robotic process automation

This study explores how Robotic Process Automation (RPA) can enhance efficiency, reduce costs, and minimize errors in the logistics supply chain of a shipbuilding company, with a focus on the naval industry. Unlike prior research, which examined RPA applications across various sectors, this study specifically targets its use in shipbuilding logistics, an industry that has not fully leveraged automation technologies. The study evaluates RPA's impact in three critical areas: optimizing productivity by reducing cycle times, lowering operational costs, and improving profitability through error reduction. The methodology employed a combination of qualitative and quantitative methods. Interviews with industry experts and case studies were used to gather qualitative insights, while quantitative analysis tracked key performance indicators such as cycle times, operational costs, and error rates. This comprehensive approach allowed for a well-rounded evaluation of RPA's impact. The results show that RPA can significantly lower operational costs by automating repetitive tasks like inventory management, order processing, and invoicing. By reducing the need for manual intervention, RPA streamlines these processes, resulting in faster cycle times and fewer errors. Additionally, the study highlights improvements in profitability, primarily driven by the reduction in errors throughout the supply chain. With fewer mistakes, financial losses are minimized, and decision-making becomes more accurate. This enhanced accuracy allows decisionmakers to allocate resources more effectively, improving overall service delivery. In conclusion, the implementation of RPA in shipbuilding logistics offers transformative potential by improving efficiency, cutting costs, and enhancing profitability. By automating repetitive tasks and reducing errors, RPA not only makes operations more cost-effective but also strengthens the company's competitiveness in the industry. This research provides a strong case for the broader adoption of RPA technologies in the naval sector, where automation has yet to be fully realized.

This study explores how Robotic Process Automation (RPA) can enhance efficiency, reduce costs, and minimize errors in the logistics supply chain of a shipbuilding company, with a focus on the naval industry. Unlike prior research, which examined RPA applications across various sectors, this study specifically targets its use in shipbuilding logistics, an industry that has not fully leveraged automation technologies. The study evaluates RPA’s impact in three critical areas: optimizing productivity by reducing cycle times, lowering operational costs, and improving profitability through error reduction. The methodology employed a combination of qualitative and quantitative methods. Interviews with industry experts and case studies were used to gather qualitative insights, while quantitative analysis tracked key performance indicators such as cycle times, operational costs, and error rates. This comprehensive approach allowed for a well-rounded evaluation of RPA’s impact. The results show that RPA can significantly lower operational costs by automating repetitive tasks like inventory management, order processing, and invoicing. By reducing the need for manual intervention, RPA streamlines these processes, resulting in faster cycle times and fewer errors. Additionally, the study highlights improvements in profitability, primarily driven by the reduction in errors throughout the supply chain. With fewer mistakes, financial losses are minimized, and decision- making becomes more accurate. This enhanced accuracy allows decisionmakers to allocate resources more effectively, improving overall service delivery. In conclusion, the implementation of RPA in shipbuilding logistics offers transformative potential by improving efficiency, cutting costs, and enhancing profitability. By automating repetitive tasks and reducing errors, RPA not only makes operations more cost-effective but also strengthens the company’s competitiveness in the industry. This research provides a strong case for the broader adoption of RPA technologies in the naval sector, where automation has yet to be fully realized.

This study explores how Robotic Process Automation (RPA) can enhance efficiency, reduce costs, and minimize errors in the logistics supply chain of a shipbuilding company, with a focus on the naval industry. Unlike prior research, which examined RPA applications across various sectors, this
study specifically targets its use in shipbuilding logistics, an industry that has not fully leveraged automation technologies. The study evaluates RPA’s impact in three critical areas: optimizing productivity by reducing cycle times, lowering operational costs, and improving profitability through error reduction. The methodology employed a combination of qualitative and quantitative methods. Interviews with industry experts and case studies were used to gather qualitative insights, while quantitative analysis tracked key performance indicators such as cycle times, operational costs, and error rates. This comprehensive approach allowed for a well-rounded evaluation of
RPA’s impact. The results show that RPA can significantly lower operational costs by automating repetitive tasks like inventory management, order processing, and invoicing. By reducing the need for manual intervention, RPA streamlines these processes, resulting in faster cycle times and fewer
errors. Additionally, the study highlights improvements in profitability, primarily driven by the reduction in errors throughout the supply chain. With fewer mistakes, financial losses are minimized, and decision- making becomes more accurate. This enhanced accuracy allows decisionmakers
to allocate resources more effectively, improving overall service delivery. In conclusion, the implementation of RPA in shipbuilding logistics offers transformative potential by improving efficiency, cutting costs, and enhancing profitability. By automating repetitive tasks and reducing
errors, RPA not only makes operations more cost-effective but also strengthens the company’s competitiveness in the industry. This research provides a strong case for the broader adoption of RPA technologies in the naval sector, where automation has yet to be fully realized.

This study explores how Robotic Process Automation (RPA) can enhance efficiency, reduce costs,
and minimize errors in the logistics supply chain of a shipbuilding company, with a focus on the
naval industry. Unlike prior research, which examined RPA applications across various sectors, this
study specifically targets its use in shipbuilding logistics, an industry that has not fully leveraged
automation technologies. The study evaluates RPA’s impact in three critical areas: optimizing
productivity by reducing cycle times, lowering operational costs, and improving profitability
through error reduction. The methodology employed a combination of qualitative and quantitative
methods. Interviews with industry experts and case studies were used to gather qualitative insights,
while quantitative analysis tracked key performance indicators such as cycle times, operational
costs, and error rates. This comprehensive approach allowed for a well-rounded evaluation of
RPA’s impact. The results show that RPA can significantly lower operational costs by automating
repetitive tasks like inventory management, order processing, and invoicing. By reducing the need
for manual intervention, RPA streamlines these processes, resulting in faster cycle times and fewer
errors. Additionally, the study highlights improvements in profitability, primarily driven by the
reduction in errors throughout the supply chain. With fewer mistakes, financial losses are
minimized, and decision- making becomes more accurate. This enhanced accuracy allows decisionmakers
to allocate resources more effectively, improving overall service delivery. In conclusion,
the implementation of RPA in shipbuilding logistics offers transformative potential by improving
efficiency, cutting costs, and enhancing profitability. By automating repetitive tasks and reducing
errors, RPA not only makes operations more cost-effective but also strengthens the company’s
competitiveness in the industry. This research provides a strong case for the broader adoption of
RPA technologies in the naval sector, where automation has yet to be fully realized.

Year 2018 Pages 55 Robotic Process Automation (RPA) is an emergent technology since 2015 and is considered to be the next significant phenomenon in business processes around the world, especially in Central and Eastern Europe. The Finnish Financial Group WallStreet and Finnish Consulting Group Eera have joined forces to become Korkia Group. Korkia has a background in consulting, investing and cooperate finance, focusing on RPA from 2016. To date, Korkia has accomplished many successful projects across Finland, Chile and UK. In 2018, Korkia's next destination is the Asian market in general and particularly the Vietnamese market. As RPA is considered extraordinary in Asia, Korkia has encountered miscellaneous challenges in Vietnam, specifically in negotiating with a Vietnamese bank, one of their first clients in the banking industry. Thus, RPA in Asia requires further analysis in order to gain a superior understanding and administration of it. This research proposes to give an overview of RPA in the financial industry and an analysis of RPA vendors in the current market. In terms of RPA vendors, the research indicates how each vendor governs the market and emphasizes which vendor might correspond to Korkia's need. Furthermore, this research exploits the software development life cycle (SDLC) Waterfall method to implement the RPA development for the Vietnamese bank, Korkia's client. Following all five stages from the SDLC Waterfall method, the thesis delivers a process description, a process analysis, a list of requirements, a process roadmap design and significantly process development based on REFramework. All the investigations discussed in the research, especially the process framework architecture design can be universally applied to more clients of Korkia in the near future.

Year 2018 Pages 55 Robotic Process Automation (RPA) is an emergent technology since 2015 and is considered to be the next significant phenomenon in business processes around the world, especially in Central and Eastern Europe. The Finnish Financial Group WallStreet and Finnish Consulting Group Eera have joined forces to become Korkia Group. Korkia has a background in consulting, investing and cooperate finance, focusing on RPA from 2016. To date, Korkia has accomplished many successful projects across Finland, Chile and UK. In 2018, Korkia's next destination is the Asian market in general and particularly the Vietnamese market. As RPA is considered extraordinary in Asia, Korkia has encountered miscellaneous challenges in Vietnam, specifically in negotiating with a Vietnamese bank, one of their first clients in the banking industry. Thus, RPA in Asia requires further analysis in order to gain a superior understanding and administration of it. This research proposes to give an overview of RPA in the financial industry and an analysis of RPA vendors in the current market. In terms of RPA vendors, the research indicates how each vendor governs the market and emphasizes which vendor might correspond to Korkia's need. Furthermore, this research exploits the software development life cycle (SDLC) Waterfall method to implement the RPA development for the Vietnamese bank, Korkia's client. Following all five stages from the SDLC Waterfall method, the thesis delivers a process description, a process analysis, a list of requirements, a process roadmap design and significantly process development based on REFramework. All the investigations discussed in the research, especially the process framework architecture design can be universally applied to more clients of Korkia in the near future.

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey-logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.

Robotic Process Automation (RPA) is a new favorite among IT leaders. It can be quickly deployed to automate repetitive tasks, and it saves organizations time and money. RPA bots handle sensitive data, moving it across systems from one process to another. If the data is not secured, it can be exposed and can cost organizations millions of dollars. Security design considerations are vital in RPA implementation for its success. Based on my recent Robotic Process Automation project implementation and research, able to put together the design strategies and best practices to implement security in RPA. In this paper described about RPA, types of Robots and major risks in RPA process and security design considerations in overall RPA process implementations in Organizations. Keywords: Robotic Process Aut

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey-logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.

The aim of the article is to identify drivers and limiters of the development of Business Process Management Systems (BPMS) from the point of view of the industry and the academia, and to formulate practical recommendations. Their identification is crucial in order to remove a considerable gap between the approach to knowledge-intensive business processes (kiBPs), which require dynamic management and are decisive with regard to the competitive position of the organization under the conditions of Industry 5.0, as well as the possibilities offered by ICT solution, and the current possibilities and needs of BPM practitioners. The authors applied a methodological approach based on a theoretical literature review and a review of practice through online structured expert interviews with key BPMS solution providers. According to the literature, the main drivers pertain to the enterprises’ efforts to reduce costs and improve their productivity and efficiency, develop technology, and enact c...

Robotic Process Automation (RPA) is a novel approach for immediate cost reduction and gaining operational efficiency. RPA tools can automate repeatable tasks, thus reducing the error rates and increasing overall process performance. Even more, RPA improves tne quality of the data (data completeness, data consistency/correctness, etc.). Although, being widely used in many organisations, RPA suffers from high time consumption allocated to the training of software robots (bots for short). Moreover, the models used for training are often inaccurate, which leads to increase of time spent on testing the bots. One of the possible solutions is to apply process mining in order to extract the information about the processes from UI logs such as clickstreams and keylogs, which can then be used to train the bots. However, traditional process discovery techniques are not suitable for the purpose of RPA, as they discover only control-flow perspective of the process and can not deal well with the UI logs, producing huge and complex models. The proposed research project aims at shifting process mining techniques from working on event logs to working on UI logs as well as developing multi-perspective automated discovery technique, which can than be applied to train the RPA bots.

The aim of the article is to identify drivers and limiters of the development of Business Process Management Systems (BPMS) from the point of view of the industry and the academia, and to formulate practical recommendations. Their identification is crucial in order to remove a considerable gap between the approach to knowledge-intensive business processes (kiBPs), which require dynamic management and are decisive with regard to the competitive position of the organization under the conditions of Industry 5.0, as well as the possibilities offered by ICT solution, and the current possibilities and needs of BPM practitioners. The authors applied a methodological approach based on a theoretical literature review and a review of practice through online structured expert interviews with key BPMS solution providers. According to the literature, the main drivers pertain to the enterprises’ efforts to reduce costs and improve their productivity and efficiency, develop technology, and enact c...

Es wird der „WI-Koffer“ vorgestellt, der analog zu existierenden Koffern aus den Bereichen Biologie, Chemie, Physik in beeindruckender Weise Menschen für das Fach Wirtschaftsinformatik (WI) aufmerksam machen soll. Ziel ist es, das Verständnis von Wirtschaftsinformatik anschaulich zu präsentieren und Studierende kurz- oder langfristig für diesen Studiengang und später Beruf zu gewinnen.

The need for companies to seek new techniques that generate productivity gains made them carry out the mapping of their processes using Business Process Management (BPM). Well-mapped processes make it possible to identify repetitive tasks, which can be automated using Robotic Process Automation (RPA), where a computer program mimics the actions of an employee. Furthermore, recent advances in Artificial Intelligence have brought new possibilities to RPA. The systematic review developed aims to raise information on Robotic Process Automation (RPA) integrated with Artificial Intelligence (AI) for autonomously automating work processes.

Robotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by executing scripts that encode sequences of fine-grained interactions with Web and desktop applications. Examples of clerical tasks include opening a file, selecting a field in a Web form or a cell in a spreadsheet, and copy-pasting data across fields or cells. Given that RPA can automate a wide range of routines, this raises the question of which routines should be automated in the first place. This paper presents a vision towards a family of techniques, termed robotic process mining (RPM), aimed at filling this gap. The core idea of RPM is that repetitive routines amenable for automation can be discovered from logs of interactions between workers and Web and desktop applications, also known as user interactions (UI) logs. The paper defines a set of basic concepts underpinning RPM and presents a pipeline of processing steps that would allow an RPM tool to gene...

Although the subtitle of this book is "A Guide to the Future of Work," this chapter will explore the challenges of automation and some solutions that have a legitimate claim to affect the present and the future of work. As we will show in this chapter, automation is not a series of distinct moments but a continuum of strategies and technologies that intend to increase levels of automation and improve the efficiency and effectiveness of business operations. Some of the strategies and technologies we discuss are already being deployed; others are only at the initial stages but will have an impact on who does what work in the future. Increasing automation has been a goal of information technology since the earliest attempts to use computing to handle vast amounts of data and repetitive tasks. If we look at some of the significant places on the continuum of automation, we can gain perspective. In the 1940s, Colossus, one of the earliest computers, automated the reading and comparison of vast amounts of encoded cipher text that helped humans to decrypt secret messages. At the next significant point, in the 1960s, along the continuum record keeping and particularly business ledgers led to a need to further

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey-logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Un verre de pipi tous les matins éloigne le médecin. Les pratiques informationnelles des internautes en lien avec l'urinothérapie

A smart contract is a computer protocol for creating or improving a contract which makes it possible to create valid transactions without intermediaries. The most important feature is security and speed, because this technology runs on a blockchain platform and its information will remain confidential. Despite these benefits, unfortunately, companies still use paper contracts. Knowledge-based companies can save time and money by implementing smart contracts with their customers in the form of robotic process automation and process management, and by reducing errors and risks in processes. Increase productivity in business. The purpose of this study was to present a smart contract model in knowledge-based companies based on Grounded Theory by Focusing on the robotic process automation strategies and process management using qualitative and quantitative paradigms. The analysis approach in this research is quantitative-qualitative. To collect data in the qualitative part, semi-structured interviews were used. In the quantitative part, the structural equation method was used. The sample size was calculated according to confirmatory factor analysis of 110 experts. Based on the data analysis, due to the abnormality of the data distribution, the partial least squares method was used with the help of Smart PLS software version 2.