaboration between audit professionals and IT specialists. By leveraging technology, internal audit functions can evolve into proactive, agile frameworks that align with organizational goals, providing robust risk oversight and contributing to long-term sustainability.

Analysis of innovative approaches to technology-enabled public finance management

The purpose of the article to analyze the role of technological innovations in improving public financial management, identify barriers to their implementation and offer recommendations for the formation of an effective organizational and legal framework. The author identifies various types of innovations and explains their importance in ensuring the efficiency of public funds management. However, the author pays the main attention to technological innovations. Thus, electronic public procurement platforms, big data analytics, artificial intelligence and robotic process automation were highlighted. The article demonstrates their impact on the transparency, efficiency and accountability of the use of public resources. In addition, the article analyzes specific examples of countries that are already applying relevant innovations and qualitative statistical indicators of their importance for the budget sector. By analyzing successful foreign cases, the most effective models of integrating innovations into public institutions were identified. The author's approach in this paper involves not only describing and analyzing individual successful cases, but also identifying organizational and legal barriers. Author also finds specific ways to overcome negative elements. The proposed recommendations include a roadmap, staff training and regulatory framework improvement. Taking into account the specifics of legislative systems and the capabilities of the national economy, they can be adapted to different countries and regions. In conclusion, the article substantiates that the systematic implementation of innovative technologies can not only increase the efficiency of budget processes and reduce corruption risks, but also contribute to the formation of a new management culture focused on transparency and effectiveness.

FORMATION OF AN ENTERPRISE MANAGEMENT SYSTEM IN THE CONDITIONS OF THE DIGITAL ECONOMY

The purpose of the article is to study the features of the formation of an enterprise management system in the conditions of digital transformation of the economy. Attention is focused on the importance of building an enterprise management system in the conditions of digitalization. Key changes that the transition to a digital economy leads to are identified. Factors that contribute to the development of the digital economy are highlighted (development of the information and communication technologies industry, strong educational institutions, competitiveness of innovations). The stages of digital transformation that an enterprise must go through are characterized. The conceptual principles of the enterprise management system in the conditions of digital transformation of the economy are defined. The goal of enterprise management in the conditions of digital economy is established. Management tasks are defined, the implementation of which ensures the achievement of the goal. The principles (innovation, adaptability, digitalization, automation, customer-orientation, flexibility, transparency, accountability) and functions (planning, organization, motivation, control, communicative, adaptive) of management in the conditions of digital transformation of the economy are revealed. The principle of omnichannel is proposed for use, which involves the integration of various communication channels, which will ensure the efficiency and quality of management decisions. The list of functions is supplemented with communicative and adaptive functions. Management methods in the digital economy are characterized, which are based on the use of digital technologies and allow for the development of effective management solutions (management method based on digital transformations, data-driven management method, management method based on the use of Agille principles, management using cloud technologies, management using robotics and process automation (Robotic Process Automation (RPA)), management based on multichannel, management using digital platforms). The main directions of development of the management system in the context of digitalization are determined.

Reducing administration? Examining the alignment of robotic process automation and social assistance in Swedish Personal Social Services

ABSTRACT In line with the global trend towards digitalization, digital automation has become a politically endorsed strategy to enhance efficiency and transparency in public service delivery. One such example is the adoption of Robotic Process Automation (RPA) in the context of social assistance (SA) in Sweden. While SA is a municipally organized means-tested subsidy for the most financially vulnerable, RPA functions as highly structured software executing administrative tasks based on predetermined rules. Employing a sociomaterial perspective, this article analyses group interviews conducted in four Swedish municipalities, to explore if and how RPA adoption configures the dynamics of SA casework administration and practice. Findings suggest that RPA adoption does not inherently lead to expected all-encompassing enhancements of faster and fairer eligibility determinations as well as a more client-centric approach in SA casework. Instead, the instrumentalist approach of leveraging digital tools to achieve specific outcomes, combined with the task delineation required by RPA, appears incongruent with the nature of SA casework practice. As caseworkers attest to organizational adjustments and a more instrumental approach towards clients’ situations alongside RPA adoption, this study underscores the inadequacy of the rationalist notion of segmenting SA casework in order to achieve efficiency in casework that, by law, should be based on individual judgements by professional caseworkers.

Finance Receipting using Robotic Process Automation

Finance Receipting using Robotic Process Automation

The use of artificial intelligence for automatic analysis and reporting of software defects.

The COVID-19 pandemic marked a before and after in the business world, causing a growing demand for applications that streamline operations, reduce delivery times and costs, and improve the quality of products. In this context, artificial intelligence (AI) has taken a relevant role in improving these processes, since it incorporates mathematical models that allow analyzing the logical structure of the systems to detect and reduce errors or failures in real-time. This study aimed to determine the most relevant aspects to be considered for detecting software defects using AI. The methodology used was qualitative, with an exploratory, descriptive, and non-experimental approach. The technique involved a documentary review of 79 bibliometric references. The most relevant finding was the use of regression testing techniques and automated log files, in machine learning (ML) and robotic process automation (RPA) environments. These techniques help reduce the time required to identify failures, thereby enhancing efficiency and effectiveness in the lifecycle of applications. In conclusion, companies that incorporate AI algorithms will be able to include an agile model in their lifecycle, as they will reduce the rate of failures, errors, and breakdowns allowing cost savings, and ensuring quality.

Utilizing Robotic Process Automation and Artificial Intelligence in Auditing to Mitigate Audit Risks

Automating repetitive tasks significantly increases the efficiency of operations by identifying repetitive tasks, then choosing the appropriate tools for automation, designing successful workflows, testing, iteration, monitoring the performance of operations continuously, and making the necessary adjustments, which helps auditors accomplish their mission. This research aims to highlight the urgent need to develop the skills of accountants and auditors to maintain alignment with the swift advancements in digital technology in the accounting field to reduce fraud risks and protect stakeholders. The study relied on the applied aspect of 157 questionnaires distributed to a sample of auditors working in auditing firms and Federal Financial Supervision Bureau auditors. We used a five-point Likert scale to answer the questions on the questionnaire and the SPSS V.25 statistical package to look at the data and test our research hypotheses. We used Pearson correlation, simple regression, the coefficient of determination and interpretation R2, and the standard coefficient of regression B. Our research showed that using robotic process automation and artificial intelligence in auditing would make audited financial statements more reliable. Adding auditors' skills, artificial intelligence, and process automation will also significantly mitigate inherent control and detection risks. Furthermore, enhancing the quality of auditing

Prospects of additive technologies in construction: expectations and reality

Introduction. Additive technologies in construction are currently considered to be technologies for emerging future markets, i. e. technological solutions that have not yet been formed but are potentially capable of providing a significant volume of consumption in the future. The aim of this paper is to analyse the 20-year period of science and practice development in the field of additive technologies in construction, to identify the main achievements and unresolved problems, and to outline the prospects for development. The potential of additive technologies in construction is associated with the possibility of creating bionic design of construction objects, which implies a combination of freeform and organised internal space of object structures, in which the mass of material is located only along the lines of load. This can lead to a radical reduction of material mass in the volume of the structure and change the principles of design and construction. The practice of application of construction additive technologies in modern construction. On the basis of the analysis of typical implemented projects it is shown that its introduction so far is limited to low-rise housing construction, creation of objects of functional-decorative and special purpose. At present, the robotic process of 3D printing is used only for the construction of the shell of vertical structures of building objects; other structures of these objects are made by the traditional technology of concrete casting, which determines their high cost. Unresolved problems and factors hindering the introduction of construction additive technologies consist in the lack of design methods, regulatory framework, effective universal technological complexes, sufficient nomenclature of mixtures for printing. Approaches to solving these problems are presented. Development prospects. The rational directions of introduction of building additive technologies at the present technological level are: construction of small building objects, especially in territories with severe climatic conditions, where there is no developed base of building industry; introduction of building additive technologies in industrial house-building for finishing of building facades and printing of elements of decorative infrastructure of residential complexes.

Multi-Agent Decisional System Based on Emotion Recognition in Speech for Controlling Exceptional Situations in Robotic Production Processes

The paper proposes a multi-agent decision-making system designed to manage exceptional situations in robotic production processes by recognizing human emotions in speech. The importance of human-robot collaboration was highlighted, with a focus on automatically detecting human operators’ emotions as potential warning signals for technical or safety issues. This approach contributes to improving the safety and efficiency of the production process by enabling agents to quickly adjust system settings according to the emotions expressed by operators in speech, for example, in cases of stress or frustration. The paper details the structural and functional scheme of the system. It presents the mathematical model and shows how deep learning algorithms implemented through hybrid neural networks (CNN and RNN) enable the system to accurately recognize and classify emotional patterns in an audio signal. The technology uses Python libraries such as TensorFlow and Keras to analyze acoustic characteristics such as tone, intensity, rhythm, and timbre of the voice. These parameters are used to identify emotions and initiate proactive or automatic corrective actions in robotic processes. Thus, the multi-agent system provides an excellent level of human-robot interaction, optimizing both productivity and safety in complex and dynamic industrial environments.

Optimization of Application Testing in Financial Companies Using Robotic Process Automation (RPA)

In the rapidly evolving era of digitalization, financial companies face the challenge of enhancing efficiency and accuracy in application testing processes. Manual testing, which is time-consuming and prone to human error, is a major obstacle in ensuring the reliability of applications. This study aims to optimize the application testing process in financial companies by implementing Robotic Process Automation (RPA) as a tool for automated testing. The methodology used includes the analysis of testing requirements, selection of the appropriate RPA tools, and the implementation and performance evaluation of the RPA system. The results of the study indicate that the implementation of RPA can reduce testing time and improve error detection accuracy. For the partner application, there are a total of 6 test sets, 31 test cases, 31 scenarios, and 112 test steps. Meanwhile, for the sales application, 6 test sets, 29 test cases, 29 scenarios, and 115 test steps were identified. Using RPA, the duration of manual testing, which was previously limited to 8 hours per day, significantly increased to 24 hours per day, allowing continuous testing without human intervention. The number of test cases handled increased from 7 cases per day to 63 cases per day, indicating a significant improvement in efficiency. The number of test steps also increased from 328 steps per day to 2952 steps per day. The implementation of RPA also positively impacted accuracy by reducing human errors that frequently occur in manual testing. Overall, this study demonstrates that the application of RPA in testing applications at AMF Finance significantly improves the capacity, efficiency, and accuracy of the application testing process.

Developing standard criteria for robotic process automation candidate process selection

<p>Robotic process automation (RPA) is a cutting-edge technology that provides software robots to repeat and mimic the repeatable tasks that a human user earlier performed. The use of software robots is encouraging because of their cost efficiency and easy implementation. Selecting and prioritizing a candidate process for automation is always challenging as all the business processes in an organization are not equally suitable for RPA implementation. Various studies have highlighted several criteria found in the literature for determining, prioritising, and selecting a business process for RPA. Nevertheless, there are no set standards for evaluating and analyzing a certain process or its tasks to determine whether they may be automated to use RPA. This paper aims to develop standard criteria and propose a consistent model to select and prioritize candidate process for RPA projects. To assess these criteria's applicability in the context of RPA, surveys among subject matter experts (SMEs) are used to validate them. Principal component analysis (PCA) and correlation are used to identify the top 20 criteria. Naïve Bayes algorithm is applied on the collected data for decision-making. The developed multi-criteria model exhibits strong precision and recall measures, with training and validation accuracy of 96% and 90%, respectively.</p>

Organizational Aspects of Managing the Robotic Process Automation (RPA) Department: The Example of a Polish SAP Service Provider

The technological development of enterprises is one of the key challenges faced by modern entities. Enterprises are looking for more and more easily adoptable low-code technologies, an example of which is RPA. The success of implementations depends to a large extent on the professional competences and knowledge of entities implementing RPA projects. The literature on the subject contains many studies on the RPA technology itself or its applications in enterprises. However, there are few studies on the management of organizations focused on implementing RPA projects. The article fills this gap. The aim of the article is to analyze and evaluate the management of the RPA department on the example of a company providing SAP and RPA services. The article uses literature analysis and a case study of a company providing SAP and RPA services operating on the Polish market as a research method. One of the key conclusions from the conducted research was that there is little complexity in the integration of the use elements of the 7S model in the RPA department,and the implementation of soft elements of the 7S model is important to create market advantage. Surprisingly difficulties were identified in adapting the hard elements of the model to the requirements of the parent company, related to poor understanding of the characteristics of the RPA team’s operation in the post-transactional integration process.

Exploring the Research Landscape of Business Applications of Robotic Process Automation Through Bibliometric Analysis

The field of business process optimization and automation has seen the emergence of robotic process automation (RPA) as a disruptive technology. This research aims to give a systematic bibliometric analysis of the research ecosystem of robotic process automation in business to identify trends, patterns, and developments in this quickly developing area. Bibliometric methodologies, such as co-authorship analysis, keyword analysis, citation patterns, and publishing trends are performed in this work. Research papers from Scopus scientific databases are incorporated into the analysis through the identification of key writers, organizations, and nations that have made a substantial contribution to the growth of RPA literature. The report also explores the temporal evolution of RPA research, highlighting the development of research areas over time and identifying pockets of active research as well as prospective paradigm shifts. The research reveals key publications that have significantly influenced the course of RPA research by looking at citation networks. The results of this bibliometric analysis enable scholars, practitioners, and policymakers to develop a more detailed grasp of the RPA research landscape in business. This study provides a roadmap for future research directions in robotic process automation by identifying research gaps and emerging trends in business management.

Faculty Assistant Bot-automation of administrative activities using robotic process automation

Faculty Assistant Bot-automation of administrative activities using robotic process automation

Automation in financial reporting: A conceptual framework for efficiency and accuracy in U.S. corporations

This paper reviews the role of automation in financial reporting within U.S. corporations, focusing on how advanced technologies such as artificial intelligence (AI), robotic process automation (RPA), and cloud-based systems are transforming traditional financial processes. By automating routine tasks, these technologies offer significant improvements in efficiency, accuracy, and scalability. The paper highlights key challenges, including system integration, data security, and regulatory compliance, while also discussing strategies for successful implementation, such as establishing strong technological infrastructures, ensuring data integrity, and fostering organizational readiness. Best practices for maximizing the benefits of automation are explored, emphasizing the need for continuous improvement and alignment with business objectives. Recommendations are provided for corporations looking to adopt or enhance automation in financial reporting, with a focus on strategic planning, employee training, and maintaining compliance with financial regulations.

Unlocking the Potential of Robotic Process Automation for Digital Transformation in Logistics and Supply Chain Management

Digital transformation (DT) and automation technologies have significantly impacted logistics and supply chain management (LSCM), enhancing business performance. Efforts to automate processes alongside machine and robotic automation aim to improve reliability, consistency, efficiency, and cost-effectiveness. While existing research has explored specific aspects of DT and robotic process automation (RPA), the deployment and implementation of RPA as a service (RPAaaS) in LSCM are under-explored. This study focuses on RPA in LSCM and aims to improve organisational processes associated with DT. A systematic review identifies five knowledge clusters regarding RPA deployment for DT in LSCM. Real-life RPA implementation cases in a third-party logistics company highlight challenges and opportunities related to RPA deployment. Insights on the timing and choice of the RPAaaS platform to facilitate DT in enterprises are discussed. This paper provides extensive theoretical insights into RPA for DT in LSCM and offers practical guidance for streamlined implementation.

Optimizing Renewable Strategies for Emission Reduction Through Robotic Process Automation in Smart Grid Management

The integration of renewable energy into Intelligent Distribution Networks (IDNs) is challenged by the inherent variability and fluctuations in energy supply, particularly with photovoltaic (PV) generation as the primary form of distributed generation (DG). However, managing the fluctuations and variability in renewable energy supply presents significant challenges. To address these complexities, it is vital to optimally coordinate flexible resources from source–network–storage–load (SNSL) in a manner that aligns with cross-sectoral emission reduction strategies while enhancing grid stability and efficiency. This paper addresses these challenges by proposing a strategy that optimizes the coordination of PV-based DG, storage, and load resources through Robotic Process Automation (RPA) to enhance grid stability and support emissions reduction. We use a two-layer dispatching framework: the lower-layer model, formulated as a quadratic programming problem, maximizes PV utilization for individual users, while the upper-layer model, based on a second-order cone relaxation approach, manages the overall IDN to minimize operational costs. The iterative solution leverages tie-line power flow as boundary information to ensure convergence across the network. Validated on an enhanced IEEE 33-bus system, the approach demonstrates a 62% increase in PV-based DG consumption and a 25% reduction in active power losses, highlighting its potential to improve grid efficiency and contribute to emission reduction goals.

Gait planning of a 4–5R rolling mechanism based on the planar 6R single-loop chain

Abstract. This paper proposes a 4–5R rolling mechanism based on the spatial extension design of a planar 6R single-loop chain. By analyzing the locomotion of the planar equivalent form, a modular gait theory integrating different modes of gait with high efficiency, low energy consumption, and high speed is established. A unified kinematic strategy expression, encapsulated in the form of the gait period table, is tailored for the kinematic chain's gait on the flat terrain. A contrast gait is conducted to ascertain its velocity parameters and volatility of the center of mass (CM). By optimizing the corresponding indicators, two distinct gait patterns are achieved: a faster speed gait that prioritizes increased speed and a steady gait that emphasizes stability with reduced CM volatility. Drawing from the mobility analysis and simulation outcomes of the planar 6R single-loop kinematic chain, a theory of locomotion for a closed-chain linkage mechanism in space is proposed. A locomotion strategy on the flat ground is derived, and a unified evaluation index is proposed. Finally, the feasibility of the two working modes is verified using a physical prototype. The theoretical work in this paper simplifies the design process of closed-chain linkage robots and improves the mobility performance of closed-chain linkage robots. It lays the foundation for researching new types of closed-chain linkage robots.

Handwritten Data Extraction Using OpenAI ChatGPT4o and Robotic Process Automation.

This paper proposes to create an Robotic Process Automation style application that can digitalize and extract data from handwritten medical forms. The RPA robot uses OpenAI ChatGPT4o model to extract handwritten medical data and transform it into typed data. The handwritten data is transcribed correctly at a rate of 100%. The data interpretation is accomplished by the UiPath machine learning API. By creating new nonstandard form templates and associated taxonomies the system can be scaled as desired. After the data extraction process the saved data can be sent to a database, spreadsheet. The access to this medical data is restricted to the physicians and medical nurses employed at the medical facility.