TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko T1 - Der Industrie-4.0-Leitfaden für kleine und mittlere Unternehmen BT - Die dritte Richtlinie: Intelligente Logistik und Hardware JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb UR - https://doi.org/10.3139/104.112259 Y1 - 2020 UR - https://doi.org/10.3139/104.112259 SN - 2511-0896 VL - 115 IS - 4 SP - 262 EP - 265 PB - Hanser CY - München ER - TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko T1 - The Five Dimensions of Digital Technology Assessment with the Focus on Robotic Process Automation (RPA) JF - Tehnički glasnik N2 - In Technology Management, the assessment of new digital technologies is a challenging process. Most assessments are focusing on cost & benefit. These approaches often fail because main points are neglected. In this paper, the holistic approach of "The Five Dimensions of Digital Technology Assessment" will be described with the example of RPA (Robotic Process Automation). RPA is one of the most promising technologies to save data processing efforts in the office. The Five Dimensions of RPA Assessment is performed by assessing the benefits, technology readiness, usability, company readiness, and the costs that burden the company in the RPA implementation. UR - https://doi.org/10.31803/tg-20210429105337 KW - assessment KW - benefit KW - company readiness KW - cost KW - RPA (Robotic Process Automation) KW - technology readiness KW - usability Y1 - 2021 UR - https://doi.org/10.31803/tg-20210429105337 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10395 SN - 1848-5588 VL - 15 IS - 2 SP - 267 EP - 274 PB - University North CY - Koprivnica ER - TY - JOUR A1 - Axmann, Bernhard A1 - Hamberger, Werner A1 - Liegl, Thomas T1 - Digitalisierung der Fabrik – Datenqualität als Schlüssel zum Erfolg BT - Welchen Wert haben Daten? JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb T2 - Digitalization of the Factory – Data Quality as the Key to Success UR - https://doi.org/10.3139/104.112083 Y1 - 2019 UR - https://doi.org/10.3139/104.112083 SN - 2511-0896 VL - 114 IS - 5 SP - 302 EP - 305 PB - Hanser CY - München ER - TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko T1 - Der Industrie-4.0-Leitfaden für kleine und mittlere Unternehmen BT - Die erste Richtlinie: Daten BT - The First Readiness Pillar: Data JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb T2 - The Guideline of Industry 4.0 for SMEs UR - https://doi.org/10.3139/104.112229 Y1 - 2020 UR - https://doi.org/10.3139/104.112229 SN - 2511-0896 VL - 115 IS - 1-2 SP - 94 EP - 97 PB - Hanser CY - München ER - TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko T1 - Der Industrie-4.0-Leitfaden für kleine und mittlere Unternehmen BT - Die zweite Richtlinie: Software JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb UR - https://doi.org/10.3139/104.112249 Y1 - 2020 UR - https://doi.org/10.3139/104.112249 SN - 2511-0896 VL - 115 IS - 3 SP - 178 EP - 181 PB - Hanser CY - München ER - TY - JOUR A1 - Axmann, Bernhard A1 - Pujar, Sanket T1 - Artificial Intelligence in Knowledge Management: Overview and Selection of Software for Automotive Reporting JF - Tehnički glasnik N2 - Knowledge Management is essential for modern organizations, enabling the systematic capture, organization, and sharing of knowledge to enhance decision-making and innovation. Traditional Knowledge Management tools, focused on document storage and retrieval, struggle with unstructured data and collaboration, necessitating advanced technological solutions, particularly those incorporating Artificial Intelligence. - Artificial Intelligence-driven Knowledge Management systems revolutionize data handling through automation, and real-time insights. This is particularly valuable in data-intensive industries like automotive, finance, and healthcare. In the automotive sector, annual reports provide critical insights but are complex and time-consuming to analyze and are a complex example and therefore a good test case. Annual reports of 5 major automotive companies BMW, Volkswagen group, Toyota Motors, General Motors and Tesla were selected as the testing dataset. Artificial Intelligence tools, using natural language processing and machine learning, streamline data extraction. - Despite their benefits, organizations face challenges in selecting the right Artificial Intelligence-driven Knowledge Management software due to a lack of standardized evaluation frameworks. This research applies a systematic methodology for assessing such software, considering usability, adaptability, cost-effectiveness, and data privacy compliance, specifically tailored to automotive reporting and gives recommendation for software tools. UR - https://doi.org/10.31803/tg-20250313154901 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250313154901 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59480 SN - 1848-5588 VL - 19 IS - si1 SP - 130 EP - 135 PB - University North CY - Koprivnica ER - TY - JOUR A1 - Straßer, Thomas Andreas A1 - Axmann, Bernhard T1 - Analyse und Bewertung von KI-Anwendungen in der Logistik JF - Logistics Journal T2 - Analysis and evaluation of AI applications in logistics UR - https://doi.org/10.2195/lj_NotRev_strasser_de_202108_01 Y1 - 2021 UR - https://doi.org/10.2195/lj_NotRev_strasser_de_202108_01 SN - 1860-5923 VL - 2021 PB - WGTL CY - Dresden ER - TY - CHAP A1 - Axmann, Bernhard A1 - Dzhelil, Sevgin Ahmed A1 - Najeeb, Asna T1 - Practical Comparison of UiPath and Power Automate by Creating an Automation Use Case from Logistics T2 - 2024 14th International Conference on Advanced Computer Information Technologies ACIT’2024: Conference Proceedings UR - https://doi.org/10.1109/ACIT62333.2024.10712623 Y1 - 2024 UR - https://doi.org/10.1109/ACIT62333.2024.10712623 SN - 979-8-3503-5004-3 SP - 224 EP - 229 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko T1 - Process & Software Selection for Robotic Process Automation (RPA) JF - Tehnički glasnik N2 - Robotic process automation (RPA) is a technology for office automation to imitate human behaviour when interacting with computers to perform digitized tasks manually, such as opening and closing applications, reading documents, entering data, and sending e-mails. As with any new digital technology answering the question of where to start and what is the right software, is challenging. In the case of RPA, the question of where to start depends on the selection of the business process to be automated and optimized. There are approaches for process selection in research, but they are relatively complex and have not been validated in practice. To fill this gap, we have simplified the process selection method and validated it on a practical example. We also present a simple method to select the appropriate RPA software. The criteria selection and evaluation were done with the Pairwise Comparison and Benefit Value Analysis method. This approach is relatively easy to follow and to apply in practice and thus also closes a gap in applied research. UR - https://doi.org/10.31803/tg-20220417182552 KW - assessment KW - office automation KW - process selection KW - RPA (Robotic Process Automation) KW - software selection Y1 - 2022 UR - https://doi.org/10.31803/tg-20220417182552 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-35250 SN - 1848-5588 VL - 16 IS - 3 SP - 412 EP - 419 PB - University North CY - Koprivnica ER - TY - JOUR A1 - Axmann, Bernhard A1 - Harmoko, Harmoko A1 - Malhotra, Rahul T1 - The Assessment of Robotic Process Automation Projects with a Portfolio Analysis: First Step - Evaluation Criteria Identification and Introduction of the Portfolio Concept JF - Tehnički glasnik N2 - RPA’s (Robotic Process Automation) usage in organizations has rapidly increased in recent years; as a result, companies have developed high expectations from this technology. However, according to Ernst & Young (E&Y), 30-50% of observed RPA projects initially fail and reveal several risks, which lead to investment losses. Consequently, the RPA project is prematurely retired, and the company is back to the manual process. This premature retirement is mainly because of wrong process selection and the not sufficient company automation (RPA) maturity. Therefore, this paper will introduce the concept of an RPA Portfolio, which will assess the complexity of business processes with a company’s automation (RPA) maturity. The RPA Portfolio is a new innovative concept to simplify and visualize the business process selection for RPA projects, and will help to introduce successfully the right RPA projects. UR - https://doi.org/10.31803/tg-20230416193006 KW - automation maturity KW - business process KW - portfolio KW - robotic process automation KW - technology assessment Y1 - 2023 UR - https://doi.org/10.31803/tg-20230416193006 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-37809 SN - 1848-5588 VL - 17 IS - 2 SP - 207 EP - 214 PB - University North CY - Koprivnica ER -