Design

The digitalization in sustainability management and the creation of a consistent database for sustainability data can significantly support companies in meeting increasing sustainability requirements and transparency regarding the sustainability performance. This paper presents a service-oriented approach for the development of a platform for data-driven sustainability management in manufacturing companies.

A considerable part of global greenhouse gas emissions is caused in the industrial sector. Its digitialization is often seen as a means to increase sustainability. At the same time, ecological and social risks emerge. Their exploration is still in its infancy, however, previous findings point out multiple challenges. These must be conceptually taken into account in order to realize a sustainable industry 4.0. Building on a literature analysis, the following contribution presents current developments in research, industry, and policy. We shed light on a number of selected approaches, which aim at a sustainable industry 4.0. Finally, practical design options are outlined.

Accelerating climate change drives companies to reduce their greenhouse gas emissions. Road freight transport accounts for around 6 % of global CO2 emissions. However, high growth rates, the dependence on fossil fuels, and the high fragmentation of the market make the decarbonization of road freight transport challenging. Based on survey results, this paper elaborates how small road carriers, together with their clients, can contribute to achieving global climate targets by implementing appropriate measures and incentives.

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 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.

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.