On the public citation graph

A systematic literature review on machine tool energy consumption

https://doi.org/10.1016/j.jclepro.2020.123125
0 signed · 391 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-32098-4_11openalex-snapshot
Modelling and Verification of Energy Consumption in CNC Milling
inferredcites →https://doi.org/10.1007/978-3-642-19692-8openalex-snapshot
Glocalized Solutions for Sustainability in Manufacturing
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_44openalex-snapshot
Modelling Machine Tools for Self-Optimisation of Energy Consumption
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_45openalex-snapshot
Energy-Efficient Machine Tools through Simulation in the Design Process
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_46openalex-snapshot
Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_47openalex-snapshot
An Investigation into Fixed Energy Consumption of Machine Tools
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_48openalex-snapshot
Energy Efficiency Measures for the Design and Operation of Machine Tools: An Axiomatic Approach
inferredcites →https://doi.org/10.1007/978-3-642-19692-8_49openalex-snapshot
Analyzing Energy Consumption of Machine Tool Spindle Units and Identification of Potential for Improvements of Efficiency
inferredcites →https://doi.org/10.1007/978-3-642-29069-5openalex-snapshot
Leveraging Technology for a Sustainable World
inferredcites →https://doi.org/10.1007/978-3-642-29069-5_40openalex-snapshot
Simulation of the Energy Consumption of Machine Tools for a Specific Production Task
inferredcites →https://doi.org/10.1007/978-3-642-29069-5_41openalex-snapshot
Energy Efficient Cooling Systems for Machine Tools
inferredcites →https://doi.org/10.1007/978-3-642-29069-5_42openalex-snapshot
Simulation and Prediction of Process-Oriented Energy Consumption of Machine Tools
inferredcites →https://doi.org/10.1007/978-3-642-40352-1_3openalex-snapshot
Energy-Efficient Machining via Energy Data Integration
inferredcites →https://doi.org/10.1007/978-981-4451-48-2openalex-snapshot
Re-engineering Manufacturing for Sustainability
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_31openalex-snapshot
Energy Efficient Solutions for Hydraulic Units of Machine Tools
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_32openalex-snapshot
Impact of Machine Tools on the Direct Energy and Associated Carbon Emissions for a Standardized NC Toolpath
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_33openalex-snapshot
Modeling Energy States in Machine Tools: An Automata Based Approach
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_37openalex-snapshot
Analysis of Energy Consumption in CNC Machining Centers and Determination of Optimal Cutting Conditions
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_38openalex-snapshot
Increasing the Energy Efficiency in Metal Cutting Manufacturing through a Demand Based Coolant Filtration
inferredcites →https://doi.org/10.1007/978-981-4451-48-2_41openalex-snapshot
A Universal Hybrid Energy Consumption Model for CNC Machining Systems
inferredcites →https://doi.org/10.1007/bf02654511openalex-snapshot
On the closed form mechanistic modeling of milling: Specific cutting energy, torque, and power
inferredcites →https://doi.org/10.1007/s00170-013-5017-7openalex-snapshot
Modeling and impact factors analyzing of energy consumption in CNC face milling using GRASP gene expression programming
inferredcites →https://doi.org/10.1007/s00170-013-5227-zopenalex-snapshot
Optimization of cutting parameters for energy saving
inferredcites →https://doi.org/10.1007/s00170-013-5547-zopenalex-snapshot
Multi-objective optimization of machining parameters considering energy consumption
inferredcites →https://doi.org/10.1007/s00170-013-5551-3openalex-snapshot
Energy efficiency techniques in machining process: a review
inferredcites →https://doi.org/10.1007/s00170-014-5756-0openalex-snapshot
Energy-efficient machining systems: a critical review
inferredcites →https://doi.org/10.1007/s00170-014-6101-3openalex-snapshot
Assessment of cutting energy consumption and energy efficiency in machining of 4140 steel
inferredcites →https://doi.org/10.1007/s00170-014-6763-xopenalex-snapshot
Study on optimized principles of process parameters for environmentally friendly machining austenitic stainless steel with high efficiency and little energy consumption
inferredcites →https://doi.org/10.1007/s00170-015-7477-4openalex-snapshot
Evaluation on models of calculating energy consumption in metal cutting processes: a case of external turning process
inferredcites →https://doi.org/10.1007/s00170-015-7679-9openalex-snapshot
Optimization of cutting parameters to minimize energy consumption during turning of AISI 1018 steel at constant material removal rate using robust design
inferredcites →https://doi.org/10.1007/s00170-015-8033-yopenalex-snapshot
An integrated model for predicting the specific energy consumption of manufacturing processes
inferredcites →https://doi.org/10.1007/s00170-015-8133-8openalex-snapshot
Energy modeling for variable material removal rate machining process: an end face turning case
inferredcites →https://doi.org/10.1007/s00170-016-8441-7openalex-snapshot
Modelling and optimization of energy consumption for feature based milling
inferredcites →https://doi.org/10.1007/s00170-016-8952-2openalex-snapshot
Energy consumption modeling of machining transient states based on finite state machine
inferredcites →https://doi.org/10.1007/s00170-016-9497-0openalex-snapshot
An energy consumption optimization strategy for CNC milling
inferredcites →https://doi.org/10.1007/s00170-016-9654-5openalex-snapshot
A simulation approach for predicting energy use during general milling operations
inferredcites →https://doi.org/10.1007/s00170-016-9868-6openalex-snapshot
Energy consumption characteristics of turn-mill machining
inferredcites →https://doi.org/10.1007/s00170-016-9929-xopenalex-snapshot
An improved cutting power model of machine tools in milling process
inferredcites →https://doi.org/10.1007/s00170-017-0342-xopenalex-snapshot
An investigation on the impact of toolpath strategies and machine tool axes configurations on electrical energy demand in mechanical machining
inferredcites →https://doi.org/10.1007/s00170-017-1521-5openalex-snapshot
Plastic deformation-based energy consumption modelling for machining
inferredcites →https://doi.org/10.1007/s00170-017-1545-xopenalex-snapshot
A new multi-source and dynamic energy modeling method for machine tools
inferredcites →https://doi.org/10.1007/s00170-018-1588-7openalex-snapshot
Development and analysis of energy consumption map for high-speed machining of Al 6061-T6 alloy
inferredcites →https://doi.org/10.1007/s00170-018-1647-0openalex-snapshot
Optimization of cutting parameters with a sustainable consideration of electrical energy and embodied energy of materials
inferredcites →https://doi.org/10.1007/s00170-018-1668-8openalex-snapshot
Multi-responses optimization in dry turning of a stainless steel as a key factor in minimum energy
inferredcites →https://doi.org/10.1007/s00170-018-1848-6openalex-snapshot
Optimization of machining economics and energy consumption in face milling operations
inferredcites →https://doi.org/10.1007/s00170-018-1885-1openalex-snapshot
Identification of the optimum cutting parameters in intermittent hard turning with specific cutting energy, damage equivalent stress, and surface roughness considered
inferredcites →https://doi.org/10.1007/s00170-018-2269-2openalex-snapshot
Comprehensive effects of tool paths on energy consumption, machining efficiency, and surface integrity in the milling of alloy cast Iron
inferredcites →https://doi.org/10.1007/s00170-018-2550-4openalex-snapshot
A practical energy consumption prediction method for CNC machine tools: cases of its implementation
inferredcites →https://doi.org/10.1007/s10845-012-0723-9openalex-snapshot
Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing
inferredcites →https://doi.org/10.1007/s10845-013-0812-4openalex-snapshot
A quantitative approach to analyze carbon emissions of CNC-based machining systems
inferredcites →https://doi.org/10.1007/s10845-013-0851-xopenalex-snapshot
A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process
inferredcites →https://doi.org/10.1007/s10845-014-0894-7openalex-snapshot
Machining activity extraction and energy attributes inheritance method to support intelligent energy estimation of machining process
inferredcites →https://doi.org/10.1007/s10845-016-1233-yopenalex-snapshot
A comprehensive approach to parameters optimization of energy-aware CNC milling
inferredcites →https://doi.org/10.1007/s11740-013-0492-0openalex-snapshot
Energy-efficient manufacturing on machine tools by machining process improvement
inferredcites →https://doi.org/10.1007/s12541-015-0347-zopenalex-snapshot
An analysis framework for characterization of electrical power data in machining
inferredcites →https://doi.org/10.1007/s12541-016-0188-4openalex-snapshot
Multi-objective optimization of turning process of hardened material for energy efficiency
inferredcites →https://doi.org/10.1007/s12541-018-0074-3openalex-snapshot
Optimization of Cutting Parameters for Minimizing Environmental Impact: Considering Energy Efficiency, Noise Emission and Economic Dimension
inferredcites →https://doi.org/10.1007/s40684-014-0023-2openalex-snapshot
Simulation-based energy usage profiling of machine tool at the component level
inferredcites →https://doi.org/10.1007/s40684-015-0001-3openalex-snapshot
Optimal workpiece orientation to reduce the energy consumption of a milling process
inferredcites →https://doi.org/10.1007/s40684-016-0001-yopenalex-snapshot
Modeling and parameter optimization for cutting energy reduction in MQL milling process
inferredcites →https://doi.org/10.1007/s40684-017-0001-6openalex-snapshot
Analysis of new, energy-efficient hydraulic unit for machine tools
inferredcites →https://doi.org/10.1016/j.advengsoft.2017.08.014openalex-snapshot
A multi-granularity NC program optimization approach for energy efficient machining
inferredcites →https://doi.org/10.1016/j.apenergy.2017.05.180openalex-snapshot
Development of dynamic energy benchmark for mass production in machining systems for energy management and energy-efficiency improvement
inferredcites →https://doi.org/10.1016/j.bmc.2010.04.023openalex-snapshot
Bacterial transferase MraY inhibitors: Synthesis and biological evaluation
inferredcites →https://doi.org/10.1016/j.cirp.2010.03.042openalex-snapshot
Automated energy monitoring of machine tools
inferredcites →https://doi.org/10.1016/j.cirp.2011.03.018openalex-snapshot
Unit process energy consumption models for material removal processes
inferredcites →https://doi.org/10.1016/j.cirp.2011.03.088openalex-snapshot
Calculation of optimum cutting parameters based on minimum energy footprint
inferredcites →https://doi.org/10.1016/j.cirp.2011.03.099openalex-snapshot
A study on energy efficiency improvement for machine tools
inferredcites →https://doi.org/10.1016/j.cirp.2012.03.103openalex-snapshot
Development of an energy consumption monitoring procedure for machine tools
inferredcites →https://doi.org/10.1016/j.cirp.2012.05.002openalex-snapshot
Towards energy and resource efficient manufacturing: A processes and systems approach
inferredcites →https://doi.org/10.1016/j.cirp.2013.03.139openalex-snapshot
Design and control of a novel hybrid feed drive for high performance and energy efficient machining
inferredcites →https://doi.org/10.1016/j.cirp.2015.04.056openalex-snapshot
Energy efficient machining of Ti–6Al–4V
inferredcites →https://doi.org/10.1016/j.cirp.2017.04.015openalex-snapshot
Dynamic feature based adaptive process planning for energy-efficient NC machining
inferredcites →https://doi.org/10.1016/j.cirp.2018.03.015openalex-snapshot
A hybrid approach to integrate machine learning and process mechanics for the prediction of specific cutting energy
inferredcites →https://doi.org/10.1016/j.cirpj.2011.04.002openalex-snapshot
Lightweight components for energy-efficient machine tools
inferredcites →https://doi.org/10.1016/j.cirpj.2011.06.017openalex-snapshot
Structure principles of energy efficient machine tools
inferredcites →https://doi.org/10.1016/j.cirpj.2012.03.007openalex-snapshot
Energy efficient process planning for CNC machining
inferredcites →https://doi.org/10.1016/j.cirpj.2012.04.001openalex-snapshot
Integrated methodology for the evaluation of the energy- and cost-effectiveness of machine tools
inferredcites →https://doi.org/10.1016/j.cirpj.2017.05.003openalex-snapshot
Evaluation and modeling of the energy demand during machining
inferredcites →https://doi.org/10.1016/j.cirpj.2017.08.003openalex-snapshot
A methodology for online visualization of the energy flow in a machine tool
inferredcites →https://doi.org/10.1016/j.enconman.2018.01.005openalex-snapshot
Optimising the machining time, deviation and energy consumption through a multi-objective feature sequencing approach
inferredcites →https://doi.org/10.1016/j.enconman.2018.07.030openalex-snapshot
Energy modeling method of machine-operator system for sustainable machining
inferredcites →https://doi.org/10.1016/j.energy.2015.10.074openalex-snapshot
Methods for evaluation of energy efficiency of machine tools
inferredcites →https://doi.org/10.1016/j.energy.2016.02.126openalex-snapshot
The Total Energy Efficiency Index for machine tools
inferredcites →https://doi.org/10.1016/j.energy.2017.01.039openalex-snapshot
Minimising the machining energy consumption of a machine tool by sequencing the features of a part
inferredcites →https://doi.org/10.1016/j.energy.2017.01.047openalex-snapshot
A novel approach for acquiring the real-time energy efficiency of machine tools
inferredcites →https://doi.org/10.1016/j.energy.2017.05.110openalex-snapshot
Energy consumption in machining: Classification, prediction, and reduction strategy
inferredcites →https://doi.org/10.1016/j.energy.2017.07.039openalex-snapshot
A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking
inferredcites →https://doi.org/10.1016/j.energy.2017.07.120openalex-snapshot
Therblig-embedded value stream mapping method for lean energy machining
inferredcites →https://doi.org/10.1016/j.energy.2017.08.032openalex-snapshot
Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed
inferredcites →https://doi.org/10.1016/j.energy.2017.10.030openalex-snapshot
Energy benchmarking rules in machining systems
inferredcites →https://doi.org/10.1016/j.energy.2018.01.046openalex-snapshot
Minimising the energy consumption of tool change and tool path of machining by sequencing the features
inferredcites →https://doi.org/10.1016/j.energy.2018.06.096openalex-snapshot
Energy efficiency evaluation for machining systems through virtual part
inferredcites →https://doi.org/10.1016/j.ijmecsci.2018.07.033openalex-snapshot
Specific cutting energy modeling for turning nickel-based Nimonic 90 alloy under MQL condition
inferredcites →https://doi.org/10.1016/j.ijpe.2016.12.012openalex-snapshot
Pareto fronts of machining parameters for trade-off among energy consumption, cutting force and processing time
inferredcites →https://doi.org/10.1016/j.jclepro.2010.01.025openalex-snapshot
Sustainable machining: selection of optimum turning conditions based on minimum energy considerations
inferredcites →https://doi.org/10.1016/j.jclepro.2010.10.010openalex-snapshot
Evaluating the use phase energy requirements of a machine tool system
inferredcites →https://doi.org/10.1016/j.jclepro.2011.10.033openalex-snapshot
A modeling method of task-oriented energy consumption for machining manufacturing system
inferredcites →https://doi.org/10.1016/j.jclepro.2012.01.013openalex-snapshot
An on-line approach for energy efficiency monitoring of machine tools
inferredcites →https://doi.org/10.1016/j.jclepro.2012.05.005openalex-snapshot
Optimization of cutting conditions for sustainable machining of PEEK-CF30 using TiN tools
inferredcites →https://doi.org/10.1016/j.jclepro.2012.08.008openalex-snapshot
Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites
inferredcites →https://doi.org/10.1016/j.jclepro.2012.10.015openalex-snapshot
Modelling of direct energy requirements in mechanical machining processes
inferredcites →https://doi.org/10.1016/j.jclepro.2013.02.030openalex-snapshot
Multi-objective optimization of milling parameters – the trade-offs between energy, production rate and cutting quality
inferredcites →https://doi.org/10.1016/j.jclepro.2013.02.039openalex-snapshot
Energy requirements evaluation of milling machines based on thermal equilibrium and empirical modelling
inferredcites →https://doi.org/10.1016/j.jclepro.2013.03.049openalex-snapshot
Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA
inferredcites →https://doi.org/10.1016/j.jclepro.2013.09.055openalex-snapshot
Therblig-based energy supply modeling of computer numerical control machine tools
inferredcites →https://doi.org/10.1016/j.jclepro.2013.10.025openalex-snapshot
Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel
inferredcites →https://doi.org/10.1016/j.jclepro.2014.01.036openalex-snapshot
Impact of un-deformed chip thickness on specific energy in mechanical machining processes
inferredcites →https://doi.org/10.1016/j.jclepro.2014.03.061openalex-snapshot
Empirical power-consumption model for material removal in three-axis milling
inferredcites →https://doi.org/10.1016/j.jclepro.2014.04.065openalex-snapshot
Critical factors in energy demand modelling for CNC milling and impact of toolpath strategy
inferredcites →https://doi.org/10.1016/j.jclepro.2014.05.099openalex-snapshot
Empirical models for specific energy consumption and optimization of cutting parameters for minimizing energy consumption during turning
inferredcites →https://doi.org/10.1016/j.jclepro.2014.07.073openalex-snapshot
Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining
inferredcites →https://doi.org/10.1016/j.jclepro.2014.09.058openalex-snapshot
A method for predicting the energy consumption of the main driving system of a machine tool in a machining process
inferredcites →https://doi.org/10.1016/j.jclepro.2014.12.017openalex-snapshot
Optimization of cutting parameters using Response Surface Method for minimizing energy consumption and maximizing cutting quality in turning of AISI 6061 T6 aluminum
inferredcites →https://doi.org/10.1016/j.jclepro.2015.01.058openalex-snapshot
Intelligent energy based status identification as a platform for improvement of machine tool efficiency and effectiveness
inferredcites →https://doi.org/10.1016/j.jclepro.2015.03.097openalex-snapshot
An operation-mode based simulation approach to enhance the energy conservation of machine tools
inferredcites →https://doi.org/10.1016/j.jclepro.2015.05.049openalex-snapshot
A hybrid approach to energy consumption modelling based on cutting power: a milling case
inferredcites →https://doi.org/10.1016/j.jclepro.2015.05.093openalex-snapshot
Energy consumption model and energy efficiency of machine tools: a comprehensive literature review
inferredcites →https://doi.org/10.1016/j.jclepro.2015.06.043openalex-snapshot
Energy conservation in manufacturing operations: modelling the milling process by a new complexity-based evolutionary approach
inferredcites →https://doi.org/10.1016/j.jclepro.2015.07.040openalex-snapshot
Experimental study on energy consumption of computer numerical control machine tools
inferredcites →https://doi.org/10.1016/j.jclepro.2015.09.100openalex-snapshot
An energy modeling and evaluation approach for machine tools using generalized stochastic Petri Nets
inferredcites →https://doi.org/10.1016/j.jclepro.2015.10.094openalex-snapshot
Energy consumption and modeling in precision hard milling
inferredcites →https://doi.org/10.1016/j.jclepro.2016.04.012openalex-snapshot
Energy oriented multi cutting parameter optimization in face milling
inferredcites →https://doi.org/10.1016/j.jclepro.2016.04.071openalex-snapshot
Proper selection of cutting parameters and cutting tool angle to lower the specific cutting energy during high speed machining of 7050-T7451 aluminum alloy
inferredcites →https://doi.org/10.1016/j.jclepro.2016.06.097openalex-snapshot
A method integrating Taguchi, RSM and MOPSO to CNC machining parameters optimization for energy saving
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.029openalex-snapshot
Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.083openalex-snapshot
An interoperable energy consumption analysis system for CNC machining
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.084openalex-snapshot
Decision rules for energy consumption minimization during material removal process in turning
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.086openalex-snapshot
Selection of optimum parameters in multi-pass face milling for maximum energy efficiency and minimum production cost
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.092openalex-snapshot
Analytical approach to establishment of predictive models of power consumption of machine tools' auxiliary units
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.095openalex-snapshot
Impact of feed axis on electrical energy demand in mechanical machining processes
inferredcites →https://doi.org/10.1016/j.jclepro.2016.07.220openalex-snapshot
Optimization of energy consumption response parameters for turning operation using Taguchi method
inferredcites →https://doi.org/10.1016/j.jclepro.2016.08.094openalex-snapshot
Drivers of sustainable cleaner production and sustainable energy options
inferredcites →https://doi.org/10.1016/j.jclepro.2016.08.140openalex-snapshot
Machine based energy-saving tool path generation for five-axis end milling of freeform surfaces
inferredcites →https://doi.org/10.1016/j.jclepro.2016.12.045openalex-snapshot
An investigation into reducing the spindle acceleration energy consumption of machine tools
inferredcites →https://doi.org/10.1016/j.jclepro.2017.01.077openalex-snapshot
A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions
inferredcites →https://doi.org/10.1016/j.jclepro.2017.02.178openalex-snapshot
Simulation-based machining condition optimization for machine tool energy consumption reduction
inferredcites →https://doi.org/10.1016/j.jclepro.2017.03.231openalex-snapshot
Multi-objective optimization of cutting parameters to minimize power consumption in dry turning of stainless steel 316
inferredcites →https://doi.org/10.1016/j.jclepro.2017.04.096openalex-snapshot
Modelling of energy demand from computer numerical control (CNC) toolpaths
inferredcites →https://doi.org/10.1016/j.jclepro.2017.05.013openalex-snapshot
Energy efficiency of milling machining: Component modeling and online optimization of cutting parameters
inferredcites →https://doi.org/10.1016/j.jclepro.2017.05.084openalex-snapshot
Influence factors and operational strategies for energy efficiency improvement of CNC machining
inferredcites →https://doi.org/10.1016/j.jclepro.2017.06.077openalex-snapshot
Multi objective optimization using different methods of assigning weights to energy consumption responses, surface roughness and material removal rate during rough turning operation
inferredcites →https://doi.org/10.1016/j.jclepro.2017.07.175openalex-snapshot
Energy saving opportunities in direct drive machine tool spindles
inferredcites →https://doi.org/10.1016/j.jclepro.2017.07.219openalex-snapshot
Multi-objective optimization of tool path considering efficiency, energy-saving and carbon-emission for free-form surface milling
inferredcites →https://doi.org/10.1016/j.jclepro.2017.08.022openalex-snapshot
Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption
inferredcites →https://doi.org/10.1016/j.jclepro.2017.09.234openalex-snapshot
Integrated energy analysis of cutting process and spindle subsystem in a turning machine
inferredcites →https://doi.org/10.1016/j.jclepro.2018.01.251openalex-snapshot
Cumulative energy demand and environmental impact in sustainable machining of inconel superalloy
inferredcites →https://doi.org/10.1016/j.jclepro.2018.02.239openalex-snapshot
A novel energy consumption model for milling process considering tool wear progression
inferredcites →https://doi.org/10.1016/j.jclepro.2018.04.204openalex-snapshot
A novel method for energy efficiency evaluation to support efficient machine tool selection
inferredcites →https://doi.org/10.1016/j.jclepro.2018.04.265openalex-snapshot
Energy efficiency state identification in milling processes based on information reasoning and Hidden Markov Model
inferredcites →https://doi.org/10.1016/j.jclepro.2018.06.028openalex-snapshot
Empirical power consumption model for rotational axes in machine tools
inferredcites →https://doi.org/10.1016/j.jmapro.2018.08.036openalex-snapshot
Energy consumption characteristics in finish hard milling
inferredcites →https://doi.org/10.1016/j.jmatprotec.2015.09.032openalex-snapshot
Energy consumption and process sustainability of hard milling with tool wear progression
inferredcites →https://doi.org/10.1016/j.jmsy.2013.12.004openalex-snapshot
A novel energy demand modelling approach for CNC machining based on function blocks
inferredcites →https://doi.org/10.1016/j.procir.2012.04.091openalex-snapshot
Optimization of Energy Consumption and Surface Quality in Finish Turning
inferredcites →https://doi.org/10.1016/j.procir.2012.04.092openalex-snapshot
Environmental Impact Characterization of Milling and Implications for Potential Energy Savings in Industry
inferredcites →https://doi.org/10.1016/j.procir.2013.06.045openalex-snapshot
Energy Efficient Manufacturing from Machine Tools to Manufacturing Systems
inferredcites →https://doi.org/10.1016/j.procir.2013.06.046openalex-snapshot
Realizing Energy Reduction of Machine Tools Through a Control-integrated Consumption Graph-based Optimization Method
inferredcites →https://doi.org/10.1016/j.procir.2013.09.023openalex-snapshot
Characterising the Energy Consumption of Machine Tool Actuator Components Using Pattern Recognition
inferredcites →https://doi.org/10.1016/j.procir.2014.01.105openalex-snapshot
A Reduced Model for Energy Consumption Analysis in Milling
inferredcites →https://doi.org/10.1016/j.procir.2014.06.020openalex-snapshot
A Model- and Signal-based Power Consumption Monitoring Concept for Energetic Optimization of Machine Tools
inferredcites →https://doi.org/10.1016/j.procir.2014.07.072openalex-snapshot
Predictive Modeling for Power Consumption in Machining Using Artificial Intelligence Techniques
inferredcites →https://doi.org/10.1016/j.procir.2014.07.083openalex-snapshot
Investigation into Energy Efficiency of Outdated Cutting Machine Tools and Identification of Improvement Potentials to Promote Sustainability
inferredcites →https://doi.org/10.1016/j.procir.2014.07.185openalex-snapshot
Framework of a Machine Tool Configurator for Energy Efficiency
inferredcites →https://doi.org/10.1016/j.procir.2015.01.022openalex-snapshot
How Services Influence the Energy Efficiency of Machine Tools: A Case Study of a Machine Tool Manufacturer
inferredcites →https://doi.org/10.1016/j.procir.2015.01.035openalex-snapshot
Data Collection for Energy Monitoring Purposes and Energy Control of Production Machines
inferredcites →https://doi.org/10.1016/j.procir.2015.02.059openalex-snapshot
Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools
inferredcites →https://doi.org/10.1016/j.procir.2015.02.165openalex-snapshot
Vibration Analysis and Energy Efficiency in Interrupted Face Milling Processes
inferredcites →https://doi.org/10.1016/j.procir.2015.03.002openalex-snapshot
Developing Energy Estimation Model Based on Sustainability KPI of Machine Tools
inferredcites →https://doi.org/10.1016/j.procir.2015.03.085openalex-snapshot
Development of a Discrete Event Model for Energy and Resource Efficient Milling
inferredcites →https://doi.org/10.1016/j.procir.2015.08.081openalex-snapshot
Predictive Modelling for Energy Consumption in Machining Using Artificial Neural Network
inferredcites →https://doi.org/10.1016/j.procir.2015.12.030openalex-snapshot
Multi-level Energy Demand Optimizer System for Machine Tool Controls
inferredcites →https://doi.org/10.1016/j.procir.2016.01.072openalex-snapshot
Online on-board Optimization of Cutting Parameter for Energy Efficient CNC Milling
inferredcites →https://doi.org/10.1016/j.procir.2016.06.034openalex-snapshot
Automatic Assessment of Machine Tool Energy Efficiency and Productivity
inferredcites →https://doi.org/10.1016/j.procir.2016.11.141openalex-snapshot
Energy and Cost Estimation of a Feature-based Machining Operation on HRSA
inferredcites →https://doi.org/10.1016/j.procir.2016.11.162openalex-snapshot
Optimization of Machining Parameters for Improving Energy Efficiency using Integrated Response Surface Methodology and Genetic Algorithm Approach
inferredcites →https://doi.org/10.1016/j.procir.2016.11.167openalex-snapshot
The Automated Evaluation of the Energy Efficiency for Machining Applications based on the Least Energy Demand
inferredcites →https://doi.org/10.1016/j.procir.2016.11.188openalex-snapshot
Multi-objective Tool Sequence Optimization in 2.5D Pocket CNC Milling for Minimizing Energy Consumption and Machining Cost
inferredcites →https://doi.org/10.1016/j.procir.2016.11.202openalex-snapshot
Energy Efficiency in Machine Tool Operation by Online Energy Monitoring Capturing and Analysis
inferredcites →https://doi.org/10.1016/j.procir.2016.11.215openalex-snapshot
Energy-Efficient Cutting Parameters Determination for NC Machining with Specified Machining Accuracy
inferredcites →https://doi.org/10.1016/j.procir.2017.11.041openalex-snapshot
Understanding Energy Consumption in a Machine Tool through Energy Mapping
inferredcites →https://doi.org/10.1016/j.procir.2017.11.081openalex-snapshot
Development of a Structured Algorithm to Identify the Status of a Machine Tool to Improve Energy and Time Efficiencies
inferredcites →https://doi.org/10.1016/j.procir.2017.12.005openalex-snapshot
Optimization Parameters for Energy Efficiency in End milling
inferredcites →https://doi.org/10.1016/j.procir.2017.12.181openalex-snapshot
Simulation-assisted Investigation of the Electric Power Consumption of Milling Processes and Machine Tools
inferredcites →https://doi.org/10.1016/j.procir.2018.03.099openalex-snapshot
Selection of optimum turning parameters based on cooperative optimization of minimum energy consumption and high surface quality
inferredcites →https://doi.org/10.1016/j.procir.2018.03.115openalex-snapshot
Energy Efficiency State Mechanism and Identification in Milling Processes
inferredcites →https://doi.org/10.1016/j.procir.2018.05.081openalex-snapshot
Energy Consumption Characteristics and Influence on Surface Quality in Milling
inferredcites →https://doi.org/10.1016/j.procir.2018.08.300openalex-snapshot
Sustainable Optimization of Dry Turning of Stainless Steel based on Energy Consumption and Machining Cost
inferredcites →https://doi.org/10.1016/j.proeng.2015.12.018openalex-snapshot
Determining the Effective Conditions for Machining Fabrication Procedures Based on the Cutting Process Energy Patterns
inferredcites →https://doi.org/10.1016/j.promfg.2015.09.007openalex-snapshot
Energy Consumption Characteristics in Finish Hard Milling of Tool Steels
inferredcites →https://doi.org/10.1016/j.promfg.2016.12.060openalex-snapshot
Energy Demand Reduction in Milling Based on Component and Toolpath Orientations
inferredcites →https://doi.org/10.1016/j.promfg.2018.07.046openalex-snapshot
Trade-off analysis of tool wear, machining quality and energy efficiency of alloy cast iron milling process
inferredcites →https://doi.org/10.1016/j.rcim.2015.09.014openalex-snapshot
Trade-off analysis between machining time and energy consumption in impeller NC machining
inferredcites →https://doi.org/10.1016/j.rser.2015.03.100openalex-snapshot
Towards greener machine tools – A review on energy saving strategies and technologies
inferredcites →https://doi.org/10.1016/j.watres.2017.08.068openalex-snapshot
Greywater reuse - Assessment of the health risk induced by Legionella pneumophila
inferredcites →https://doi.org/10.1016/s0007-8506(07)61174-3openalex-snapshot
Some Basic Relationships for Identification of the Machining Processes
inferredcites →https://doi.org/10.1016/s0924-0136(02)00930-5openalex-snapshot
Models of machine tool efficiency and specific consumed energy
inferredcites →https://doi.org/10.1080/00207543.2014.944281openalex-snapshot
Estimating machining-related energy consumption of parts at the design phase based on feature technology
inferredcites →https://doi.org/10.1080/00207543.2017.1404160openalex-snapshot
A mechanistic model of energy consumption in milling
inferredcites →https://doi.org/10.1080/00207543.2018.1436787openalex-snapshot
Energy modelling and energy saving strategy analysis of a machine tool during non-cutting status
showing the first 200 of 239

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4566637openalex-extracted
Physics-Informed Multi-Modal Transformers for Machine Tool Energy Consumption Modelling and Prediction
inferred← citeshttps://doi.org/10.2139/ssrn.4682291openalex-extracted
Research on Cutting Energy Consumption Model of Micro-Texture Tools
inferred← citeshttps://doi.org/10.1002/9781119836780.ch11openalex-snapshot
Optimization Methodologies in Intelligent Manufacturing Systems
inferred← citeshttps://doi.org/10.1002/bse.2910openalex-snapshot
Progress and trends in integrating Industry 4.0 within Circular Economy: A comprehensive literature review and future research propositions
inferred← citeshttps://doi.org/10.1002/mawe.202200136openalex-snapshot
Optimization of cutting power and power efficiency during particleboard helical milling
inferred← citeshttps://doi.org/10.1007/978-3-031-28839-5_56openalex-snapshot
A Practical Approach to Realize a Closed Loop Energy Demand Optimization of Milling Machine Tools in Series Production
inferred← citeshttps://doi.org/10.1007/978-3-031-36121-0_23openalex-snapshot
Systematic Literature Review About Energy and Industry 4.0: A Manufacturing Perspective
inferred← citeshttps://doi.org/10.1007/978-3-031-82986-4_9openalex-snapshot
Challenges and Future Perspectives of Sustainable Machining
inferred← citeshttps://doi.org/10.1007/978-3-032-38598-7_11openalex-snapshot
A Material- and Tool State-Aware Dynamic Power Estimation Model for Milling Processes
inferred← citeshttps://doi.org/10.1007/978-981-99-1338-1_6openalex-snapshot
Cutting Force and Energy Modelling in Ultra-Precision Machining of Micro-structures
inferred← citeshttps://doi.org/10.1007/s00170-022-08854-5openalex-snapshot
Energy consumption modelling in milling of variable curved geometry
inferred← citeshttps://doi.org/10.1007/s00170-022-10194-3openalex-snapshot
An estimation methodology of energy consumption for the intelligent CNC machining using STEP-NC
inferred← citeshttps://doi.org/10.1007/s00170-023-10927-yopenalex-snapshot
Optimization techniques for energy efficiency in machining processes—a review
inferred← citeshttps://doi.org/10.1007/s00170-023-12205-3openalex-snapshot
Multi-objective analysis and optimization of energy aspects during dry and MQL turning of unreinforced polypropylene (PP): an approach based on ANOVA, ANN, MOWCA, and MOALO
inferred← citeshttps://doi.org/10.1007/s00170-023-12761-8openalex-snapshot
Investigation of MQL and CNC turning parameters on the machinability of unreinforced polypropylene: study of surface roughness, temperature, and specific cutting energy
inferred← citeshttps://doi.org/10.1007/s00170-024-13100-1openalex-snapshot
A rapid modelling method for machine tool power consumption using transfer learning
inferred← citeshttps://doi.org/10.1007/s00170-024-13687-5openalex-snapshot
Automatic classification of smart sensor data for evaluating machine tool efficiency
inferred← citeshttps://doi.org/10.1007/s00170-024-13951-8openalex-snapshot
Roughness prediction using machine learning models in hard turning: an approach to avoid rework and scrap
inferred← citeshttps://doi.org/10.1007/s00170-024-14600-wopenalex-snapshot
Evolutionary optimization technique to minimize energy consumption for dry turning operation processes
inferred← citeshttps://doi.org/10.1007/s00170-025-15458-2openalex-snapshot
High-speed machining of hardened steel during moldand die production: a critical review toward an Industry 5.0 environment
inferred← citeshttps://doi.org/10.1007/s00170-026-17418-wopenalex-snapshot
An economical model for predicting machine tool energy consumption using machine learning
inferred← citeshttps://doi.org/10.1007/s00170-026-18838-4openalex-snapshot
Electroplasticity-assisted manufacturing of difficult-to-machine materials: Mechanisms, process design, and outlook
inferred← citeshttps://doi.org/10.1007/s10845-022-02030-yopenalex-snapshot
State identification of a 5-axis ultra-precision CNC machine tool using energy consumption data assisted by multi-output densely connected 1D-CNN model
inferred← citeshttps://doi.org/10.1007/s10845-023-02293-zopenalex-snapshot
Intelligent G-code-based power prediction of ultra-precision CNC machine tools through 1DCNN-LSTM-Attention model
inferred← citeshttps://doi.org/10.1007/s11367-026-02635-yopenalex-snapshot
Integrating process replicability in the life cycle assessment of manufacturing fiber-reinforced polymer composites
inferred← citeshttps://doi.org/10.1007/s11465-021-0668-9openalex-snapshot
Coupling evaluation for material removal and thermal control on precision milling machine tools
inferred← citeshttps://doi.org/10.1007/s11465-022-0694-2openalex-snapshot
Energy saving design of the machining unit of hobbing machine tool with integrated optimization
inferred← citeshttps://doi.org/10.1007/s11740-024-01318-7openalex-snapshot
Automatic preload adaptation for rack-and-pinion drives to maximize performance and energy efficiency
inferred← citeshttps://doi.org/10.1007/s11831-022-09841-5openalex-snapshot
The Role of Machine Learning in Tribology: A Systematic Review
inferred← citeshttps://doi.org/10.1007/s11869-023-01329-wopenalex-snapshot
Estimating ground-level PM2.5 using subset regression model and machine learning algorithms in Asian megacity, Dhaka, Bangladesh
inferred← citeshttps://doi.org/10.1007/s12008-024-01789-zopenalex-snapshot
A review on energy efficiency techniques used in machining for combined generation units
inferred← citeshttps://doi.org/10.1007/s12206-021-1201-0openalex-snapshot
Artificial intelligence enabled smart machining and machine tools
inferred← citeshttps://doi.org/10.1007/s12541-025-01334-2openalex-snapshot
Recent Advances in CNC Technology: Toward Autonomous and Sustainable Manufacturing
inferred← citeshttps://doi.org/10.1007/s13369-025-10240-8openalex-snapshot
Characterizing Machining Indicators with Machine Learning Models Under Cellulose Nanocrystal and Graphene-Based Nanofluid Conditions
inferred← citeshttps://doi.org/10.1007/s40430-024-05012-8openalex-snapshot
Prediction model and optimization of energy consumption, cutting force, and surface roughness during machine tool cutting process based on high-order response surface methodology
inferred← citeshttps://doi.org/10.1007/s40430-024-05242-wopenalex-snapshot
A process parameters decision approach considering spindle vibration in helical surface milling for minimising energy consumption and surface roughness value
inferred← citeshttps://doi.org/10.1007/s40436-024-00526-9openalex-snapshot
A mechanism-data hybrid-driven modeling method for predicting machine tool-cutting energy consumption
inferred← citeshttps://doi.org/10.1007/s40436-025-00567-8openalex-snapshot
Green machining technology and application driven by digital intelligence: a review
inferred← citeshttps://doi.org/10.1007/s40436-025-00571-yopenalex-snapshot
Data-driven optimization of frozen sand mold cryogenic cutting process parameters for cutting energy and tool wear reduction
inferred← citeshttps://doi.org/10.1007/s40684-022-00457-5openalex-snapshot
Improving Sustainability Index of Grey Cast Iron Finish Cutting Through High-Speed Dry Turning and Cutting Parameters Optimization Using Taguchi-Based Bayesian Method
inferred← citeshttps://doi.org/10.1007/s40684-025-00816-yopenalex-snapshot
Towards Sustainable Machining: A Comprehensive Review of Energy-Reduction Strategies in Machine Tools
inferred← citeshttps://doi.org/10.1007/s43684-022-00036-0openalex-snapshot
A service-oriented energy assessment system based on BPMN and machine learning
inferred← citeshttps://doi.org/10.1007/s44245-025-00101-xopenalex-snapshot
Development of a novel CNC energy consumption model and energy analyzer software: towards energy-efficient tool pathway strategies in CNC machining
inferred← citeshttps://doi.org/10.1016/j.aei.2023.102101openalex-snapshot
Energy consumption optimisation for machining processes based on numerical control programs
inferred← citeshttps://doi.org/10.1016/j.aej.2025.07.034openalex-snapshot
Optimisation decision of machining process parameters considering milling energy consumption and specific cutting energy
inferred← citeshttps://doi.org/10.1016/j.clman.2026.100005openalex-snapshot
A dynamic energy comparison of additive and traditional manufacturing in sustainable customized product design for fashion through an interactive 3D web-platform
inferred← citeshttps://doi.org/10.1016/j.clrc.2026.100389openalex-snapshot
Influence of customer satisfaction and perceived water service quality on urban water supply management: A systematic review
inferred← citeshttps://doi.org/10.1016/j.compind.2023.103943openalex-snapshot
Predicting electrical power consumption of end milling using a virtual machining energy toolkit (V_MET)
inferred← citeshttps://doi.org/10.1016/j.enconman.2025.119763openalex-snapshot
Energy efficiency improvement for decarbonization in manufacturing industry: A review
inferred← citeshttps://doi.org/10.1016/j.energy.2023.127244openalex-snapshot
A multi-dimension coupling model for energy-efficiency of a machining process
inferred← citeshttps://doi.org/10.1016/j.energy.2025.137220openalex-snapshot
Thermal energy efficiency evaluation of cutting space for dry cutting machine tools: An exergy time-varying graphical method
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113469openalex-snapshot
Sustainable configuration of production lines: Multi-objective energy-efficient optimization with adaptive differential evolution and golden ratio algorithms
inferred← citeshttps://doi.org/10.1016/j.isatra.2023.03.025openalex-snapshot
Time and energy optimal trajectory generation for coverage motion in industrial machines
inferred← citeshttps://doi.org/10.1016/j.jclepro.2020.125367openalex-snapshot
An adaptive policy for on-line Energy-Efficient Control of machine tools under throughput constraint
inferred← citeshttps://doi.org/10.1016/j.jclepro.2021.126249openalex-snapshot
Modelling approach for energy efficiency of machining system based on torque model and angular velocity
inferred← citeshttps://doi.org/10.1016/j.jclepro.2021.127043openalex-snapshot
Investigation of cutting and specific cutting energy in turning of POM-C using a PCD tool: Analysis and some optimization aspects
inferred← citeshttps://doi.org/10.1016/j.jclepro.2021.130295openalex-snapshot
Material removal energy in ultraprecision machining of micro-lens arrays on single crystal silicon by slow tool servo
inferred← citeshttps://doi.org/10.1016/j.jclepro.2024.141356openalex-snapshot
Energy index for evaluating machine tool energy performance: Classification, model and application
inferred← citeshttps://doi.org/10.1016/j.jclepro.2024.141612openalex-snapshot
Sustainability assessment during machining processes: Evidence from the econ-environmental modelling
inferred← citeshttps://doi.org/10.1016/j.jclepro.2024.143406openalex-snapshot
Integrated multi-objective optimization of rough and finish cutting parameters in plane milling for sustainable machining considering efficiency, energy, and quality
inferred← citeshttps://doi.org/10.1016/j.jclepro.2025.145075openalex-snapshot
An integration model enabled deep learning for energy prediction of machine tools
inferred← citeshttps://doi.org/10.1016/j.jclepro.2026.149501openalex-snapshot
Morphology-aware bidirectional state-space model for power prediction in CNC milling
inferred← citeshttps://doi.org/10.1016/j.jhazmat.2021.125399openalex-snapshot
Sustainable and high-efficiency recycling of valuable metals from oily honing ferroalloy scrap via de-oiling and smelting separation
inferred← citeshttps://doi.org/10.1016/j.jii.2026.101080openalex-snapshot
A multi-level multi-source digital twin model for performance enhancement and optimization decision-making in precision milling machines
inferred← citeshttps://doi.org/10.1016/j.jjimei.2022.100122openalex-snapshot
Big data analytics and sustainable tourism: A comprehensive review and network based analysis for potential future research
inferred← citeshttps://doi.org/10.1016/j.jmapro.2023.05.042openalex-snapshot
Assessment of the tribological and wear performance of new duplex AlTiN-based coating systems at high temperatures when threading super duplex stainless steel
inferred← citeshttps://doi.org/10.1016/j.jmapro.2023.08.049openalex-snapshot
Electro-mechanical-thermal energy coupling characteristics analysis and EFMM-based energy modelling for machine tools considering dynamic thermal environment
inferred← citeshttps://doi.org/10.1016/j.jmapro.2024.07.044openalex-snapshot
Comprehensive review of advanced methods for improving the parameters of machining steels
inferred← citeshttps://doi.org/10.1016/j.jmapro.2026.08.033openalex-snapshot
Assessment methodology and cutting parameters-based decision-making for minimizing the environmental impact of machining
inferred← citeshttps://doi.org/10.1016/j.jmrt.2024.12.029openalex-snapshot
Metal flow behavior and energy consumption model during the extrusion process of a 6063 aluminum alloy profile with complex cross-section
inferred← citeshttps://doi.org/10.1016/j.jmsy.2021.05.013openalex-snapshot
Modelling the startup of machine tools for energy efficient multi-sleep control policies
inferred← citeshttps://doi.org/10.1016/j.jmsy.2021.10.002openalex-snapshot
A generalized method for the inherent energy performance modeling of machine tools
inferred← citeshttps://doi.org/10.1016/j.jmsy.2024.05.004openalex-snapshot
Energy flexibility in aerospace manufacturing: The case of low carbon intensity production
inferred← citeshttps://doi.org/10.1016/j.jup.2021.101283openalex-snapshot
A review of global research on private investment in the water sector
inferred← citeshttps://doi.org/10.1016/j.matpr.2021.03.441openalex-snapshot
Performance of hardfaced/heat treated materials under solid particle erosion: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.mfglet.2025.06.006openalex-snapshot
Development of energy consumption monitoring system for machine tools in accordance with ISO14955
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2025.112819openalex-snapshot
Multi-objective optimization of cutting parameters for ultrasonic vibration hard drilling of 42CrMo steel
inferred← citeshttps://doi.org/10.1016/j.procir.2021.01.136openalex-snapshot
Modelling of Energy Consumption for Milling of Circular Geometry
inferred← citeshttps://doi.org/10.1016/j.procir.2021.01.170openalex-snapshot
An Investigation of Energy Efficiency in Finish Turning of EN 353 Alloy Steel
inferred← citeshttps://doi.org/10.1016/j.procir.2023.09.047openalex-snapshot
Industry 4.0 energy monitoring system for multiple production machines
inferred← citeshttps://doi.org/10.1016/j.procir.2024.10.299openalex-snapshot
Enhancing efficiency and environmental performance of laser-cutting machine tools: An explainable machine learning approach
inferred← citeshttps://doi.org/10.1016/j.procir.2024.10.316openalex-snapshot
Analytical modeling and optimization of the environmental impact of milling 42CrMo4 steel
inferred← citeshttps://doi.org/10.1016/j.procir.2026.05.106openalex-snapshot
Simulation-based prediction of electrical load profile in machining processes
inferred← citeshttps://doi.org/10.1016/j.rcradv.2026.200354openalex-snapshot
The life cycle climate impacts of industry-specific machinery technologies: A meta-analysis
inferred← citeshttps://doi.org/10.1016/j.rser.2022.112168openalex-snapshot
Knowledge demands for energy management in manufacturing industry - A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.rser.2025.116073openalex-snapshot
State-of-the-art review of energy consumption in machining operations: Challenges and trends
inferred← citeshttps://doi.org/10.1016/j.susmat.2022.e00416openalex-snapshot
Energy consumption and ecological analysis of sustainable and conventional cutting fluid strategies in machining 15–5 PHSS
inferred← citeshttps://doi.org/10.1016/j.susoc.2024.01.001openalex-snapshot
Sustainable CNC machining operations, a review
inferred← citeshttps://doi.org/10.1038/s41598-025-29397-1openalex-snapshot
COGEniX: an industrial informatics framework for cognitive energy forecasting and carbon-aware scheduling in smart zones
inferred← citeshttps://doi.org/10.1051/e3sconf/202454006015openalex-snapshot
Artificial Intelligence Approaches for Predictive Power Consumption Modeling in Machining-Short Review
inferred← citeshttps://doi.org/10.1080/00207543.2023.2175175openalex-snapshot
Simultaneous control of multiple machines for energy efficiency: a simulation-based approach
inferred← citeshttps://doi.org/10.1080/00207543.2026.2663371openalex-snapshot
ChatEMT: large language model framework for energy-efficient machine tools – review, paradigm, and perspectives
inferred← citeshttps://doi.org/10.1080/0951192x.2022.2028010openalex-snapshot
A new study for prediction and optimisation of energy consumption during high-speed milling
inferred← citeshttps://doi.org/10.1080/0951192x.2024.2314778openalex-snapshot
Toward cyber-physical systems for monitoring and analyzing energy consumption of machine tools
inferred← citeshttps://doi.org/10.1080/10910344.2025.2494798openalex-snapshot
Advancing the energy consumption prediction of the milling machine with small sample sets: a virtual sample generation approach with MC-PSO
inferred← citeshttps://doi.org/10.1080/17480272.2022.2049867openalex-snapshot
Modeling and optimizing the specific cutting energy of medium density fiberboard during the helical up-milling process
inferred← citeshttps://doi.org/10.1088/1742-6596/2540/1/012013openalex-snapshot
Energy efficiency of the Process Planning Design in the scope of Industry 4.0
inferred← citeshttps://doi.org/10.1088/1742-6596/2656/1/012012openalex-snapshot
A Method for Identifying Energy Consumption of Machine Tools Based on Integrated Models
inferred← citeshttps://doi.org/10.1088/1757-899x/1032/1/012036openalex-snapshot
Modeling the basis power in the systems for continuous transport of fluids and bulk materials
inferred← citeshttps://doi.org/10.1108/jeim-07-2021-0293openalex-snapshot
The role of digital technologies to unleash a green recovery: pathways and pitfalls to achieve the European Green Deal
inferred← citeshttps://doi.org/10.1108/tqm-12-2020-0285openalex-snapshot
A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions
inferred← citeshttps://doi.org/10.1109/access.2025.3573400openalex-snapshot
Hybrid Machine Learning for CNC Process Monitoring
inferred← citeshttps://doi.org/10.1109/etfa61755.2024.10710983openalex-snapshot
Representing Property Dependencies within AutomationML Based Digital Twins
inferred← citeshttps://doi.org/10.1109/icecit54077.2021.9641199openalex-snapshot
Comparative Analysis of Continuous Wavelet Transforms on Vibration signal in Bearing Fault Diagnosis of Induction Motor
inferred← citeshttps://doi.org/10.1109/icps65515.2025.11087921openalex-snapshot
Power State Machines: Structuring Black-Box Models for Determining Energy Consumption
inferred← citeshttps://doi.org/10.1109/ieem55944.2022.9989738openalex-snapshot
Economic Production Quantity Model with Energy Consideration
inferred← citeshttps://doi.org/10.1109/mmar70562.2026.11667932openalex-snapshot
Modelling Dynamic and Time-Dependent Power Consumption Using a Black-Box Approach
inferred← citeshttps://doi.org/10.1109/tase.2023.3242198openalex-snapshot
Prediction-Based Power Consumption Monitoring of Industrial Equipment Using Interpretable Data-Driven Models
inferred← citeshttps://doi.org/10.1109/tase.2024.3430394openalex-snapshot
Data-Driven Energy Modeling of Machining Centers Through Automata Learning
inferred← citeshttps://doi.org/10.1109/tie.2023.3257359openalex-snapshot
Energy-Saving Control Strategy for Multisleep States of CNC Machine Tool Considering Components Priority
inferred← citeshttps://doi.org/10.1155/2021/6621235openalex-snapshot
Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview
inferred← citeshttps://doi.org/10.1177/09544062221087547openalex-snapshot
A new approach to increase the environmental sustainability of the discharging process in the over-injection of conduits for bowden cables using automation
inferred← citeshttps://doi.org/10.1177/09596518241247861openalex-snapshot
Energy consumption forecast model of CNC machine tools based on support vector regression optimized by improved artificial hummingbird algorithm
inferred← citeshttps://doi.org/10.12819/2021.18.1.12openalex-snapshot
Qualidade de Serviço no Ensino Superior Público: Uma Adaptação do Servperf
inferred← citeshttps://doi.org/10.18280/ijsdp.170618openalex-snapshot
Classification of Attributes on Green Manufacturing Practices: A Systematic Review
inferred← citeshttps://doi.org/10.20517/gmo.2022.11openalex-snapshot
Perspectives on future research directions in green manufacturing for discrete products
inferred← citeshttps://doi.org/10.20944/preprints202402.1572.v1openalex-snapshot
Modelling of Energy Consumption in Manufacturing: A Practical Framework to Select the Modelling Approach
inferred← citeshttps://doi.org/10.21203/rs.3.rs-10766502/v1openalex-snapshot
Parametric Optimization of CNC Milling of Aluminium 7075 Using the TOPSIS Multi-Criteria Decision-Making Method
inferred← citeshttps://doi.org/10.25100/iyc.v24i02.11377openalex-snapshot
Estudio de consumos energéticos en los centros de mecanizado CNC Haas UMC-750 y Leadwell V-40iT®.
inferred← citeshttps://doi.org/10.29327/aconemi.405707openalex-snapshot
EFICIÊNCIA ENERGÉTICA NO PROCESSO DE FURAÇÃO - UMA REVISÃO
inferred← citeshttps://doi.org/10.3233/faia220425openalex-snapshot
Data-Driven Fault Classification of Induction Motor Based on Recurrence Plot and Deep Convolution Neural Network
inferred← citeshttps://doi.org/10.3390/app11104602openalex-snapshot
Bearing Anomaly Recognition Using an Intelligent Digital Twin Integrated with Machine Learning
inferred← citeshttps://doi.org/10.3390/app11199032openalex-snapshot
Sustainability-Based Analysis of Conventional to High-Speed Machining of Al 6061-T6 Alloy
inferred← citeshttps://doi.org/10.3390/app14178044openalex-snapshot
A Self-Adaptive Neighborhood Search Differential Evolution Algorithm for Planning Sustainable Sequential Cyber–Physical Production Systems
inferred← citeshttps://doi.org/10.3390/app142411499openalex-snapshot
Development of an Original Integrated System for Heat Recovery from Coolant in the Machining Process and Investigation of Its Efficiency
inferred← citeshttps://doi.org/10.3390/coatings14060691openalex-snapshot
Cutting Energy Consumption Modeling by Considering Tool Wear and Workpiece Material Properties for Multi-Objective Optimization of Machine Tools
inferred← citeshttps://doi.org/10.3390/en14217446openalex-snapshot
Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times
inferred← citeshttps://doi.org/10.3390/en16031095openalex-snapshot
Efficient Energy Use in Manufacturing Systems—Modeling, Assessment, and Management Strategy
inferred← citeshttps://doi.org/10.3390/en16166011openalex-snapshot
Parameterized Modeling of the Energy Demand of Machining Processes as a Basis for Reusable Life Cycle Inventory Datasets
inferred← citeshttps://doi.org/10.3390/en17153659openalex-snapshot
A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability
inferred← citeshttps://doi.org/10.3390/met11040565openalex-snapshot
Determination of Energy Consumption during Turning of Hardened Stainless Steel Using Resultant Cutting Force
inferred← citeshttps://doi.org/10.3390/met13020216openalex-snapshot
Cost Estimation Tool for Metallic Parts Made by Casting: A Case Study
inferred← citeshttps://doi.org/10.3390/mi13122206openalex-snapshot
Evaluation of Objective Functions for the Optimal Design of an Assistive Robot
inferred← citeshttps://doi.org/10.3390/pr10122585openalex-snapshot
Low-Carbon and Low-Energy-Consumption Gear Processing Route Optimization Based on Gray Wolf Algorithm
inferred← citeshttps://doi.org/10.3390/s23010488openalex-snapshot
On the Behaviour of an AC Induction Motor as Sensor for Condition Monitoring of Driven Rotary Machines
inferred← citeshttps://doi.org/10.3390/s24072324openalex-snapshot
Cyber–Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era—A Review
inferred← citeshttps://doi.org/10.3390/su13105617openalex-snapshot
Bibliometric Analysis of Specific Energy Consumption (SEC) in Machining Operations: A Sustainable Response
inferred← citeshttps://doi.org/10.3390/su132413918openalex-snapshot
A Novel CNC Milling Energy Consumption Prediction Method Based on Program Parsing and Parallel Neural Network
inferred← citeshttps://doi.org/10.3390/su15097663openalex-snapshot
Low-Carbon-Driven Product Life-Cycle Process Optimization Framework for Manufacturing Equipment
inferred← citeshttps://doi.org/10.3390/su16020847openalex-snapshot
Review on Design Research in CNC Machine Tools Based on Energy Consumption
inferred← citeshttps://doi.org/10.3390/su17136207openalex-snapshot
A Hybrid Energy-Saving Scheduling Method Integrating Machine Tool Intermittent State Control for Workshops
inferred← citeshttps://doi.org/10.3390/su17188390openalex-snapshot
A Novel Collaborative Method to Integrate Carbon Efficiency into Multi-Equipment Operational Coupling for Smart Manufacturing System
inferred← citeshttps://doi.org/10.35168/2176-896x.utp.tuiuti.2021.vol7.n63.pp52-73openalex-snapshot
O Uso da ISO 50001/14001 de Gestão de Energia na Construção da Imagem Socioambiental das Empresas
inferred← citeshttps://doi.org/10.36897/jme/166463openalex-snapshot
Towards Sustainable and Intelligent Machining: Energy Footprint and Tool Condition Monitoring for Media-Assisted Processes
inferred← citeshttps://doi.org/10.37423/2022.edcl514openalex-snapshot
Engenharia: a máquina que constrói o futuro
inferred← citeshttps://doi.org/10.37423/220605964openalex-snapshot
ESTUDO DA VIABILIDADE DO USO DE DUCT BURNERS EM CALDEIRAS DE RECUPERAÇÃO UTILIZANDO A TÉCNICA DE CFD
inferred← citeshttps://doi.org/10.37423/220605966openalex-snapshot
ESTUDO DO DESEMPENHO DE UM MOTOR DE COMBUSTÃO INTERNA TURBOALIMENTADO E COM RESTRIÇÃO DA ENTRADA DE AR
inferred← citeshttps://doi.org/10.37423/220606004openalex-snapshot
Testes de Usabilidade no app CovIdosos – um aplicativo para auxiliar pacientes idosos com Covid-19
inferred← citeshttps://doi.org/10.37423/220606014openalex-snapshot
ESTUDO DE VIABILIDADE PARA AQUECIMENTO DE ÁGUA APROVEITANDO O CALOR REJEITADO DO AR CONDICIONADO
inferred← citeshttps://doi.org/10.37423/220606127openalex-snapshot
ESTUDO DOS SISTEMAS DE INFORMAÇÃO: UM LEVANTAMENTO DOS PRINCIPAIS CONCEITOS APRESENTADOS NA LITERATURA
inferred← citeshttps://doi.org/10.52795/mateca.1792370openalex-snapshot
Optimisation of Energy Consumption in Milling of Inconel 718 Alloy and Prediction Model with Machine Learning
inferred← citeshttps://doi.org/10.7736/jkspe.025.033openalex-snapshot
Development of an International Standards-based Energy Consumption Evaluation System for Enhancing Machine Tool Energy Efficiency
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.