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With the growing concerns on global warming, much research attention has been focused on industrial activities which largely consume energy and emit carbon to the atmosphere. Low-carbon manufacturing, aiming to reduce carbon intensity and enhance resource utilization, is then emerging as a timely topic and spurs much research into a low carbon scenario. This paper proposes an analytical method of quantifying carbon emissions of a computer numerical control (CNC)-based machining system. In particular, the paper discusses the breakdown of the processes that contribute to the overall carbon emissions of a CNC-based machining system, such as electricity, cutting fluid, wear and tear of cutting tools, material consumption and disposal of chips, etc. The way of quantifying the amount of carbon emissions from individual processes are then analyzed. Finally, the proposed methodology is applied into two different machining cases, in which the impact of different machining parameters and different machining methods on carbon emissions in the CNC machining process are analyzed, respectively.

In the digital assembly system of large aircraft components (LAC), multiple numerical control positioners (NCPs) are usually used as actuators to adjust the position and posture of LAC to realize the docking of LAC. The posture adjustment mechanism (PAM) composed of multiple NCPs is a redundant actuated parallel mechanism (RAPM). The traditional full position control (FPC) method may lead to interference between NCPs, resulting in the deformation of NCPs and bracket, affecting the service life of the equipment. This paper proposes a posture adjustment method based on hybrid control, which divides the motion axes of the NCPs into the position control axis and the force control axis to avoid the internal force of posture adjustment caused by the cooperative motion error of the NCPs. The driving force of the axis of the RAPM under the same posture adjustment trajectory is uncertain. To further reduce the internal force of posture adjustment, a driving force distribution method based on the dynamic model of PAM is proposed. Then, the principle of selecting the position control axis of the PAM is analyzed, and the optimization strategy of the position control axis based on the condition number of the Jacobian matrix is studied to improve the motion performance of the PAM. Finally, the posture adjustment experiment of LAC is carried out. The results show that the hybrid control method based on the optimum contact force can significantly reduce the interaction force between NCPs. The experimental results of posture adjustment accuracy verification show that the optimization strategy of position control axis makes the accuracy of single posture adjustment meet the requirements of LAC docking, which can effectively improve the docking efficiency of LAC.

With the rapid development of the manufacturing industry, industrial automation equipment represented by computer numerical control (CNC) machine tools has put forward higher and higher requirements for the machining accuracy of parts. Compared with the multi-axis serial platform solution, the parallel platform solution is theoretically more suitable for high-precision machining equipment. There are many parallel platform solutions, but not one can provide a common physical platform to test the effectiveness of a variety of control algorithms. To achieve the goals, this paper is based on the Stewart six degrees of freedom parallel platform, and it mainly studies the platform construction. This study completed the mechanical structure design of the parallel platform. Based on the microprogrammed control unit (MCU) + pre-driver chip + three-phase full bridge solution, we have completed the circuit design of the motor driver. We wrote the program of MCU to drive six parallel robotic arms as well as the program of the parallel platform control center on the PC, and we completed the system joint debugging. The closed-loop control effect of the parallel platform workspace pose is realized.

Purpose – The purpose of this study is to compare the environmental impacts of two additive manufacturing machines to a traditional computer numerical control (CNC) milling machine to determine which method is the most sustainable. Design/methodology/approach – A life-cycle assessment (LCA) was performed, comparing a Haas VF0 CNC mill to two methods of additive manufacturing: a Dimension 1200BST FDM and an Objet Connex 350 “inkjet”/“polyjet”. The LCA’s functional unit was the manufacturing of two specific parts in acrylonitrile butadiene styrene (ABS) plastic or similar polymer, as required by the machines. The scope was cradle to grave, including embodied impacts, transportation, energy used during manufacturing, energy used while idling and in standby, material used in final parts, waste material generated, cutting fluid for CNC, and disposal. Several scenarios were considered, all scored using the ReCiPe Endpoint H and IMPACT 2002+ methodologies. Findings – Results showed that the sustainability of additive manufacturing vs CNC machining depends primarily on the per cent utilization of each machine. Higher utilization both reduces idling energy use and amortizes the embodied impacts of each machine. For both three-dimensional (3D) printers, electricity use is always the dominant impact, but for CNC at maximum utilization, material waste became dominant, and cutting fluid was roughly on par with electricity use. At both high and low utilization, the fused deposition modeling (FDM) machine had the lowest ecological impacts per part. The inkjet machine sometimes performed better and sometimes worse than CNC, depending on idle time/energy and on process parameters. Research limitations/implications – The study only compared additive manufacturing in plastic, and did not include other additive manufacturing technologies, such as selective laser sintering or stereolithography. It also does not include post-processing that might bring the surface finish of FDM parts up to the quality of inkjet or CNC parts. Practical implications – Designers and engineers seeking to minimize the environmental impacts of their prototypes should share high-utilization machines, and are advised to use FDM machines over CNC mills or polyjet machines if they provide sufficient quality of surface finish. Originality/value – This is the first paper quantitatively comparing the environmental impacts of additive manufacturing with traditional machining. It also provides a more comprehensive measurement of environmental impacts than most studies of either milling or additive manufacturing alone – it includes not merely CO2 emissions or waste but also acidification, eutrophication, human toxicity, ecotoxicity and other impact categories. Designers, engineers and job shop managers may use the results to guide sourcing or purchasing decisions related to rapid prototyping.

The application of intelligent computer numerical control(CNC) technology enjoys a key strategic position in various countries, and countries that attach importance to the development of CNC machine tools and their fields of innovation branches generally have a solid foundation of intelligent manufacturing and strong production capacity. Combined with big data and artificial intelligence, CNC technology has become an important cornerstone of smart manufacturing. In order to achieve the goal of sustainable development, the machinery manufacturing industry should not only improve product accuracy and enrich product types, but also shorten the production cycle as much as possible and avoid the impact of human errors on product quality. Based on this, this paper mainly analyzes in detail the actual development of machinery manufacturing based on intelligent robot numerical control technology in order to provide some help for the long-term development of the industry. This paper is dedicated to the visualization of relevant data and finally provides a reliable basis for the corresponding decision-making based on the current actual development of intelligent CNC technology. After this paper analyzes the current situation of the industry, we find that intelligent numerical control technology has a vital role in the intelligent transformation of China’s industry, high-tech innovation, and rationalization of AI applications, and we hope that this paper can provide a reference for China’s industrial production industry.

This paper reports a comparison between the advantages and disadvantages of fused filament fabrication (FFF) and computer numerical control (CNC) milling, when applied to a specific case of conservation of cultural heritage: the reproduction of four missing columns of a 17th-century tabernacle. To make the replica prototypes, European pine wood (the original material) was used for CNC milling, while polyethylene terephthalate glycol (PETG) was used for FFF printing. Neat materials were chemically and structurally characterized (FTIR, XRD, DSC, contact angle measurement, colorimetry, and bending tests) before and after artificial aging, in order to study their durability. The comparison showed that although both materials are subject to a decrease in crystallinity (an increase in amorphous bands in XRD diffractograms) and mechanical performance with aging, these characteristics are less evident in PETG (E = 1.13 ± 0.01 GPa and σ = 60.20 ± 2.11 MPa after aging), which retains water repellent (ca = 95.96 ± 5.56°) and colorimetric (∆E = 2.6) properties. Furthermore, the increase in flexural strain (%) in pine wood, from 3.71 ± 0.03% to 4.11 ± 0.02%, makes it not suitable for purpose. Both techniques were then used to produce the same column, showing that for this specific application CNC milling is quicker than FFF, but, at the same time, it is also much more expensive and produces a huge amount of waste material compared to FFF printing. Based on these results, it was assessed that FFF is more suitable for the replication of the specific column. For this reason, only the 3D-printed PETG column was used for the subsequent conservative restoration.

The posture adjustment mechanism (PAM) for large components of aircraft is composed of several numerical control positioners (NCPs). This paper proposes a self-calibration method of positioner to guarantee the accuracy of posture alignment. Firstly, the redundant axis of the PAM is controlled by force feedback to obtain additional joint trajectory information, and the ball joint center (BJC) position is calculated by the spatial circle fitting method. Secondly, the coordinates of the BJC in the base coordinate system and the positioner coordinate system are registered to obtain the position and posture parameters between the positioners. Thirdly, the main factors affecting the calibration accuracy are studied, and the uncertainty of positioner calibration is analyzed by Monte Carlo simulation. Finally, a simulated posture adjustment system of large components is built, and two methods are used to calibrate the positioner. The posture adjustment experiment results show that compared with the conventional calibration method, the proposed calibration method can improve the posture alignment accuracy and significantly reduce the interaction force between the positioners.

A method to identify the position error of direct drive numerical control turntable by measuring current and eccentric load is proposed, and the position error model of direct drive numerical control turntable based on whale Optimized BP (WOABP) neural network is established. The test-bed is built to measure the current, eccentric load and position error. The measured current and eccentric load are trained by WOABP neural network, and the position error of direct drive numerical control turntable is obtained. By comparing the original error, the error obtained by BP neural network and the error obtained by WOABP neural network, the effectiveness of WOABP neural network model is verified. The position error of direct drive numerical control turntable is compensated by the error obtained by the model.

The present study investigates the CNC milling performance of the machining of AISI 316 stainless steel using a carbide cutting tool insert. Three critical machining parameters, namely cutting speed (v), feed rate (f) and depth of cut (d), each at three levels, are chosen as input machining parameters. The face-centred central composite design (FCCCD) of the experiment is based on response surface methodology (RSM), and machining performances are measured in terms of material removal rate (MRR) and surface roughness (SR). Analysis of variance, response graphs, and three-dimensional surface plots are used to analyse experimental results. Multi-response optimization using the data envelopment analysis based ranking (DEAR) approach is used to find the ideal configuration of the machining parameters for milling AISI 316 SS. The variables v = 220 m/min, f = 0.20 mm/rev and d = 1.2 mm were obtained as the optimal machine parameter setting. Study reveals that MRR is affected dominantly by d followed by v. For SR, f is the dominating factor followed by d. SR is found to be almost unaffected by v. Finally, it is important to state that this work made an attempt to successfully machine AISI 316 SS with a carbide cutting tool insert, to investigate the effect of important machining parameters on MRR and SR and also to optimize the multiple output response using DEAR method.

Traditional industrial robots' force control systems exhibit limited practicality and cost-effectiveness in manufacturing complex parts. Therefore, this paper proposes an open CNC force control simulation system based on the “PLC + CNC force control technical table (FCTT)”, integrating both hardware and software components. The hardware includes PLC and CNC force control technology, drivers and servo systems, sensor systems, and system control circuits. The software is implemented in C++ with a modular design, while the upper and lower computers communicate primarily via a standard PCI bus. The corresponding CNC machine control technology receives application program commands from the upper computer. Then, it performs motion control according to the corresponding CNC force, driving the servo system to complete the corresponding motion control commands. This system solves the problem of query speed in the force control system, improving its responsiveness and reliability. The design of complex curved parts was validated using this system, and the results showed that the CNC force control system proposed in this paper improved by about 10% compared to traditional systems in terms of CNC force accuracy, rotation accuracy, surface roughness, and matching between virtual and actual values, demonstrating significant advantages.