Industry 4.0 envisions Cyber-Physical Production Systems (CPPSs) to foster adaptive production of mass-customizable products. Manufacturing approaches based on capabilities and skills aim to support this adaptability by encapsulating machine functions and decoupling them from specific production processes. At the 2022 IEEE conference on Emerging Technologies and Factory Automation (ETFA), a special session on capability- and skill-based manufacturing is hosted for the fourth time. However, an overview on capability- and skill based systems in factory automation and manufacturing systems is missing. This paper aims to provide such an overview and give insights to this particular field of research. We conducted a concise literature survey of papers covering the topics of capabilities and skills in manufacturing from the last ten years of the ETFA conference. We found 247 papers with a notion on capabilities and skills and identified and analyzed 34 relevant papers which met this survey's inclusion criteria. In this paper, we provide (i) an overview of the research field, (ii) an analysis of the characteristics of capabilities and skills, and (iii) a discussion on gaps and opportunities.

In manufacturing, many use cases of Industry 4.0 require vendor-neutral and machine-readable information models to describe, implement and execute resource functions. Such models have been researched under the terms capabilities and skills. Standardization of such models is required, but currently not available. This paper presents a reference model developed jointly by members of various organizations in a working group of the Plattform Industrie 4.0. This model covers definitions of most important aspects of capabilities and skills. It can be seen as a basis for further standardization efforts.

Manufacturing is a special field. On the one hand, the slogan „never touch a running system" is the maxim for some production managers. This way of thinking is typically found in areas with strong audit requirements, such as in the medical industry. On the other hand, there are production managers who are real innovators. Following the value proposition of Industrie 4.0, they use technology to improve quality, reduce delivery times or increase efficiency in their factories.

Many manufacturing and industrial companies have realised that digital transformation will require changes in the way they do business. Experts will tell you that digital transformation is not about making energy, discrete and process manufacturing more efficient, but is about establishing new business models while continuing to make money from their old business models. These changes are so substantial that many talk about a revolution, namely the 4th industrial revolution. The Industrial Internet of Things – abbreviated to IIoT and known in Germany as Industrie 4.0 – is a technology trend that is the enabler of this revolution, and is bringing about a transformation in the way we do business. So, how do you know you're on the right path?

In this installment of the AI in Supply Chain series (#AIinSupplyChain), we explore the topic of industrial supply chains and factories of the future since this is where the AI applications we are covering will primarily be used. According to the German Federal Ministry for Economic Affairs and Energy, "Industrie 4.0 refers to the intelligent networking of machines and processes for industry with the help of information and communication technology." Industrie 4.0 is a term that is closely related to the terms Factory of the Future and Fourth Industrial Revolution. Industrie 4.0 envisions a future in which: Factories produce goods in fluctuating quantities based on real-time demand rather than preset production quotas. Production lines are modularized and can be reconfigured easily to enable the production of different types of products in small lots.

The model simulates realistic production environments using a training model from Fischertechnik, the protocols MQTT, OPC UA, as well as Amazon Web Services and a programmable logic controller from Siemens. The AR apps were designed to be platform-independent, so that they run on iPadOS, iOS and Android, as well as HoloLens 1 and 2. The "SmARt Factory" continues to evolve: in the future, for example, a multi-agent system will enable adaptable production.

Experience the look and feel of the industrial workplace of the future: Adaptive assistance systems, collaboration between human and large industrial robots, smart sensors and virtual industrial engineering. We are opening our doors to international guests for a tour through our Future Work Lab. You will be able to visit our large Demonstrator World and talk to our experts about innovations of Industrie 4.0, artificial intelligence and the smart factory of the future. Find out what the future workplace of manufacturing might look like during a free visit or a guided tour through our Demonstrator World. We will be happy to welcome you at our campus in Stuttgart!

PUBLICATION OF THE PLATFORM - This publication addresses the question of the extent to which the existing legal norms can be applied to Artificial Intelligence. The Working Group on the Legal Framework highlights which legislative gaps the legislator may have to close.

Wipro signed a strategic partnership with the Industrie 4.0 Maturity Center (I4.0MC), Based in Aachen, Germany, I4.0MC is a part of RWTH Aachen Campus With the help of this strategic partnership, Wipro consultants use the i4.0MC's program to support their client's digital transformation processes, the announcement notes. The acatech Industrie 4.0 Maturity Index, applied by the Industrie 4.0 Maturity Center, works as a methodical guideline to individually design the path to an agile company and to derive the necessary steps. The partnership will also promote the collaboration between the industry and academic experts across the industries such as industrial manufacturing, consumer goods, automotive, oil & gas, and life science. Christian Hocken, MBA, Managing Partner said, "We are looking forward to the cooperation with a leading technology company. Our competences complement each other in an ideal way. We are providing the management frameworks and tools while Wipro will be realizing the digital transformation. Together we will be able to serve our customers with tailor-made transformation projects to become a data-driven, agile company."

The disruptive potential of the upcoming digital transformations for the industrial manufacturing domain have led to several reference frameworks and numerous standardization approaches. On the other hand, the Semantic Web community has made significant contributions in the field, for instance on data and service description, integration of heterogeneous sources and devices, and AI techniques in distributed systems. These two streams of work are, however, mostly unrelated and only briefly regard each others requirements, practices and terminology. We contribute to closing this gap by providing the Semantic Asset Administration Shell, an RDF-based representation of the Industrie 4.0 Component. We provide an ontology for the latest data model specification, created a RML mapping, supply resources to validate the RDF entities and introduce basic reasoning on the Asset Administration Shell data model. Furthermore, we discuss the different assumptions and presentation patterns, and analyze the implications of a semantic representation on the original data. We evaluate the thereby created overheads, and conclude that the semantic lifting is manageable, also for restricted or embedded devices, and therefore meets the needs of Industrie 4.0 scenarios.