Sustainability assessment of production networks using simulation-data-based process mining
Year: 2024
Type: conference-paper
Abstract: The sustainability of businesses determines the long-term success of companies and is increasingly being integrated into the target systems of industrial companies. Production, and thus the strategic network design of internal production networks, is one of the most important fields of action for global manufacturing companies. During strategic network design, tactical and strategic structural decisions strongly influence the sustainability of the planned production network. Therefore, a sustainability perspective should be part of this phase when comparing alternative network solutions to identify an appropriate network design. Due to limited data availability, the currently available sustainability assessment approaches cannot be used during the early design phase of the production network. Moreover, current approaches mainly focus on the sustainability impact of strategic structural decisions rather than tactical decisions. To address these problems, this contribution presents a methodology for creating and integrating simulation data into the sustainability evaluation of production networks in the early design phase. First, simulation-based event log data is linked to planning data and data from the literature to build a data model. Then, a key performance indicator (KPI) system is derived from scientific literature and specified using the data model and strategic network planning decision variables. The KPI system is finally applied to evaluate the sustainability of alternative network solutions according to the triple bottom line (social, environmental, economic) of sustainability. A process mining based evaluation methodology is linked to the KPI system. The concept was exemplarily applied in an automotive case study.
Source: Procedia Computer Science
Institutions: Technical University of Munich, BMW (Germany)
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4399209487