Intelligent Systems for the Prognosis of Energy Consumption in Manufacturing and Assembly

Stetter, Ralf; Witczak, Piotr; Spindler, Claudius; Hertel, Julian David; Witczak, Marcin

doi:10.1016/j.procir.2015.06.084

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…Therefore, during the last years more robust control systems able to treat and use the available information have been developed. For example, currently, control systems oriented to prognosis and maintenance of manufacturing systems, based on the historical data, have been developed with the aim to predict and program the required changes or maintenance activities [107,108,109]. Additional to the prediction of maintenance tasks, strategies such as receding horizon control and advanced methods of process control (e.g., model predictive control (MPC)), have started to gain attention too, mainly, focusing on problems of energy efficiency and flexibility for planning and scheduling of processes at machine, line, and plant level [110,111,112,113].…”

Section: Control Strategies In Manufacturing Systemsmentioning

confidence: 99%

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

Diaz

Ocampo‐Martínez

2019

Journal of Manufacturing Systems

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Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.

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Section: Control Strategies In Manufacturing Systemsmentioning

confidence: 99%

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

Diaz

Ocampo‐Martínez

2019

Journal of Manufacturing Systems

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Fuzzy Prognosis System for Decision Making to Vibrations Monitoring in Gas Turbine

Boulanouar

Hafaifa

Rachid

et al. 2021

Strojnícky Časopis - Journal of Mechanical Engineering

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This paper proposes a decision making approach based on the development of a fuzzy prognostic system to ensure the vibrations monitoring of a gas turbine based on real time information obtained from different installed sensors. In this approach the case of incomplete obtained data which may occur frequently is taken into account by using an approach of full data reconstitution form incomplete data. The proposed fuzzy prognostic system approach presented in this paper allows the analysis of the data obtained via the vibration indicators of a gas turbine system for the accurate identification of the faults to avoid the performance degradation of such systems. In order to prove the robustness of the proposed approach presented in this paper, several tested has been performed.

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Improvement of Working Performance of the Gas Compressor Station

Aliyeva¹,

Allahverdiyev²

2021

PAHTEI

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The working performance of compressor unit for compressing of gas to required pressure for injection of gas to underground reservoir and for transportation of it is considered. Performance data of compressor station for 2018 and 2019 analyzed. Dependencies of power consumption, specific consumption of gas which uses as fuel for compressor is designed. Changes in noted above parameters during given two years are found based on detail analysis. The expediency of processing the signals of the sensors connected to the monitoring and control system of the compressor station, using fuzzy logic algorithms and digital signal processing for increasing of efficiency entire system is shown. Keywords: gas compressor, working performance, power consumption, signal processing, algorithms

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Intelligent Systems for the Prognosis of Energy Consumption in Manufacturing and Assembly

Cited by 4 publications

References 6 publications

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

Fuzzy Prognosis System for Decision Making to Vibrations Monitoring in Gas Turbine

Improvement of Working Performance of the Gas Compressor Station

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