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Companies, especially SMEs, face the challenge of introducing digital technologies efficiently and as smoothly as possible. Using the introduction of a digital assistance system in technical service as an example, this article shows which challenges and problem areas arise, how they can be overcome and which factors promote a successful introduction process. In the process it is worked out how SMEs with few resources can generate a high degree of participation and acceptance. The basis is a socio-technical understanding that takes a holistic view of the overall system of people, technology and organization in the introduction process of digital technologies.

Data plays an important role in our world - including production technology. Businesses are faced with rising customer demands and competitive pressure. Furthermore, the trend towards smaller batch sizes and increasing variant diversity requires quick reactivity and agility. In order to make the right decisions under these circumstances, data must be generated and analyzed to derive insights. AI technologies are suitable to address the growing uncertainty and complexity. In the following, methods are described that are vital to master data processes for high-quality AI technologies.

The increasing shortage of IT specialists requires lower-skilled employees to be empowered to perform tasks that previously required the involvement of experts. Industry 4.0’s emerging technologies for human-technology interaction and for the digital twin allow the design of intuitive user interfaces, system-independent communication interfaces, and user-specific assistance functionalities to meet this challenge. This paper presents a framework for configuring and monitoring of process flows for different production and logistics systems. By reviewing existing programming approaches, the paper derives requirements for the framework, describes its general architecture and the technical realization of the modular interaction interface. A prototypical implementation validates the presented concept on the example of a cellular conveyor system and a collaborative robot system.

Deep learning-based error detection methods outperform traditional methods because of the continuously increasing complexity of technical systems and inherent flexibility and scalability of Deep Learning techniques. This article introduces the KrakenBox – an autonomous Deep Learning-based error detector for industrial Cyber-Physical Systems (CPS). It exploits a lightweight, Long Short-Term Memory (LSTM) network capable of online error detection that can be deployed on an embedded platform such as NVIDIA Jetson AGX Xavier or even Google Coral Edge TPU. This article describes the architecture of the KrakenBox and demonstrates its application with two case studies.

In the project ARAS (Advanced Robot Assistance Solution) a robot programming assistant was developed, which allows for automated generation of robot programs for assembly processes. By using a multimodal approach for human-machine-interaction, assembly steps are recognized with machine learning algorithms while a worker is showing the robot how an assembly process is performed. Afterwards, a robot program is generated automatically. This way, new robot programs are created within minutes without the user having any knowledge about programming or robotics.

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.

Intense global competition, shorter product life cycles and an increasing number of variants require flexible and adaptable, but at the same time economical production and logistics systems. This requires constant replanning of factories and logistics systems. Value-adding processes are being outsourced to contract logistics providers. Contract logistics planners must respond to tenders as quickly as possible and develop a proposal with an initial planning concept and a cost estimation. Despite standardization efforts in planning, the knowledge is often only implicit at the planners. This article describes the need for support by an AI-based assistance system during the planning process and how a digital platform for such an assistance system should look like.

There is hardly any day without publishing news on digitization and industry 4.0 and their respective necessity. Risks and shortcomings of IT-security are as well current topics. The striking question on management level is, where is my company regarding IT-security? How can we get a guiding light into the complexity of all related terms? This article is an outcome of research activities at the University of Applied Sciences Middlehesse. It is meant to support management to identify the actual status of IT-security and identify possible shortfalls. Based on a maturity grade model IT-security is described by six aspects with five levels each. This will help to point out room for improvements

The “IT’S DIGITIVE” research project developed the prerequisites for collaborative and platform-supported processing of additive manufacturing-based services and thus important building blocks for an additive manufacturing-based service network. The focus was on intellectual property protection and the development of secure and trustworthy order fulfillment processes. Based on the identified inherent risks and threats in this distributed order processing, appropriate security countermeasures were developed using two use cases as examples and implemented as demonstrators.

Plant construction and engineering companies have to go to great lengths to present their highly complex products that weigh tons. Because sales staff cannot take them to the customer. Exhibiting them at trade fairs has proven its worth. But with the Corona pandemic, this sales channel has disappeared. That’s why digital alternatives are needed, such as a virtual showroom that supports salespeople in presenting and selling equipment. An API management platform ensures the smooth flow of data between various source systems and the virtual showroom app.