Abstract
An analysis of energy efficiency at the machine level has become an important element of contemporary control and measurement systems. The results of such an analysis can not only be used as information about energy consumption but can also be used for predictive maintenance. The authors present a novel approach that is dedicated to the classification of machine-level energy efficiency that can be applied in the case of multivariate production. The concept was proven by research on the use case of an assembling station that consisted of a number of pneumatic devices. The proposed approach does not require detailed analysis about the production technology that is being used and also does not require additional knowledge about the order of the production variants that are being executed. The algorithm is based on observing the behaviour of the machine and then clustering the machine cycles that are observed.
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Acknowledgements
This work was supported by Polish National Centre of Research and Development from the project (“Knowledge integrating shop floor management system supporting preventive and predictive maintenance services for automotive polymorphic production framework” (grant agreement no: POIR.01.02.00-00-0307/16-00). The project is realized as Operation 1.2: “B + R sector programs” of Intelligent Development operational program in years 2014–2020 and co-financed by European Regional Development Fund.
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Cupek, R., Ziębiński, A., Drewniak, M., Fojcik, M. (2018). Estimation of the Number of Energy Consumption Profiles in the Case of Discreet Multi-variant Production. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_63
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