Data quality in environmental assessment methods – Implications for the operational management in manufacturing

Procedia CIRP, vol. 122, pp. 807–812

Abstract

To implement environmentally sustainable, resource-efficient manufacturing, the quantification of the environmental impacts is a central task. This task requires suitable methods. Various lifecycle phases, including remanufacturing concepts, and the associated increasing complexity demand a change from static to dynamic assessment methods. Flexible changes must be considered. Thereby, data quality has a major impact on the subsequent assessment results. Though the available data amount in a manufacturing environment is constantly increasing, the influence of data quality on the respective method – and thus, the reliability of the results – remains a key issue. To address this problem, this paper investigates the necessary developments regarding data quality for environmental assessment methods in dynamically changing manufacturing settings. First, relevant data quality dimensions are identified. Subsequently, a cross-comparison of data quality dimensions and different approaches of environmental evaluation in manufacturing is developed. The necessary changes to data quality requirements in operational environmental assessments are derived. Finally, a concept for the improvement of data quality in dynamic assessments is proposed and discussed based on the use case of battery modules’ remanufacturing. This paper contributes to the development of environmental assessment methods that are evolving from static, historical data-based evaluations to dynamic assessment tools of flexible productions.

Authors 4

1. Juliane Elsner corresponding Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering, WZL of RWTH Aachen University, 52074 Aachen, Germany

2. Hanna Brings Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering, WZL of RWTH Aachen University, 52074 Aachen, Germany

3. Felix Sohnius Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering, WZL of RWTH Aachen University, 52074 Aachen, Germany

4. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology IPT Laboratory for Machine Tools and Production Engineering (WZL)

   Fraunhofer Institute for Production Technology IPT · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT, Steinbachstraße 17, 52074 Aachen, Germany

   Laboratory for Machine Tools and Production Engineering, WZL of RWTH Aachen University, 52074 Aachen, Germany