A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking

Cai, Wei; Liu, Fei; Xie, Jun; Liu, Peiji; Tuo, Junbo

doi:10.1016/j.energy.2017.07.039

Cited by 51 publications

(15 citation statements)

References 62 publications

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“…To summarise, the existing models for energy consumption in machine tools can be roughly categorised into three types (Cai et al, 2017): linear models in terms of MRR, detailed parameter models and process oriented models. The conducted review of literature shows that although there are mechanistic models of energy consumption in machine tools at process level, there is currently no such model at machine level.…”

Section: Literature Review: Energy Consumption Models For Machine Toolsmentioning

confidence: 99%

A mechanistic model of energy consumption in milling

Asrai

Newman

Nassehi

2017

International Journal of Production Research

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In this paper, a novel mechanistic model is proposed and validated for the consumption of energy in milling processes. The milling machine is considered as a thermodynamic system. Mechanisms of the significant energy conversion processes within the system are used to construct an explicit expression for the power consumption of the machine as a function of the cutting parameters. This model has been validated experimentally and is shown to be significantly more accurate than popular existing models. A simplified form of the model is also proposed that provides a balance between complexity and accuracy. The novelty of the model is that it maps the flow of energy within a machine tool, based solely on the active mechanisms of energy conversion. As a result, only limited assumptions are made in the model, resulting in an error of less than one percent, verified by experiments. This accurate model can be used to substantially reduce energy consumption in milling processes at machine and factory levels leading to massive cost savings and reduction of environmental impact of numerous industries. The generality of the modelling method makes it applicable to other types of machine tools with minimal adjustments.

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Section: Literature Review: Energy Consumption Models For Machine Toolsmentioning

confidence: 99%

A mechanistic model of energy consumption in milling

Asrai

Newman

Nassehi

2017

International Journal of Production Research

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“…Lv developed therblig power models for calculating the energy supply to provide a reliable prediction of CNC machine tools [24]. Besides, Cai carried out a series of studies on energy benchmarking, recognized as an effective analytical methodology and management tool to improve energy efficiency and performance, and proposed energy benchmarking rules [25], energy benchmarking frameworks [26], energy modeling [27], etc., laying a crucial foundation for sustainability production.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method of Sustainability Evaluation in Machining Processes

et al. 2019

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In order to quantitatively evaluate and improve the sustainability of machining systems, this paper presents an emergy (the amount of energy consumed in direct and indirect transformations to make a product or service) based sustainability evaluation and improvement method for machining systems, contributing to the improvement of energy efficiency, resource efficiency and environmental performance, and realizing the sustainability development. First, the driver and challenge are studied, and the scope and hypothesis of the sustainable machining system are illustrated. Then, the emergy-based conversion efficiency model is proposed, which are (1) effective emergy utilization rate (EEUR), (2) emergy efficiency of unit product (EEUP) and (3) emergy conversion efficiency (ECE), to measure and evaluate the sustainable machining system from the perspectives of energy, resource and environment. Finally, the proposed model is applied to a vehicle-bridge machining process, and the results show that this paper provides the theoretical and method support for evaluating and improving the sustainable machining processes to decouple the resources and development of the manufacturing industry.

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“…By executing these operations, the power level of machine tools further increases because servo motors and spindle motors are all loaded. Finally, the actual cutting requires a further additional power [13]. Most existing research on reducing the EMT has been focused on actual cutting energy consumption [14] and standby energy consumption [15].…”

Section: Introductionmentioning

confidence: 99%

Optimising the machining time, deviation and energy consumption through a multi-objective feature sequencing approach

Tang

Liu

et al. 2018

Energy Conversion and Management

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Minimising the energy consumption of tool change and tool path of machining by sequencing the features Abstract: A considerable amount of energy is consumed by machine tools during the run-time operations such as tool change and tool path. The value of this part of energy is affected by the processing sequence of features of a part (PSFP) because the tool path and tool change plan will vary based on the different PSFP. This paper firstly aims to understand the relationship between the PSFP and the energy consumption of tool change and tool path during the feature transitions. Then, a model is introduced for the single objective optimisation problem that minimises the energy consumption of machine tools during the feature transitions which include all the tool path and tool change operations. Finally, optimisation approaches including depth-first search and genetic algorithm are modified and applied to find the optimal PSFP which results in the minimisation of the energy consumption of feature transitions (EFT). In the case study, the optimal and nearoptimal sequences of features, in terms of the minimum EFT, of a 15 features part which is processed by a machining centre have been found. The optimal PSFP achieves a 28.60% EFT reduction, which validates the effectiveness of the developed model and optimisation approaches. Besides, a 27.95% time reduction of feature transitions benefits from the EFT minimisation.

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A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking

Cited by 51 publications

References 62 publications

A mechanistic model of energy consumption in milling

A mechanistic model of energy consumption in milling

A Novel Method of Sustainability Evaluation in Machining Processes

Optimising the machining time, deviation and energy consumption through a multi-objective feature sequencing approach

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