Energy Efficient Manufacturing from Machine Tools to Manufacturing Systems

Salonitis, Konstantinos; Ball, Peter D.

doi:10.1016/j.procir.2013.06.045

Cited by 136 publications

(76 citation statements)

References 16 publications

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“…of cutting tool in milling and drilling (mm), n = spindle speed (RPM), Em= energy consumption per unit material volume(kWh/mm 3 ), MRV = material removal volume (mm 3 ) Also, the total energy required by a machine tool for performing a specific process can be estimated using the equation as given below [7]: (5) where,Eprocess is the energy required for the physical process to occur and Eauxiliary is the additional energy consumed from the machine tool by the auxiliary devices. The process energy can be estimated from the specific cutting energy and it depends on the mechanics of the process, therefore, it depends on the process parameters [7]. The auxiliary energy can be further analyzed to the energy that is a function of the machine load and the energy consumed regardless whether the machine cuts or is idle (background energy) as can be seen in the following equation:…”

Section: Energy Aspects In Metal Machiningmentioning

confidence: 99%

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Energy Consideration in Metal Machining

Desai¹,

Chopra²,

Pawade³

2015

Int. Jour. Intel. Elec. Sys.

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We cannot say that present day machining processes are clean. Current trends in the manufacturing sector will not be acceptable in the future. This will an arise need for extensive research and development work necessary to meet the environmental concern. Although research on promising green energy technologies manage to supply partially for current machining systems; the high energy-efficient machining systems that demand less energy remain important and highly desirable. The energy-efficient machining system requires a comprehensive understanding as well as optimization of energy consumption. This paper focuses upon the energy requirement during actual metal machining. The first part explains about the basics of energy in machining and the flow of energy in a production line. In the later part, two energy models are described that shows dependence of energy consumption in machining process upon the operating parameters and set-up parameters. Effects of these different parameters on specific energy consumption are also summarized. Finally, a brief introduction to few energy optimization techniques is given.

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Section: Energy Aspects In Metal Machiningmentioning

confidence: 99%

“…The background energy depends on the specific machine tool used and can be determined experimentally through an energy audit.The load energy depends on the workpiece characteristics (weight, material, size and properties), the process parameters selected and the cutting tool used [7].…”

Section: Energy Aspects In Metal Machiningmentioning

confidence: 99%

Energy Consideration in Metal Machining

Desai¹,

Chopra²,

Pawade³

2015

Int. Jour. Intel. Elec. Sys.

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“…Triggered by the necessity to improve the energy efficiency and environmental performance of the manufacturing industry, energy modeling [11][12][13][14][15][16], energy-efficiency improvement [17][18][19][20][21][22] and carbon-emission reduction [23,24] of the manufacturing industry have been studied. Experiments show that power peaks will be caused by state transitions during the machining process [25,26], as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

et al. 2017

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Abstract:Energy demand modeling of machining processes is the foundation of energy optimization. Energy demand of machining state transition is integral to the energy requirements of the machining process. However, research focus on energy modeling of state transition is scarce. To fill this gap, an energy demand modeling methodology of key state transitions of the turning process is proposed. The establishment of an energy demand model of state transition could improve the accuracy of the energy model of the machining process, which also provides an accurate model and reliable data for energy optimization of the machining process. Finally, case studies were conducted on a CK6153i CNC lathe, the results demonstrating that predictive accuracy with the proposed method is generally above 90% for the state transition cases.

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“…De manera general, estos modelos pueden ser catalogados en dos niveles: nivel de máquina (machine tool level ) y nivel de sistema (manufacturing system level ) [6].…”

Section: Introductionunclassified

PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP

Morillo-Torres¹,

Barber²,

Salido³

2014

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Scheduling problems is one of the core areas in the planning and development of any project, with a wide applicability to real-world situations. Due to the high complexity of these problems, the solving process is often based on metaheuristics techniques, so that the evaluation of these methods is empirical. Therefore benchmarks, which provide a set of test cases to assess the behavior of algorithms, are generated. This paper extends the PSPLIB library. This extension incorporates to each instance of RCPSP (Resource Constrained Project Scheduling Problem), a realistic mathematical model of energy consumption. This proposal provides an alternative to the current trend in the field of optimization and manufacturing that requires the inclusion of components and methods that reduce the environmental impact in the process of decision making. Finally a new optimality criterion is proposed to compare different search techniques. The PSPLIB-ENERGY is available at http://gps. webs.upv.es/psplib-energy/. Resumen Los problemas de scheduling constituyen una de lasáreas centrales en la planificación y desarrollo de cualquier proyecto, con una gran aplicabilidad a situaciones del mundo real. Debido a la gran complejidad que habitualmente presentan estos problemas, su resolución suele basarse en métodos metaheurísticos de optimización, de forma que la evaluación de estos métodos es empírica. Por esta razón se generan benchmarks, que proveen de un conjunto de casos de prueba que permiten evaluar el comportamiento de los algoritmos que se desarrollan. En este artículo se extiende la librería PSPLIB. Esta extensión consiste en incorporar a cada instancia del RCPSP (Resource Constrained Project Scheduling Problem), un modelo matemático realista de consumo de energía. Esta propuesta brinda una alternativa a la tendencia actual en el campo de la optimización y la manufactura que demanda la inclusión de componentes y métodos que reduzcan el impacto ambiental en el proceso de toma de decisiones. Finalmente se propone un nuevo criterio de optimalidad para comparar las diferentes técnicas de búsqueda. La PSPLIB-ENERGY está disponible en http://gps.webs.upv.es/psplib-energy/.

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Energy Efficient Manufacturing from Machine Tools to Manufacturing Systems

Cited by 136 publications

References 16 publications

Energy Consideration in Metal Machining

Energy Consideration in Metal Machining

Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP

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