Typeset

Innovative digital and AI solutions for more energy-efficient production can decisively contribute to the environmental impact and competitiveness of companies, especially in the manufacturing industry. Requirements for the functionality and implementation of these solutions are complex and diverse; multiple stakeholders need to be addressed when eliciting requirements and various technology and business aspects have to be considered. This article presents a procedure for requirements elicitation for energy efficiency digitalization and AI projects.

Circular Economy is considered one of the most promising concepts on the way to a more sustainable economy. Expectations of a responsible corporate orientation are rising: This is shown by a recent ruling of the Federal Constitutional Court, which demands that Germany must be more ambitious in its climate goals [1]. The EU Green Deal envisages climate neutrality by 2050 and the “Circular Economy Action Plan” calls for more effective use of resources and reserves [2]. This article describes a method that companies can use to develop ideas for circular business models.

The future of shop floor management (SFM) lies in its digitization. The visualization of key performance indicators is already supported by various providers or set up by companies themselves to save time. But particularly valuable in SFM is the sustainable problem solving, which contains the knowledge of the employees in text. Therefore, approaches from Natural Language Processing (NLP) are applied to these text data to realize assistance functions. This article provides situation-specific implementation strategies.

Managers are still facing significant challenges in implementing Industry 4.0 technologies and many companies have not gone beyond their initial Industry 4.0 lighthouse project to date. In the midst of this ongoing transformation, the European Commission published a white paper in January 2021 dealing with the “Industry 5.0 concept”. This paper investigates the term “Industry 5.0” with regard to the contribution of the European Commission and illustrates the connection with current Industry 4.0 initiatives.

The complexity of manual activities in different areas of a company is increasing due to smaller batch sizes, higher product variants and shorter product life cycles. The balanced provision of information ensures shorter training times, higher acceptance among employees and can be used directly at the workplace. For system implementation, organizational factors must also be considered in accordance of a socio-technical system design.

The digital twin has moved into the focus of manufacturing companies and has been identified by Gartner as a key technology [1]. In the automotive industry, VW uses the digital twin in the cloud to plan, control and optimize production at all 122 locations in the future [2]. The digital twin is also the basis and an integral part of new, digital business models and the digitization of production companies. This article gives an overview of the current state of the art and describes a flexible reference model for planning and optimizing production systems based on the digital twin. The focus is on the one hand on the optimization of static layouts and material flows and on the other hand on the optimization of dynamic material flows and the temporal organization of processes.

The diffusion of networked, intelligent products and production goods within the framework of Industry 4.0 is not only changing production, but is also causing the emergence of new forms of value creation and new types of business models that offer products and services in an integrated manner. This trend is called hybrid value creation and aims to offer customers holistic and individual solutions. The development of such business models requires a multi-criterial feasibility study. This paper deals with the specifics of the feasibility study of hybrid value creation business models.