Decision Procedure for Efficient Data Acquisition for Distinct Energy Prognosis Models

Author:

Süße Marian1,Stoldt Johannes1,Schlegel Andreas1,Putz Matthias1

Affiliation:

1. Fraunhofer Institute for Machine Tools and Forming Technology IWU

Abstract

The current challenges for enterprises are heavily linked to resource and energy efficiency, a result of political guidelines and the overall consciousness for environmental issues in society. Thus, the impact of energy efficiency on factory planning and production planning is of undeniable importance. Adequate consumption information utilising various depiction methods has become a necessity in this respect. Yet, only few works provide information on the efficiency of energy data acquisition methods. This paper proposes a methodological framework for defining an efficient procedure for energy data acquisition in accordance with the depiction or prognosis method. A preliminary literature review indicates the variety of methods for energy data depiction and prognosis. The classification of these methods regarding planning state and planning levels leads to the estimation of relevant input data. Based on the fundamental investigation of necessary input data the decision approach is developed with a general heuristic decision model and incorporates the Analytic Hierarchy Process for quantification and solution of the overall decision problem. Therefore the integration of multiple decision criteria enables the consideration of different quantitative and qualitative influences. As a result the whole approach supports the collaborative identification of means for energy data acquisition and is applicable in several circumstances where energy data needs to be gathered efficiently. The decision procedures exemplary application has shown the general proficiency of the approach and that excessive data acquisition which contradicts efficiency is avoidable.

Publisher

Trans Tech Publications, Ltd.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Classification, Input Data, and Key Performance Indicators;Energy-Related Material Flow Simulation in Production and Logistics;2023-12-15

2. Decision Support for Planning Techniques in Energy Efficiency Projects;Procedia CIRP;2018

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