Datenbasierte Standortauswahl

Schuh, Günther; Gützlaff, Andreas; Adlon, Tobias; Schupp, Steffen; Endrikat, Morten; Schlosser, Tino X.

doi:10.1515/zwf-2022-1067

Cited by 1 publication

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the following, a four-step approach is presented, which objectifies the site selection process individually for each company (Schuh et al 2022).…”

Section: Data-driven Site Selection Frameworkmentioning

confidence: 99%

Managing Growing Uncertainties in Long-Term Production Management

Schuh,

Gützlaff,

Rodemann

et al. 2023

Interdisciplinary Excellence Accelerator Series

View full text Add to dashboard Cite

Long-term production management defines the future production structure and ensures the long-term competitiveness. Companies around the world currently have to deal with the challenge of making decisions in an uncertain and rapidly changing environment. The quality of decision-making suffers from the rapidly changing global market requirements and the uniqueness and infrequency with which decisions are made. Since decisions in long-term production management can rarely be reversed and are associated with high costs, an increase in decision quality is urgently needed. To this end, four different applications are presented in the following, which support the decision process by increasing decision quality and make uncertainty manageable. For each of the applications presented, a separate digital shadow was built with the objective of being able to make better decisions from existing data from production and the environment. In addition, a linking of the applications is being pursued:The Best Practice Sharing App creates transparency about existing production knowledge through the data-based identification of comparable production processes in the production network and helps to share best practices between sites. With the Supply Chain Cockpit, resilience can be increased through a data-based design of the procurement strategy that enables to manage disruptions. By adapting the procurement strategy for example by choosing suppliers at different locations the impact of disruptions can be reduced. While the Supply Chain Cockpit focuses on the strategy and decisions that affect the external partners (e.g., suppliers), the Data-Driven Site Selection concentrates on determining the sites of the company-internal global production network by creating transparency in the decision process of site selections. Different external data from various sources are analyzed and visualized in an appropriate way to support the decision process. Finally, the issue of sustainability is also crucial for successful long-term production management. Thus, the Sustainable Footprint Design App presents an approach that takes into account key sustainability indicators for network design.

show abstract

“…In the following, a four-step approach is presented, which objectifies the site selection process individually for each company (Schuh et al 2022).…”

Section: Data-driven Site Selection Frameworkmentioning

confidence: 99%