Energy Efficiency Of Machine Tools Research Articles

Energy-efficient manufacturing with indoor conditions offset considering weather conditions

• Weather effects on the energy consumption of manufacturing systems are investigated. • Indoor conditions offset strategy is proposed. • For the implementation, the rust and hygiene of workers are considered. • The effect of the thermal deformation is also experimentally investigated. • Power consumption was reduced by 0.9 kW, 33% in August. Many studies have investigated the energy efficiency of machine tools. However, few have investigated that of entire factories. Air-conditioning systems offer considerable potential for reducing energy consumption. The air-conditioning load is affected by weather, indoor heat generation, and target conditions. This study proposes air-conditioning strategy for energy-efficient manufacturing in consideration of these three factors. The proposed strategy is verified through a simulation using a model established from experimental data. The simulation results show that energy consumption can be reduced significantly. Machining tests were also performed to investigate the thermal displacement induced by air conditioning.

Energy Efficiency Optimization for Machining of Wood Plastic Composite

Enhancing energy efficiency is the key to realizing green manufacturing. One major area of interest in this regard is the improvement of energy efficiency of machine tools during the production of building materials. This project focuses on energy efficiency during the spiral milling of wood plastic composites. To this end, a response surface method was adopted to develop a model and establish the relationship between energy efficiency and milling conditions. Analysis of variance based on individual factors as well as two-factor interactions was performed to gauge their effects on energy efficiency. It was found that milling depth was positively correlated to power efficiency, while spiral angle and feed per tooth displayed non-monotonic behavior. An attempt was made to predict milling conditions that will yield the greatest material removal rate and power efficiency. For wood plastic composites subjected to up-milling, it was determined that a feed per tooth of 0.1 mm, milling depth of 1.5 mm, and spiral angle of 70° were ideal. Considering the potential improvements in energy efficiency and surface quality that these process parameters will bring, it is strongly recommended for use in the industrial machining of wood plastic composites.

Indirect Measurement of the Cutting Power Based on Spindle Motor Current

Enhancing energy efficiency of machine tools can significantly improve the environmental performance of machining systems, and acquisition of cutting power is the key to solve this problem. However, the approach that the cutting power is directly measured by the dynamometer can’t be utilized in real life application. In this paper, a cutting power estimation model, based on the inexpensive and non-invasive spindle motor total current and spindle idle current measurement, is proposed for the intermittent cylindrical turning operation. Novel signal processing strategies have been proposed for extracting useful features from the measured signals. Some experiments are performed on a CNC lathe HCK60 for the identification of the load meter constant and the analysis of the estimate error. As a result, it shows the effectiveness of the proposed method for estimation of cutting power, which can enhance the overall productivity of the machining process by optimally selected cutting parameters from the predicted model.

Prediction of energy consumption of numerical control machine tools and analysis of key energy‐saving technologies

AbstractThe objective of this study is to ensure the sustainable development of traditional machinery manufacturing industry under limited conditions of non‐renewable energy, and reduce the environmental pollution caused by high energy consumption of machine tools. Here the energy consumption of numerical control machine tools is analysed, and the relevant energy‐saving model is established. The energy consumption system of the numerical control machinery tools, including the cutting parameters, is classified. The relevant energy consumption prediction model is built to evaluate the influence of different cutting parameters, feed per tooth, and the back cutting depth on the energy consumption of numerical control machine tools. The results show that classifying the energy consumption system of numerical control machine tools can effectively predict the energy consumption of machine tools, which provides theoretical support for the subsequent energy‐saving experiments. Larger cutting parameters will increase the energy consumption of numerical control machine tools, improve the energy efficiency of machine tools at the same time. Thus, reducing the feed per tooth and the back cutting depth can effectively decrease its energy consumption. The results of this study provide data support and guidance for the energy‐saving experiments and practical applications of numerical control machine tools.

Exergy-based Energy Efficiency Evaluation Model for Machine Tools Considering Thermal Stability

Machine tools, as the extensively used basic equipment of manufacturing industry, are characterized by intensive and inefficient energy consumption. With the launch and implementation of ISO 14955-1, energy efficiency has become an important criterion for machine tool evaluation. However, most ongoing research on energy efficiency evaluation of machine tools emphasizes on workpiece material removal energy efficiency and rarely considers energy consumption needed to ensure machining accuracy and accuracy consistency, especially energy consumption for thermal stability control of machine tools. In light of this, an exergy analysis based approach is presented to assess the comprehensive energy efficiency of machine tools, including energy consumption for material removal and thermal stability control. The key performance indexes of exergy efficiency, exergy destruction, and specific exergy consumption are analyzed. The feasibility of the proposed approach was demonstrated by a case study, in which the comprehensive energy efficiency of a machine tool was found to be 21.57% instead of 14.38% of material removal energy efficiency. The proposed method is more effective to evaluate the comprehensive energy efficiency, to support designers to design high-efficient machine tool and users to operate machine tool for green and precision machining.

Exergy efficiency optimization model of motorized spindle system for high-speed dry hobbing

High-speed dry hobbing (HSDH) has been regarded as an environmentally benign gear machining technique. Current research on energy efficiency of machine tool focuses on the energy efficiency for workpiece material removal but rarely involves the energy consumption required to control thermal stability. Due to the fact that thermal effect dominates the machining accuracy and accuracy consistency, especially in the dry machining process, the energy consumption for thermal stability control should be taken as useful energy consumption. In view of this, by taking the motorized spindle system (MSS) as the study objective, which is a core subsystem of machine tool enabling HSDH and characterizes intensive and inefficient energy consumption, an exergy-based method is proposed to evaluate the comprehensive energy efficiency of MSS. Furthermore, an exergy efficiency optimization model is proposed to maximize total exergy efficiency and minimize average temperature of MSS. A solution method integrating Pareto Dominant-based Multi-objective Simulated Annealing (PDMOSA) and Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to search the best solution of the optimization model. A case study is introduced to validate the proposed model and a final optimal solution is obtained at the total exergy efficiency of 53.5% with balanced temperature of 35.4 °C. The cooling water in MSS is identified to be a dominant factor that affects total exergy destruction. The presented model can give a reference to select appropriate process parameters of MSS for green and precision machining.

A Review on Energy Consumption, Energy Efficiency and Energy Saving of Metal Forming Processes from Different Hierarchies

Energy efficiency improvement and environmental impact reduction are emerging issues in the manufacturing industry. Aside from cutting, metal forming is also an important process in manufacturing. Metal forming is energy intensive because of the low energy efficiency of the used metal forming press. Although many literature reviews focused on the energy reduction and energy efficiency of machine tools, a comprehensive literature review of metal forming processes remains lacking because of the great difference between cutting machines and forming equipment. In addition, methods for energy efficiency and energy-saving still need to be promoted in metal forming. In this review, a novel hierarchy of the metal forming system was presented to describe the relationship among the equipment, process, and manufacturing system, providing a guideline of methods for energy efficiency and saving in metal forming. Then, existing energy consumption modeling and estimation theories and methods were discussed from two aspects. One is energy monitoring and modeling of metal forming equipment, and the other is process energy analysis of metal forming based on different parameters. On the basis of the hierarchy of the metal forming system, the present methods and technologies aiming to promote energy efficiency and energy saving effects were discussed from the aspects of equipment design and control, process optimization, and scheduling management and use. Thus, this review may serve as a reference for the decision-making of producers and managers to realize energy efficiency and energy saving at the system level. In addition, the major points that need attention are accurate energy models and control of forming equipment as well as the integrated optimization of equipment, process, and scheduling.

Research on energy consumption and energy efficiency of machine tools: a comprehensive survey

The increasing demand for energy, coupled with concerns over pollution and climate change, has led governments to establish policy frameworks to reduce CO2 emissions. Moreover, rises in energy price and increasingly greener customer behaviour are pushing the manufacturing industries to develop more sustainable processes. As a major source of energy consumption in manufacturing systems, machine tools have been the focus of sustainability research communities worldwide. This paper provides a survey of manufacturing industry's sustainability trends and presents a technology-foresight-based methodology for gathering key information on the research development in this topic. Furthermore, a correlation between real world aspects, such as legal, economic and environmental, and the development of research on energy consumption and efficiency of machine tools is provided. The results highlight the leading countries, institutions, authors and subject areas in this field. Research and development shows a high correlation with governmental actions, and appears to be of core importance to meet CO2 reduction targets.

Regular Neural Network Based Machining Parameters Optimization Model Of NC Machine Tool

Energy consumption process is the basis for energy efficiency improvement of machine tools. Most of the existing researches focus on the static modelling of energy consumption of a machine tool; however, there are a few studies that paid attention to that how process parameters influence the energy consumption of machine tools during processing. It is noted that the process parameters can be selected to reduce energy consumption during machining processes without additional investment. In this paper, a characteristic energy consumption model for NC machine tool was proposed. Then, the mapping rule between process parameters and energy consumption of machine tool was studied, and the model was solved with the regular neural network (RNN). Finally, the result was verified with an experiment of milling the surface of aluminium block, which can effectively improve the energy efficiency of machine tool. The experiment results are shown that regular neural network is used to optimize the process parameters and process the same machining characteristics; we analyze the in machining process of machine tool based on the three cutting parameters, and then, a model of energy consumption. We employ to learn, and use this trained model to select optimal parameters.

Connotation and Assessment Method for Inherent Energy Efficiency of Machine Tools

Connotation and Assessment Method for Inherent Energy Efficiency of Machine Tools

Research on energy consumption and energy efficiency of machine tools: a comprehensive survey

Research on energy consumption and energy efficiency of machine tools: a comprehensive survey

Measuring and calculating the computer numerical control lathe’s cutting power and total electric power consumption based on servo parameters

Improving the energy efficiency of machine tools is the goal of sustainable development of the mechanical manufacturing industry. The key is to measure or calculate energy efficiency conveniently a...

A new approach for calculating the input power of machine tool main transmission systems

The main transmission system, the key component for transferring energy in machine tools, is essential for studying the energy efficiency of machine tools, highlighting the need for manufacturers t...

Impact of Product-Service Systems on the Energy Efficiency of Machine Tools

Many machine tool manufacturers offer services to support their customers over the lifetime of a product. This kind of integration of products and services is called Product-Service Systems (PSS). PSS offer advantages for the customers as well as for PSS providers because they fulfill customers’ requirements and ensure a long and successful customer relationship. Since sustainability is getting more and more important and customers are interested in sustainable solutions, PSS providers need to improve the environmental impact of their products and services continuously. Under this aspect, an approach is necessary that identifies the ecological potential of services for machine tools. In this paper, an approach to analyze the impact of Product-Service Systems on the energy efficiency of machine tools is presented.

A novel approach for acquiring the real-time energy efficiency of machine tools

Machine tools (MT), as the key equipment of manufacturing industry, have enormous quantity and consume great amount of energy. In order to achieve consistent improvement of energy efficiency and environmental performance in manufacturing industry, it is significant to acquire the real-time energy efficiency (REE) of MT. However, due to the unavailable parameters and the limitations of using cutting-force-measuring instruments, it is difficult for existing methods to be applied to acquire the REE of MT. This paper proposes a novel approach for acquiring the REE without any usage of cutting-force-measuring instruments. To develop this approach, a model to characterize the relationship among the REE, input power and spindle speed of MT is established based on the basic data of MT. After obtaining these basic data, this approach only requires obtaining the spindle speed and input power to calculate the REE of MT. It has been tested and validated on a common used machine tool, and the results show its practicability and high level of accuracy for obtaining the REE of MT. This approach can be applied to assess the energy efficiency of MT, to support designers to design high-efficient MT and users to improve the energy efficiency of manufacturing process.

Automatic Assessment of Machine Tool Energy Efficiency and Productivity

This work presents an approach to determine relevant energy efficiency and productivity KPIs of machining processes based on a real-time interpretation of sensor data and machine control data. A comparison of the actual power consumption during machining with an energetic model of the load-free condition enables the calculation of energetic efficiency and primary processing time. The approach was tested on a CNC turning and milling center equipped with power meters and compressed air sensors. Sensor data as well as relevant machine control data are read, processed and recorded via SCADA software in order to automatically calculate certain KPIs.

Machine Tool Energy Efficiency – A Component Mapping-Based Approach

The European Commission outlined the energy-related products (ErPs) meant to be labelled and regulated in order to achieve the goals to reduce the European amount of CO2-emissions by 20% by 2020 compared to projections. Machine tools (MTs) fulfill all mandatory criteria to be categorized as ErP, namely: significant sales volume, significant environmental impact and significant improvement potential. However, the energy consumption and energy efficiency of MTs strongly depend on their utilization. A generic evaluation approach for quantifying a MT’s energy efficiency is still under development by the working group ISO/TC 39/WG 12, which drives forward the ISO 14955 series for environmental evaluation of MTs.This work presents an approach for a generic energy efficiency evaluation of MTs. Component-specific behavior is investigated and aggregated in order to entirely describe the power consumption of a MT for any utilization by power mapping. Power maps contain all possible operational scenarios under the condition of the component boundaries. The approach allows a generic MT evaluation independent on the utilization and forms the base for future MT energy efficiency labelling. The presented approach is applied and validated in a practical case study.

Mini Special Issue on Design and Manufacturing for Environmental Sustainability

As the third special issue on Design and Manufacturing for Environmental Sustainability for IJAT, this issue focuses on design and manufacturing theories and methodologies for achieving environmental sustainability and the topic of the special issue seems to be becoming established in this journal. This special issue contains six articles consisting of a wide variety of rather novel topics emerging in the domain of design and manufacturing for environmental sustainability. The first three deal with design problem in the broader sense: designing of system of systems taking distributed energy generation systems, upgradable design problems, and selection problem of end-of-life products recovery options integrated from the view of environmental load and cost. The last three papers deal with manufacturing problems in the broader sense – motion extraction problems for disassembly automation, machine tool energy efficiency, and optimization problems related to machine tool operating conditions for increasing environmental sustainability. Some papers, revised and extended at the editor’s request, were presented originally at EcoDesign 2015, the ninth international symposium on environmentally conscious design and inverse manufacturing, held in Tokyo, Japan, 2015. The editor thanks the authors and reviewers for their comprehensive efforts in making this special issue possible and hopes these articles will encourage further research on design and manufacturing for environmental sustainability.

Energy efficiency of machining operations: A review

Manufacturing processes are among the most energy intensive on earth. As negative ecological and economic impacts increase, reducing energy consumption is becoming critically important. In this article, a comprehensive overview of energy-saving strategies and opportunities for increasing energy efficiency in manufacturing operations is presented, with a focus on metal cutting processes. The issues and approaches involved in energy efficiency of machine tools and machining operations are reported in the literature and a structured research methodology is proposed for this purpose including prediction and modelling of machine energy consumption, determining the relationship between process energy consumption and process variables for material removal processes and optimization of cutting parameters in order to reduce energy consumption. Numerous techniques for increasing energy efficiency in manufacturing processes are identified and summarized, strengths and weaknesses of previous studies are discussed and potential avenues for future research are suggested.

Energy-aware integration of process planning and scheduling of advanced machining workshop

Increasing energy consumption of manufacturing industry demands novel approaches to achieve energy conservation and emission reduction. Most of the previous research efforts in this area focused more on analyzing manufacturing energy consumption of a process or that of a machine tool with less concern on the system level of advanced machining workshop, especially a flexible manufacturing system. In this article, a new energy-saving approach of flexible manufacturing system is put forward based on energy evaluation model for integration of process planning and scheduling problem in flexible manufacturing system (flexible manufacturing system-integration of process planning and scheduling). First, complying with feature precedence and other technological requirements, flexible manufacturing system -integration of process planning and scheduling is mapped as an asymmetric traveling salesman problem of which operations are provinces and candidate operations are cities belonging to different provinces. To evaluate the performance of each solution of the asymmetric traveling salesman problem, energy consumption evaluation criteria for flexible manufacturing system-integration of process planning and scheduling are established and three energy efficiency indicators are also provided to perform further analysis on manufacturing energy consumption, that is, part energy efficiency, machine tool energy efficiency and feasible solution energy efficiency. Then, a mutation-combined ant colony optimization algorithm is proposed to solve the flexible manufacturing system-integration of process planning and scheduling which combined roulette and mutation selection methods to pick out the next candidate operation. The pheromone trails associated with edges are released by the so-far-best ant or the iteration-best ant probabilistically to both keep the search directed and avoid converging to the local best. Finally, a case study of flexible manufacturing system in advanced machining workshop is employed to demonstrate the feasibility and applicability of this approach in three different scenarios and compared with the “process planning then scheduling” approach; energy consumption obtained by the proposed method drops 10.7%.