Automation

Artificial Intelligence in ERP Systems

Artificial Intelligence in ERP Systems

Development potential and benchmarking
Marcus Grum ORCID Icon, Nicolas Korjahn
The use of artificial intelligence (AI) is becoming more important for a variety of industries, which is why enterprise resource planning (ERP) systems also offer many possible uses of AI. Due to their newly acquired, AI-based adaptability and learning abilities, modern AI-integrated ERP systems are able to develop competencies, plan processes, make forecasts and interact intelligently with humans. It is not uncommon for such systems to initiate major structural changes for companies and to open up new markets and design areas [1]. In order to measure the progress of an ERP system in terms of AI, the Center for Enterprise Research (CER) has developed an AI maturity model. Building on this model, a tool for evaluating AI integration in an ERP system should be able to showcase potential for development and enable market comparison.
Industry 4.0 Science | Volume 39 | 2023 | Edition 1 | Pages 100-105 | DOI 10.30844/I4SE.23.1.100
Information Exchange in the Maritime Supply Chain

Information Exchange in the Maritime Supply Chain

Johannes Schnelle ORCID Icon, Wolfgang Kersten ORCID Icon
Blockchain is seen as an enabler to increase the efficiency, transparency, and security of information exchange in supply chains. An important application area is maritime logistics, as blockchain facilitates the digitalization of documents and increases the efficiency of the processes. In this article, we elaborate on the example of temperature-controlled container transports the potential for adopting blockchain and the requirements to be considered from the technological and organizational environment.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 6 | Pages 29-32 | DOI 10.30844/IM_22-6_29-32
Automated Assembly of Large-Scale Water Electrolyzers

Automated Assembly of Large-Scale Water Electrolyzers

Digitale Montageplanung für eine nachhaltige Wasserstoffwirtschaft auf Grundlage von Produkt, Prozess und Ressource
Patrick Adler, Daniel Syniawa, Malte Jakschik, Lukas Christ, Alfred Hypki, Bernd Kuhlenkötter ORCID Icon
A key element of the energy transition in Germany lies in green hydrogen. The current production of electrolyzers is mostly done in a manufactory-like manner. By digital planning and preparing an assembly with automated, manual and collaborative elements, the manufacturing of water electrolyzers can be scaled economically. In this paper, a reference process from electrolyzer assembly is selected and analyzed for the complete mapping of a data structure. The determined data structure can be used as a basis for a digital twin.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 5 | Pages 12-16 | DOI 10.30844/IM_22-5_12-16
Technology Accep­tance of Robotic Process Automation

Technology Accep­tance of Robotic Process Automation

An empirical analysis
Jörg von Garrel, Jonas Geist
Based on theoretical-empirical findings presented in the article "Technology Acceptance of Robotic Process Automation (RPA) (Part 1)", this article presents the results of an empirical study on the acceptance of robotic process automation (RPA) using structural equation modeling. This survey was conducted in a finance department of the business unit "Smart Infrastructure - Digital Grid" of a global technology company distributed throughout Germany.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 5 | Pages 40-44
Automated Environment Analysis – Generation of AI Training Data Sets

Automated Environment Analysis - Generation of AI Training Data Sets

Annika Lange ORCID Icon, Julia-Anne Scholz, Thomas Knothe ORCID Icon, Magdalena Scharf
To show SMEs a way to identify changes at an early stage, the interactive situation awareness monitor developed by Fraunhofer IPK is used. This gives companies an individually structured overview about their environment and their company (e. g. order situation). The area of the corporate environment is currently being expanded to include the compa- ny-specific component of automatic recognition of context-related data in order to provide relevant information to a company automatically. For this purpose, a machine learning model is developed and trained using company-specific data sets. First- ly, it is necessary to create the data sets with relevant and irrelevant environment information. For that, the PESTEL analysis is applied in this paper. Further- more, advantages and disadvantages of the analy- sis for generating data sets are discussed.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 4 | Pages 19-22
Technology Acceptance of Robotic Process Automation (RPA)

Technology Acceptance of Robotic Process Automation (RPA)

Jonas Geist, Jörg von Garrel
This article aims to develop a model for the acceptance of RPA technologies based on the presentation of the state-of-the-art. The model is the basis of an empirical study on the acceptance of robot-assisted process automation (RPA) at a global technology company. The results of this study are presented in a corresponding publication "An Empirical Analysis of Technology Acceptance of Robotic Process Automation (RPA) (Part 2)".
Industrie 4.0 Management | Volume 38 | 2022 | Edition 4 | Pages 43-47
Robotic Process Automation (RPA) in Logistics − Implementation Model and Success Factors

Robotic Process Automation (RPA) in Logistics − Implementation Model and Success Factors

Vorgehensmodell und Erfolgsfaktoren für die Implementierung
Carsten Feldmann, Jan Krakau, Victor Kaupe
RPA refers to bots that automate repetitive, rulebased tasks in a business process. This paper describes general areas of application for RPA in logistics as well as two practical logistics examples. In addition, a procedure model for the implementation of RPA in logistics is presented. The paper answers the following questions: What are suitable use cases for RPA in logistics? What criteria support the selection of suitable processes? And how should an implementation guide be designed to systematically support an implementation project taking into account critical success factors?
Industrie 4.0 Management | Volume 38 | 2022 | Edition 3 | Pages 35-40
Digital Assistance and Learning Systems

Digital Assistance and Learning Systems

Design of Systems for Manual Assembly Conducive to Learning
Tina Haase, Dirk Berndt, Wilhelm Termath, Michael Dick
The authors present a methodological approach for designing assistance systems conducive to learning and derive requirements for their design. They base the design of these systems on a fundamental understanding of the cooperation between humans and machines, which still places decisions and responsibility with humans. Finally, the authors show concrete requirements and measures of a participatory design and implementation process.
Industrie 4.0 Management | Volume 38 | 2022 | Edition 2 | Pages 19-22
Container Terminal Automation − Success Factors for the Management of Straddle Carrier Automation

Container Terminal Automation − Success Factors for the Management of Straddle Carrier Automation

Erfolgsfaktoren für das Management der Automatisierung von Straddle Carriern
Sebastian Eberlein, Stephan Oelker, Serge Jacovis, Vanessa Beckmann, Michael Freitag ORCID Icon
Efficiency in container terminal operations is key for competitiveness. Many large German terminals use the flexible but relatively risk-laden manned straddle carriers (SCs). The research project STRADegy evaluated the reliability and profitability of automated SCs in northern-German container terminals via a combination of a pilot installation and an emulation at the container terminal in Wilhelmshaven. Parallel to that, rollout-guidelines were developed. This paper introduces central results regarding a successful rollout of auto-SC-systems.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 6 | Pages 6-10
The Path from Automation to Autonomy

The Path from Automation to Autonomy

Evolutionary Steps of a Fully Autonomous Logistics Process in Manufacturing Companies
Benjamin Nitsche, Tobias Marc Wringe, Frank Straube
The automation of informational logistics processes is already one of the core challenges of manufacturing firms on their way to autonomous logistics systems. It is quite realistic that the majority of informational logistics processes will be running autonomously by the end of this decade. However, the path to this goal is still uncertain. Therefore, this article aims at defining the evolutionary stages of autonomy of logistics processes with the involvement of industry experts, describing prerequisites for reaching individual stages and discussing challenges along the way. In addition, the most important informational logistics processes with high autonomization potential are identified and an estimate is made of when the autonomy levels can be expected to be reached industry-wide.
Industrie 4.0 Management | Volume 37 | 2021 | Edition 6 | Pages 15-19
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