An operation-mode based simulation approach to enhance the energy conservation of machine tools

Guo, Yansong; Duflou, Joost R.; Qian, Jun; Tang, Hao; Lauwers, Bert

doi:10.1016/j.jclepro.2015.03.097

Cited by 43 publications

(17 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several energy consumption assessment models have been proposed for machining (such as the ones by Kara and Li [2011]; Mori et al [2011]; Mativenga and Rajemi [2011]; Li et al [2013]). Black-box approaches empirically correlate the input machining parameters to the energy demand, whereas bottomup approaches divide the total energy consumption into the contributions attributed to machine states and/or components (Guo et al 2015). In the present research, the specific energy consumption (SEC) was related to the material removal rate (MRR) by applying the model shown in equation (6), proposed by Li and Kara (2011).…”

Section: Machiningmentioning

confidence: 99%

Influence of Material‐Related Aspects of Additive and Subtractive Ti‐6Al‐4V Manufacturing on Energy Demand and Carbon Dioxide Emissions

Priarone¹,

Ingarao²,

Lorenzo³

et al. 2016

J of Industrial Ecology

View full text Add to dashboard Cite

SummaryThe additive manufacturing of metal parts represents a promising process that could be used alongside traditional manufacturing methods. The research scenario in this field is still largely unexplored, as far as the technological solutions adopted to integrate different processes are concerned and in terms of environmental and economic impact assessment. In this article, an electron beam melting (EBM) process and a machining process have been analyzed and compared using a cradle-to-grave life cycle-based approach. The production of components made of the Ti-6Al-4V alloy has been assumed as a case study. The proposed methodology is able to account for all of the main factors of influence on energy demand and carbon dioxide emissions when the component shape is varied. The results prove that, besides the direct energy intensity of the manufacturing processes, the impacts related to material usage are usually dominant. Therefore, when complex geometries have to be manufactured, the additive manufacturing approach could be the best strategy, if it enables a larger amount of material savings than conventional machining. Vice versa, when a small amount of material has to be machined off, the high energy intensity of an EBM process has a negative effect on the performance of the process.

show abstract

Section: Machiningmentioning

confidence: 99%

Influence of Material‐Related Aspects of Additive and Subtractive Ti‐6Al‐4V Manufacturing on Energy Demand and Carbon Dioxide Emissions

Priarone¹,

Ingarao²,

Lorenzo³

et al. 2016

J of Industrial Ecology

View full text Add to dashboard Cite

show abstract

“…To meet these requirements was selected measuring instrument [Huzlik 2013]developed by the project FR-TI3 / 655 -Eco-design in the construction of machine tools. Measurements carried out both on the heel of the machine, and directly between the frequency converter and motor of linear axes or spindle.…”

Section: Demonstratormentioning

confidence: 99%

“…Same situation is also noticeable in processing and manufacturing.CNC machine tools are currently constituting the dominant market share of machine tools and at the same rate are represented in manufacturing companies engaged in chip machining.In order to allow these machines economically and efficiently operate, it is necessary to monitor their consumption [Augste 2013]to be able to predict certain phenomena which have demand on energy profile significant of given machine tool. It is thus necessary to have some available peripherals that allow the monitoring of energy consumption.Monitoring and assessment of the energy profile of a machine tool is possible only at the time when the machine is manufactured, assembled and put into operation.Methods of evaluation are different, for example, by life cycle assessment method [Krbalova 2015], [Iskandirova 2013]. The problem comes at the moment when the machine is already manufactured and does not meet the energy profile requirements that are requested.For this reason it is necessary to simulate and predict energy consumption of machine tool.…”

Section: Introductionmentioning

confidence: 99%

“…The problem comes at the moment when the machine is already manufactured and does not meet the energy profile requirements that are requested.For this reason it is necessary to simulate and predict energy consumption of machine tool. Fairly frequently is a possible method of predicting energy consumption by realization of using previously measured characteristics [Hadas 2014] from which are formed polynoms, serving as a source of input data for simulation.This is based on the creation of libraries with power profiles [Guo 2015], [Lv 2016].One of the possible principles how to predict an energy-profile is for example using Generalized Stochastic Petri Nets [Xie 2016]or Artificial Neural Network [Kant 2015]. An important element of determining the energy profile of the machine is its behavior during machining [Aluntas 2016].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Verification of Prediction Method for Energy Consumption of Machine Tool Feed Axes

Synek¹,

Tůma²,

Tůma³

2016

MM SJ

View full text Add to dashboard Cite

Energy efficiency of electrical appliances is highly debated topic at present.This topic is transferred especially in industries where are the effects of savings much more significant due to higher energy consumption.In the case of machine tools is at present energy efficiency also a hot topic,basedon the Kyoto Protocol and the European Commission Regulation of energy appliances eco-design.Machine tool manufacturers already responses to this situation by using more efficient components (motors, pumps,etc...).This article focuses especially on determining the energy profile of the machine tool at the moment where the machine is not manufactured.It is used a method allows to simulate the energy profile of the machine tool. This is verified by measurement on the test device. Realized measurement was done under different loads of clamping table and under different feed rates. Average percentual error was achieved below ten percent limit.

show abstract

“…Consequently, energy conservation and emissions reduction are attracting increasing attention. Recent related literatures on this topic of manufacturing production include (Guo et al, 2015;Lin et al, 2015;Liu et al, 2014;Wang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm

Gao

et al. 2016

Journal of Cleaner Production

View full text Add to dashboard Cite

Energy savings have become an essential consideration in sustainable manufacturing projects due to the associated environmental impacts and constraints on carbon emissions. In the past, machining operations primarily examined technological consideration (e.g., machining quality) and neglected energy consumption. Therefore, this paper investigates an energy-efficient multi-pass turning operation problem and establishes a multi-objective multi-pass turning operations model. Energy consumption and machining quality are both considered in this problem. Although several models of this problem have considered these criteria, the objectives are usually combined into a single objective using a weighted sum approach, which results in poor non-dominated solutions. To obtain high quality trade-offs between the two challenging objectives, a novel multi-objective backtracking search algorithm is proposed to solve this multi-objective optimization problem. To verify the feasibility and validity of the proposed algorithm, it is compared with other classical multi-objective metaheuristics on multi-objective multi-pass turning operations. This study's experimental results demonstrate that the proposed algorithm significantly outperforms other algorithms for this optimization problem, which is a significant result regarding practical application.

show abstract

An operation-mode based simulation approach to enhance the energy conservation of machine tools

Cited by 43 publications

References 16 publications

Influence of Material‐Related Aspects of Additive and Subtractive Ti‐6Al‐4V Manufacturing on Energy Demand and Carbon Dioxide Emissions

Influence of Material‐Related Aspects of Additive and Subtractive Ti‐6Al‐4V Manufacturing on Energy Demand and Carbon Dioxide Emissions

Verification of Prediction Method for Energy Consumption of Machine Tool Feed Axes

Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm

Contact Info

Product

Resources

About