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New production technologies have inherent technical risks, but also established production technologies can not always be transferred to new products or components without problems. Accordingly, these technical risks must be taken into account when planning production systems. This paper presents an approach for the optimized allocation of development resources with regard to the technical risks of production technologies and processes. First, the production scenario is modeled and simulated using GRAMOSA. Then the simulation results are used for the optimized assignment of the development budget by means of mathematical optimization.

Digitisation offers enormous possibilities but also holds entrepreneurial risks such as data security aspects and misinvestments. Especially small and medium sized enterprises (SMEs) are facing problems by trying to keep pace with digital progress. A helpful tool would be a classification scheme specifically designed for SMEs that shows to which degree the company has already implemented digitisation technologies. Therefore we discuss why such a model is crucial, conduct a comprehensive literature survey and outline a new model.

Industry 4.0-related potentials leading to Industry 4.0 implementation mostly remain unclear. Consequently, this paper analyzes potentials that drive manufacturers to implement Industry 4.0 in five industries. Whereas mechanical and plant engineering as well as electrical engineering companies consider business-model driven, operational as well as ecological and social benefits as relevant for Industry 4.0 implementation, the chemical and steel industry widely disregard business-model driven opportunities. The automotive industry merely focuses on operational benefits provided by Industry 4.0.

Managers across the globe discuss the impact of digitalization on their business models. Among many other functions, procurement is strongly impacted by this development. However, “Procurement 4.0” goes far beyond the increased use of IT systems. It also has an impact on strategic dimensions such as supplier relationships. Data in this context will have a more important, if not critical, role- whether as some sort of “currency” in negotiations or as the basis for many procurement decisions, from operative order processing to supplier selection.

Blockchain technology - a distributed ledger in which transactions of all kinds of values can be carried out securely, transparently and consensually without trust in a central authority - is a socio-technical innovation that has the potential to enable new business models and make existing business models obsolete. While most applications today exist in the financial sector (e.g., payment processing), the technology is suitable for various industrial applications, especially in the area of Internet of Things (IoT) applications. This article uses three propositions and various concrete examples to shed light on the possible applications of blockchain technology for new IoT business models.

BC has just passed the peak of inflated expectations. This article aims to assess the status quo of the technology in terms of logistics and to identify initial implications. To this end, the basics of BC are explained and the existing scientific literature is summarized. Subsequently, examples from practice and research projects are presented and compared with the previously presented findings in order to allow a systematization of the application potentials. Possible implications as well as opportunities and risks for logistics conclude the article.

The increasing digitization of production is leading to new requirements and an increase in complexity in data management. Data and applications will become even more decentralized in the future, while ensuring data security and data validity. These requirements are difficult to implement with traditional databases. One promising technology is the Blockchain, which has been used in the context of crypto currencies like bitcoins for several years. In this article, the blockchain is presented in an industrial application in the context of a quality data acquisition in assembly.

The fourth industrial revolution has brought about a radical change for companies in all sectors of industry. Since the consequences of this revolution cannot yet be estimated, the forecasts of the full development of industry 4.0 vary considerably. In the past, industry 4.0’s implementation date has been considered, but the level of detail on the technology side is too high and there is a substantial lack of differentiation on the users side. Knowledge of the industry-specific implementation date of Industry 4.0 is essential for a successful transformation. For this purpose a two-part analysis is carried out: First of all, a suitable innovation cycle for the new production paradigm is being developed. Secondly, determinants of adoption are derived from Industry 4.0. The combination of these parts allows classifying the sectors in the industry 4.0 innovation cycle.

Industrial communication benefits from wireless systems, which is more flexible, easily scalable and low in maintenance compared to wired systems. Hence, wireless systems are of interest to many producing companies in various industries. However, industrial applications vary broadly in their requirements regarding a communication system. Thus, applications are categorized by their typical requirements, and suitable wireless systems are proposed. Based on these considerations, methods for comparing different wireless systems are reviewed and thereby, the decision making process is supported.

Manufacturing companies, particularly small and medium-sized ones, should be supported in their Digital Transformation (Industry 4.0) and its implementation of necessary transformation measures. This article introduces a study on models and self-assessments for industry 4.0 maturity level analyses, together with a regulation framework for productivity management, which both helping companies to identify the potential that can be realised with Industry 4.0 considering their current economic activities and business options.