Intelligent energy audit and machine management for energy-efficient manufacturing

Pang, Chee Khiang; Cao, Le; Gan, Oon Peen; Chee, Xiang Min; Zhang, Dan Hong; Luo, Ming; Chan, Hian Leng; Lewis, Frank L.

doi:10.1109/iccis.2011.6070317

Cited by 10 publications

(5 citation statements)

References 4 publications

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“…In 2011, a finite-state machine was used to model energy consumption patterns of engineering processes, and a two-stage framework combining a Savizky-Golay filter with neural network was proposed to classify energy patterns. This method achieved an accuracy of 95.85% in identification of machine operation states and further realized the prediction of machine operation states and energy consumption patterns [67]. In the same year, based on non-intrusive load monitoring, a discrete wavelet transform and a modified universal threshold filter were used to divide time-series data into segments by detecting stepwise changes.…”

Section: Energy Monitoring Systemmentioning

confidence: 99%

A Comprehensive Study of Energy Conservation in Electric-Hydraulic Injection-Molding Equipment

et al. 2017

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An injection-molding machine (IMM) is equipment that produces all kinds of plastic products. At present, the global production of IMMs amounts to more than 30 million units each year, and its total production accounts for 50% of all plastic molding equipment. Now, the main energy consumption equipment of plastic processing plants consists in IMMs. Therefore, energy conservation research on IMMs has become urgent. This paper initially introduces the current development of IMMs. The working principle and the distribution of energy consumption of IMMs are then analyzed in detail. In addition, the methods and characteristics of the energy conservation technology in hydraulic control circuits and electrical control circuits are developed. Meanwhile, the recovery and the reuse of braking energy of IMMs are proposed. Moreover, some control strategies are discussed in order to improve energy efficiency. Finally, challenges and prospects for hydraulic IMMs are carried out. This paper thus provides a comprehensive review on energy-saving technology of electric-hydraulic injection-molding equipment for researchers.

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Section: Energy Monitoring Systemmentioning

confidence: 99%

A Comprehensive Study of Energy Conservation in Electric-Hydraulic Injection-Molding Equipment

et al. 2017

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“…Moreover, also the compressed air consumed by Sc1/2_U/D must be considered. According to [16]- [17] the required energy can be translated into equivalent electrical power as follows. The pneumatic cylinder that moves up and down the Stacker Crane has a diameter equal to 30 mm and a length equal to 10 mm which corresponds to a volume of air equal to 7 ml at the atmospheric pressure.…”

Section: Actuatorsmentioning

confidence: 99%

“…Further extensions of this approach have been reported in [15], [16], where the plant auxiliary systems have also been considered. In [17]- [19] the operating states of the process equipments and the associated energy consumption have been modeled in terms of Finite State Machines (FSM), see [20]- [22], a formalism suitable for dynamic simulation. A refined approach has been implemented in [23], where three different aspects of PE are taken into account, namely the mechanical, the logic control algorithms and the energy characteristics.…”

Section: Introductionmentioning

confidence: 99%

An energy consumption evaluation methodology for a manufacturing plant

Cataldo

Scattolini

Tolio

2015

CIRP Journal of Manufacturing Science and Technology

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“…used for an energy-efficient planning methodology called EnergyBlocks (Weinert et al, 2011). Other relevant energy saving techniques also used both energy data and operational states (Du et al, 2011; Kara and Li, 2011; Pang et al, 2011b).…”

Section: Introductionmentioning

confidence: 99%

Classification of energy consumption patterns for energy audit and machine scheduling in industrial manufacturing systems

Cao

Pang

Gan

et al. 2012

Transactions of the Institute of Measurement and Control

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To reduce energy consumption for sustainable and energy-efficient manufacturing, continuous energy monitoring and process tracking of industrial machines are essential. In this paper, we introduce a novel approach to reduce the number of required sensors in process tracking by identifying the operational states based on real-time energy data. Finite-state machines are used to model the engineering processes, and a two-stage framework for online classification of real-time energy measurement data in terms of machine operational states is proposed for energy audit and machine scheduling. The first stage uses advanced signal processing techniques to reduce noise while preserving important features, and the second stage uses intelligent pattern recognition algorithms to cluster energy consumption patterns. Our proposed two-stage framework is evaluated on an industrial injection moulding system using a Savizky-Golay filter and a neural network, and our experimental results show a 95.85% accuracy in identification of machine operational states.

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Intelligent energy audit and machine management for energy-efficient manufacturing

Cited by 10 publications

References 4 publications

A Comprehensive Study of Energy Conservation in Electric-Hydraulic Injection-Molding Equipment

A Comprehensive Study of Energy Conservation in Electric-Hydraulic Injection-Molding Equipment

An energy consumption evaluation methodology for a manufacturing plant

Classification of energy consumption patterns for energy audit and machine scheduling in industrial manufacturing systems

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