Modelling Machine Tools for Self-Optimisation of Energy Consumption

Schmitt, Robert; Bonefeld, Ralf

doi:10.1007/978-3-642-19692-8_44

Cited by 18 publications

(5 citation statements)

References 3 publications

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“…Therefore reducing the unproductive idle time during a manufacturing operation contributes to an increase in overall energy efficiency. Using functional states for common suppliers, Schmitt et al [176] proposed a self-optimization model to control the energy consumption depending on the usage profile of a machine tool, automatically switching to the most optimal production mode.…”

Section: 422mentioning

confidence: 99%

Towards energy and resource efficient manufacturing: A processes and systems approach

Duflou¹,

et al. 2012

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Section: 422mentioning

confidence: 99%

Towards energy and resource efficient manufacturing: A processes and systems approach

Duflou¹,

et al. 2012

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“…Based on the results of previous experimental measurements, Schmitt et al [14] concluded that auxiliary equipment (i.e., suppliers) can easily require more energy than the cutting devices. Indeed, the suppliers keep consuming energy during not productive states, because they must be available when the production has to be resumed.…”

Section: Brief Literature Surveymentioning

confidence: 98%

Machine control policies for energy saving in manufacturing

Frigerio

Matta

2013

2013 IEEE International Conference on Automation Science and Engineering (CASE)

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Energy saving in production plants is becoming more and more relevant due to the pressure from governments to contain the environmental impact of manufacturing, and from companies to reduce costs. This work deals with the problem of saving energy in single machines visited by singlepart type with stochastic interarrival times. Specifically, several control policies are proposed for switching the machine off when production is not critical, and on when the part flow has to be resumed. The policy parameter that minimizes the machine energy request is provided analytically for exponentially distributed arrival times, and numerically for general distributions. A numerical comparison with the most common practices in manufacturing is also reported, together with a real case analysis from the automotive sector. © 2013 IEEE

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“…The state control aims at reducing the fixed power consumption, which is required even if the production is not requested. Based on the results of experimental measurements, Schmitt et al [9] deduced that auxiliary equipment-i.e., suppliers-can easily require more energy than necessary. Indeed, the suppliers keep consuming energy during not productive states, because they must be available when the production has to be resumed.…”

Section: Brief Literature Surveymentioning

confidence: 99%

Analysis on Energy Efficient Switching of Machine Tool With Stochastic Arrivals and Buffer Information

Frigerio

Matta

2016

IEEE Trans. Automat. Sci. Eng.

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Energy saving in production plants is becoming more and more relevant due to the pressure from governments to contain the environmental impact of manufacturing, and from companies to reduce costs. One of the measures for saving energy is the implementation of control strategies that reduce energy consumption during the machine idle periods. This paper proposes a framework that integrates different control policies for switching the machine off when production is not critical, and on when the part flow has to be resumed. A general policy is formalized by modelling explicitly the energy consumed at each machine state. The policy parameters that minimize the requested machine expected energy are provided analytically for general distributions. Numerical results are based on data acquired with dedicated experimental measurements on a real machining centre, and a comparison with the most common practices in manufacturing is also reported.Note to Practitioners -The paper analyzes the control problem of switching off-on a machine tool for energy saving during the idle times. Different control policies are investigated pointing out the most significant factors. A mapping of the optimal control policy as a function of warm-up time and mean part arrival time is also provided. An algorithm is described for identifying the optimal control parameters. The results of this research will be useful for a practical implementation of a switching policy for energy saving. This implementation requires the fitting of the distribution modelling the part arrival times, the estimation of the warm-up time, and the estimation of the power adsorbed by the machine in four different states.

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Modelling Machine Tools for Self-Optimisation of Energy Consumption

Cited by 18 publications

References 3 publications

Towards energy and resource efficient manufacturing: A processes and systems approach

Towards energy and resource efficient manufacturing: A processes and systems approach

Machine control policies for energy saving in manufacturing

Analysis on Energy Efficient Switching of Machine Tool With Stochastic Arrivals and Buffer Information

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