An investigation into reducing the spindle acceleration energy consumption of machine tools

Machine tools are widely used in the manufacturing industry, and consume large amount of energy. Spindle acceleration appears frequently while machine tools are working. It produces power peak which is highly energy intensive. As a result, a considerable amount of energy is consumed by this acceleration during the use phase of machine tools. However, there is still a lack of understanding of the energy consumption of spindle acceleration. Therefore, this research aims to model the spindle acceleration energy consumption of computer numerical control (CNC) lathes, and to investigate potential approaches to reduce this part of consumption. The proposed model is based on the principle of spindle motor control and includes the calculation of moment of inertia for spindle drive system. Experiments are carried out based on a CNC lathe to validate the proposed model. The approaches for reducing the spindle acceleration energy consumption were developed. On the machine level, the approaches include avoiding unnecessary stopping and restarting of the spindle, shortening the acceleration time, lightweight design, proper use and maintenance of the spindle. On the system level, a machine tool selection criterion is developed for energy saving. Results show that the energy can be reduced by 10.6% to more than 50% using these approaches, most of which are practical and easy to implement

Towards Sustainable and Intelligent Machining:Energy Footprint and Tool Condition Monitoring for Media-Assisted Processes

Reducing energy consumption is a necessity towards achieving the goal of net-zero manufacturing. In this paper, the overall energy footprint of machining Ti-6Al-4V using various cooling/lubrication methods is investigated taking the embodied energy of cutting tools and cutting fluids into account. Previous studies concentrated on reducing the energy consumption associated with the machine tool and cutting fluids. However, the investigations in this study show the significance of the embodied energy of cutting tool. New cooling/lubrication methods such as WS2-oil suspension can reduce the energy footprint of machining through extending tool life. Cutting tools are commonly replaced early before reaching their end of useful life to prevent damage to the workpiece, effectively wasting a portion of the embodied energy in cutting tools. A deep learning method is trained and validated to identify when a tool change is required based on sensor signals from a wireless sensory toolholder. The results indicated that the network is capable of classifying over 90% of the tools correctly. This enables capitalising on the entirety of a tool’s useful life before replacing the tool and thus reducing the overall energy footprint of machining processes

Sustainable Machining Processes through Optimization of Process Parameters

Machining processes are a vital part of manufacturing activities in major industries that contributes to the growth of the economy. They mostly require high amount of electrical energy to power the various support modules installed on machine tools. Carrying out machining activities with a view to reducing energy consumption will therefore result in a lowered cost of production for manufactured products. Previous studies on some energy-saving methods adopted by researchers and the limitations faced in the reduction of energy consumption have been discussed. In this work, the effect of process parameters in the conservation of energy during machining processes was experimented. Results shows that much energy could be saved by optimizing parameters before machining

Energy Efficiency Improvements in Dry Drilling with Optimised Diamond-Like Carbon Coating

We demonstrate enhancements of performance and energy efficiency of cutting tools by deposition of diamond-like carbon (DLC) coatings on machine parts. DLC was deposited on steel drill bits, using plasma enhanced chemical vapour deposition (PECVD) with the acetylene precursor diluted with argon, to produce a surface with low friction and low wear rate. Drill bit performance in dry drilling of aluminium was quantified by analysis of power consumption and swarf flow. Optimised deposition conditions produced drill bits with greatly enhanced performance over uncoated drill bits, showing a 25% reduction in swarf clogging, a 36% reduction in power consumption and a greater than five-fold increase in lifetime. Surface analysis with scanning electron microscopy shows that DLC coated drills exhibit much lower aluminium build up on the trailing shank of the drill, enhancing the anti-adhering properties of the drill and reducing heat generation during operation, resulting in the observed improvements in efficiency. Variation of drilling efficiency with argon dilution of precursor is related to changes in the microstructure of the DLC coating

Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use

Since machine tools are used extensively throughout their functional life and consequently consuming valuable natural resources and emitting harmful pollutants during this time, this study reviews strategies for characterizing and reducing the energy consumption of milling machine tools during their use. The power demanded by a micromachining center while cutting low carbon steel under varied material removal rates was measured to model the specific energy of the machine tool. Thereafter the power demanded was studied for cutting aluminum and polycarbonate work pieces for the purpose of comparing the difference in cutting power demand relative to that of steel

Measures for Energy-Efficient Process Chains

Energy efficiency is an essential factor for promoting sustainable manufacturing. Various types of energy consumption occur in modern process chains. This includes usage of electrical energy, e.g. for machine tools or air compression, but also energy consumption through use of resources (such as raw materials and supplies). In this paper, a process chain from the automotive industry is considered with the purpose of identifying energy saving potentials of various kinds. The process chain is used for the production of an axle component. In order to evaluate saving potentials, the current state of the process chain is analyzed. Then, the impact of process parameter optimization on the energy demand is examined. It was found that small energy savings through parameter optimization are possible. However, this can be problematic since process parameters are closely linked to process reliability, so energy savings might be achieved at the expense of product quality. Furthermore, it turns out that the reduction of the process energy is not sufficient for a broad energetic optimization of the process chain and base load reducing measures are required instead. Therefore, further analysis is focused on energetic effects of such measures as machine design, recycling, adjustments of process chain and product design. These were found to be an effective lever for minimizing energy demand of the process chain. A combination of feasible measures adds up to a potential energy saving of 11.5% in the investigated scenario

Modeling Energy Consumption in Automotive Manufacturing

Developing a dynamic model of energy consumption for CNC machines in automotive industries helps to reduce the energy consumption in these machines. Over the last decade, a significant rise in energy usage has occurred due to the growth in the developing world. According to (IEO2013), this trend will continue over the next three decades. In CNC machines, there are various parameters in milling and turning operations which have significant roles in reducing energy consumption. In the first case study presented, parameters of machine tools are changed and the energy consumption is calculated to identify the parameters that have the greatest impact on saving energy. An energy consumption model is developed by using system dynamics in order to comprehend the behavior of complex system. Then, data from the first case study is used in order to demonstrate how buffer inventories can help manufacturers to save more energy during high electricity demand

Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Experimental study on energy consumption of computer numerical control machine tools

Machining processes are responsible for substantial environmental impacts due to their great energy consumption. Accurately characterizing the energy consumption of machining processes is a starting point to increase manufacturing energy efficiency and reduce their associated environmental impacts. The energy calculation of machining processes depends on the availability of energy supply data of machine tools. However, the energy supply can vary greatly among different types of machine tools so that it is difficult to obtain the energy data theoretically. The aim of this research was to investigate the energy characteristics and obtain the power models of computer numerical control (CNC) machine tools through an experimental study. Four CNC lathes, two CNC milling machines and one machining center were selected for experiments. Power consumption of non-cutting motions and material removal was measured and compared for the selected machine tools. Here, non-cutting motions include standby, cutting fluid spraying, spindle rotation and feeding operations of machine tools. Material removal includes turning and milling. Results show that the power consumption of non-cutting motions and milling is dependent on machine tools while the power consumption of turning is almost independent from the machine tools. The results imply that the energy saving potential of machining processes is tremendous