Decision Management LSWI

Decision Management

Key areas: Operations research, formal group decision theories, collective assessment procedures, participatory decision-making, collective future analyses, decision logic and artificial intelligence

Decision management as a decisive factor in competition

Digitization is advancing more and more, customer needs are increasing and competition is growing: In order to continue to meet the increasing demands, companies must design their processes to be efficient and optimized. Decision management offers a suitable approach for defining and analyzing decisions and identifying relevant correlations. Business processes can also be understood as a logical sequence and interweaving of independent and interdependent individual decisions, which can influence or distort the result depending on the procedure used. In our research we focus on procedures, theories and technologies of formal and discursive decision-making processes. The goal is to increase efficiency and effectiveness as well as to increase transparency of the cooperation.

Workshop Production: Artificial intelligence and proprietary decision logic

The future idea of the manufacturing industry is based on the concept of flexible workshop production. Here, machines are grouped together according to their technologies, but do not have any fixed links between them for the realisation of material and information flows. Instead, intelligent workpieces can decide for themselves where they move to for the next production step. Every production planning is therefore a decentralized decision-making process in which application systems control the factory and planning tasks are performed automatically. In our research we focus on the decision logic of individual objects in order to achieve partial selforganization within socio-technical systems.

Sequence planning in shop floor manufacturing

The orientation of production towards concepts such as Industry 4.0 is changing the framework conditions of numerous processes for sequence optimization in workshop production. Here, the sequence can change individually depending on the work order. New production orders, changed priorities at production time, delivery bottlenecks or a changed number of machines require that planning procedures must also consider the environment as an influencing factor. In our research we are looking for optimizing procedures with the aim of finding the best possible solution for organization and scheduling. Both problem-specific heuristics, which can be individually implemented by sufficient knowledge of the respective value chain, and solution space-based procedures, in which a fixed arrangement is defined between two actors who have already scheduled critical resources or orders in an ideal-typical way, are applied. With this procedure we can decisively limit the solution space and restrict strategies for its navigation to small spaces.

Applied bioeconomy, formal group decision theories and future analyses

The transformation of our society into an age without oil and fossil fuels is more than a simple change of carbon supplier. A conflict of goals is emerging in which nature and the environment compete with food and agriculture, and resources such as land and water are in conflict. Nature conservation and biodiversity are interests of the common good, which must be brought into the discourse in a participatory manner with the future stakeholders. Respectfully, every region and every company should be able to recognize and find its future role and requirements in the bioeconomic transformation process. In this context, our research project DiReBio analyses bioeconomic future analyses in regional workshops with the help of group decision theories. In our basic research, we investigate questions of influencing factors and cause-effect relationships within group decision theories and examine how collective will formation, evaluation and decisionmaking can be efficiently and effectively carried out and designed both online and offline.