Autor: Timo Klünder

As Industry 4.0 Technologies are swiftly spreading in global economy and enterprises are cooperating in supply chain networks, the question arises how fit these networks are for the imminent challenges. The contribution presents a method which allows to evaluate the industry 4.0-readiness for the example of an automotive network. As a first part, a qualitative analysis is carried out by means of an Industry 4.0-compass. Subsequently, a performance indicator based quantitative analysis is used to assess the industry 4.0-readiness of the automotive network.

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.

The digitalization is not only the basis of new business models, smart products and innovative services but also a source of uncertainty. This uncertainty about the economic benefits presents a major implementation barrier. To digitize the german production site until 2025 a reduction of risks is mandatory. The developed life cycle model of Industry 4.0 supply chain networks supports a transparent evaluation of risks. Findings show that there exists a gap between perceived and real risks. For a successful transformation, companies need to overcome those barriers.

The proliferation of technological innovations in additive manufacturing is accompanied by an increasing awareness of sustainability. In order to achieve an adequate investment methodical support is needed. A set of indicators for sustainable production represents the performance of a technology. Since an evaluation of technologies is subjective individual preferences of decision makers have to be taken into account. Hence, the multiple-criteria decision analysis methodology PROMETHEE is applicable in this context.