Process Model for the Data-driven Identification of Machine Function Usage for the Reduction of Machine Variants

Wagenmann, Steffen; Krause, Artur; Rapp, Simon; Hünemeyer, Sebastian; Albers, Albert; Bursac, Nikola

doi:10.1109/ieem55944.2022.9989909

Cited by 4 publications

(1 citation statement)

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“…Depending on the extent of the changes, the developing process of an entire system or a subsystem originates through principle variation, embodiment variation and carryovers (Albers et al, 2018). To support the development of new product generations, the analysis of field-gathered machine data can provide valuable insights into the machine usage and therefore its interconnected reference system elements (Wagenmann et al, 2022). To be able to consider sustainability within the product development process, the potential environmental impact must be assessed.…”

Section: Eco-design and Product Developmentmentioning

confidence: 99%

Data-driven life cycle assessment for mechatronic systems: a comparative analysis of environmental impact assessments

Krause,

Wagenmann,

Ritzer

et al. 2024

Proc. Des. Soc.

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The growing emphasis on sustainability integrates eco-design and life cycle analysis into product development. Despite the value of LCAs, data limitations lead to assumptions, impacting accuracy. This study compares an estimation-based LCA with a data-driven approach, focusing on a laser machine's operational phase. The significant influence of resource consumption during operation underscores the necessity of optimization. Applying a data-driven approach reveals a 24% difference compared to the estimation-based method, emphasizing the challenges in obtaining accurate data for effective LCAs.

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Section: Eco-design and Product Developmentmentioning

confidence: 99%