Method to identify energy efficiency potentials of metal cutting machine tools in industry

Petruschke, Lars; Burkhardt, Max; Kohne, Thomas; Schraml, Philipp; Helfert, Mark; Abele, Eberhard

doi:10.1016/j.procir.2020.01.066

Cited by 9 publications

(1 citation statement)

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“…The usage factor was chosen to consider that only a certain amount of power is actually consumed while the machine is running. In a study examining 32 machine tools, Petruschke et al [32] found out that only 19% of the connected power was actually consumed on average. Therefore, this factor was applied to the use case as well, to make a statement about the added value of the measurements in relation to the final PCF result in the case study.…”

Section: Closed-loop Circlementioning

confidence: 99%

Analysis of Uncertainty Factors in Part-Specific Greenhouse Gas Accounting

Weyand,

Bausch,

Engel

et al. 2023

Sustainability

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Due to the ongoing climate crisis and the resulting targets of several countries, as well as the EU, manufacturing companies face the need to address and reduce their greenhouse gas (GHG) emissions. To calculate these emissions, the product carbon footprint (PCF) can be a helpful tool, both to come up with reduction measures internally as well as to communicate it externally as competitive advantage. However, the PCF is subject to uncertainty factors that hinder its use and need to be systematically assessed. For this reason, this paper first collects and clusters relevant uncertainty factors resulting from differences between accounting standards, but also from imprecisions within the standards. Subsequently, the PCF is determined in different scenarios of uncertainty factors, applied to an industrial case study. This is used to be able to put the deviation in the final results into perspective. Recommendations for action are finally derived from the analysis of the literature and the results of the use case.

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Section: Closed-loop Circlementioning

confidence: 99%

Analysis of Uncertainty Factors in Part-Specific Greenhouse Gas Accounting

Weyand,

Bausch,

Engel

et al. 2023

Sustainability

View full text Add to dashboard Cite

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Development of a Holistic Framework for Identifying Energy Efficiency Potentials of Production Machines

Ioshchikhes

Piendl

Schmitz

et al. 2023

Lecture Notes in Mechanical Engineering

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A prerequisite to identify energy efficiency potentials and to improve energy efficiency is the measurement and analysis of the energy demand. However, in industrial practice, approaches to identify energy efficiency measures of production machines are associated with high costs for metering equipment and time consuming analysis requiring expertise. Against this background, this paper describes a comprehensive and cost-efficient framework from acquisition to analysis of energy data to serve as a starting point to increase energy efficiency in manufacturing. For this purpose, an energy transparency and analysis system is being developed that can measure, record and analyze electrical quantities. The validity of the data acquisition can be verified by utilizing a Raspberry Pi as a low-cost edge analyzer device. Measurement data is stored with associated metadata in a SQLite database for subsequent processing in a Python-based web application, in which machine learning algorithms can be deployed. The algorithms can be used to process vast amounts of data and to provide a basis for calculating energy performance indicators to reveal energy efficiency potentials. The overall workflow is validated using a lathe and a cleaning machine within the ETA Research Factory at the Technical University of Darmstadt.

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