Energy Efficiency Evaluation of Manufacturing Systems by Considering Relevant Influencing Factors

D. Flick; L. Ji; P. Dehning; S. Thiede; C. Herrmann

doi:10.1016/j.procir.2017.03.097

Energy Efficiency Evaluation of Manufacturing Systems by Considering Relevant Influencing Factors

D. Flick, L. Ji, P. Dehning, S. Thiede, C. Herrmann

Research output: Contribution to journal › Conference article › Academic › peer-review

4 Citations (Scopus)

9 Downloads (Pure)

Abstract

Recent developments show an increasing interest in energy efficiency of different stakeholders like industry, customers and legislation. Against this background the paper provides insight of how a data based energy evaluation on shop floor level could help to evaluate the energy performance of comparable manufacturing systems and will provide incipient stages for improvement. The approach for efficiency evaluation is mainly based on residual analyzing of multiple linear regression models. Additionally through coefficient standardization the influencing factors on the energy performance will get quantified and therefore directly identify fields of improvement.

Original language	English
Pages (from-to)	586-591
Journal	Procedia CIRP
Volume	63
DOIs	https://doi.org/10.1016/j.procir.2017.03.097
Publication status	Published - 2017
Externally published	Yes
Event	50th CIRP Conference on Manufacturing Systems, CIRP CMS 2017 - Taichung City, Taiwan, Province of China Duration: 3 May 2017 → 5 May 2017 Conference number: 50

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10.1016/j.procir.2017.03.097Licence: CC BY-NC-ND

Flick-2017-Energy-efficiency-evaluation-of-manFinal published version, 481 KBLicence: CC BY-NC-ND

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abstract = "Recent developments show an increasing interest in energy efficiency of different stakeholders like industry, customers and legislation. Against this background the paper provides insight of how a data based energy evaluation on shop floor level could help to evaluate the energy performance of comparable manufacturing systems and will provide incipient stages for improvement. The approach for efficiency evaluation is mainly based on residual analyzing of multiple linear regression models. Additionally through coefficient standardization the influencing factors on the energy performance will get quantified and therefore directly identify fields of improvement.",

author = "D. Flick and L. Ji and P. Dehning and S. Thiede and C. Herrmann",

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AU - Flick, D.

AU - Ji, L.

AU - Dehning, P.

AU - Thiede, S.

AU - Herrmann, C.

N1 - Conference code: 50

PY - 2017

Y1 - 2017

N2 - Recent developments show an increasing interest in energy efficiency of different stakeholders like industry, customers and legislation. Against this background the paper provides insight of how a data based energy evaluation on shop floor level could help to evaluate the energy performance of comparable manufacturing systems and will provide incipient stages for improvement. The approach for efficiency evaluation is mainly based on residual analyzing of multiple linear regression models. Additionally through coefficient standardization the influencing factors on the energy performance will get quantified and therefore directly identify fields of improvement.

AB - Recent developments show an increasing interest in energy efficiency of different stakeholders like industry, customers and legislation. Against this background the paper provides insight of how a data based energy evaluation on shop floor level could help to evaluate the energy performance of comparable manufacturing systems and will provide incipient stages for improvement. The approach for efficiency evaluation is mainly based on residual analyzing of multiple linear regression models. Additionally through coefficient standardization the influencing factors on the energy performance will get quantified and therefore directly identify fields of improvement.

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U2 - 10.1016/j.procir.2017.03.097

DO - 10.1016/j.procir.2017.03.097

M3 - Conference article

VL - 63

SP - 586

EP - 591

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JF - Procedia CIRP

SN - 2212-8271

T2 - 50th CIRP Conference on Manufacturing Systems, CIRP CMS 2017

Y2 - 3 May 2017 through 5 May 2017

ER -