Advances in Manufacturing

State-of-the-art survey on digital twin implementations

Y. K. Liu, S. K. Ong, A. Y. C. Nee

2022, 10(1): 1-23. doi:10.1007/s40436-021-00375-w

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Digital twin (DT) has garnered attention in both industry and academia. With advances in big data and internet of things (IoTs) technologies, the infrastructure for DT implementation is becoming more readily available. As an emerging technology, there are both potential and challenges. DT is a promising methodology to leverage the modern data explosion to aid engineers, managers, healthcare experts and politicians in managing production lines, patient health and smart cities by providing a comprehensive and high fidelity monitoring, prognostics and diagnostics tools. New research and surveys into the topic are published regularly, as interest in this technology is high although there is a lack of standardization to the definition of a DT. Due to the large amount of information present in a DT system and the dual cyber and physical nature of a DT, augmented reality (AR) is a suitable technology for data visualization and interaction with DTs. This paper seeks to classify different types of DT implementations that have been reported, highlights some researches that have used AR as data visualization tool in DT, and examines the more recent approaches to solve outstanding challenges in DT and the integration of DT and AR.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00375-w

Nickel-titanium shape memory alloys made by selective laser melting:a review on process optimisation

Omar Ahmed Mohamed, Syed Hasan Masood, Wei Xu

2022, 10(1): 24-58. doi:10.1007/s40436-021-00376-9

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Selective laser melting (SLM) is a mainstream powder-bed fusion additive manufacturing (AM) process that creates a three-dimensional (3D) object using a high power laser to fuse fine particles of various metallic powders such as copper, tool steel, cobalt chrome, titanium, tungsten, aluminium and stainless steel. Over the past decade, SLM has received significant attention due to its capability in producing dense parts with superior mechanical properties. As a premier shape memory alloy, the nickel-titanium (NiTi) shape memory alloy is attractive for a variety of biomedical applications due to its superior mechanical properties, superelasticity, corrosion resistance and biocompatibility. This paper presents a comprehensive review of the recent progress in NiTi alloys produced by the SLM process, with a particular focus on the relationship between processing parameters, resultant microstructures and properties. Current research gaps, challenges and suggestions for future research are also addressed.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00376-9

Material removal at atomic and close-to-atomic scale by high-energy photon:a case study using atomistic-continuum method

Hao-Jie An, Jin-Shi Wang, Feng-Zhou Fang

2022, 10(1): 59-71. doi:10.1007/s40436-021-00374-x

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Extreme ultraviolet (EUV) light plays an important role in various fields such as material characterization and semiconductor manufacturing. It is also a potential approach in material fabrication at atomic and close-to-atomic scales. However, the material removal mechanism has not yet been fully understood. This paper studies the interaction of a femtosecond EUV pulse with monocrystalline silicon using molecular dynamics (MD) coupled with a two-temperature model (TTM). The photoionization mechanism, an important process occurring at a short wavelength, is introduced to the simulation and the results are compared with those of the traditional model. Dynamical processes including photoionization, atom desorption, and laser-induced shockwave are discussed under various fluencies, and the possibility of single atomic layer removal is explored. Results show that photoionization and the corresponding bond breakage are the main reasons of atom desorption. The method developed can be further employed to investigate the interaction between high-energy photons and the material at moderate fluence.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00374-x

Debris effect on the surface wear and damage evolution of counterpart materials subjected to contact sliding

Wei Li, Liang-Chi Zhang, Chu-Han Wu, Zhen-Xiang Cui, Chao Niu, Yan Wang

2022, 10(1): 72-86. doi:10.1007/s40436-021-00377-8

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This paper aims to explore the debris effect on surface wear and damage evolution of counterpart materials during contact sliding. A cylinder-on-flat testing configuration is used to investigate the wear behaviours of the contact pair. To explore the roles of wear debris, compressed air is applied to remove the debris in sliding zones. The comparative study demonstrates that the influence of debris removal is related to the surface properties of contact pairs. When substantial wear debris accumulates on the tool surface, debris removal can considerably alter surface damage evolution, resulting in different friction transitions, distinct surface morphology of contact pair, as well as different rates of material removal. It has been found that the surface damage evolution will not reach a stable stage unless the increase of wear particle number ceases or the average size of wear particles becomes lower than a specific threshold. However, the influence of debris removal reduces when the adhesion between the contact pair materials gets smaller.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00377-8

Residual-stress relaxation mechanism and model description of 5052H32 Al alloy spun ellipsoidal heads during annealing treatment

Yong-Cheng Lin, Jiang-Shan Zhu, Jia-Yang Chen, Jun-Quan Wang

2022, 10(1): 87-100. doi:10.1007/s40436-021-00367-w

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Marginal-restraint mandrel-free spinning is an advanced technology for manufacturing ellipsoidal heads with large diameter-thickness ratios. Nevertheless, the spinning-induced residual stress, which greatly influences the in-service performance of spun heads, should be removed. In this study, the effects of annealing on the residual-stress relaxation behavior of 5052H32 aluminum alloy spun heads were investigated. It is found that the residual stress first rapidly decreases and then remains steady with the increase in annealing time at the tested annealing temperatures. The relaxation of the residual stress becomes increasingly obvious with the increase in annealing temperature. When the annealing temperature is less than 220℃, there are no obvious changes in grain size. Moreover, the spinning-induced dislocations are consumed by the static recovery behavior, which decreases the residual stress during annealing. When the annealing temperature is approximately 300℃, the broken grains transform into equiaxed grains. In addition, static recrystallization and recovery behaviors occur simultaneously to promote the relaxation of the residual stress. Considering the different stress relaxation mechanisms, a model based on the Zener-Wert-Avrami equation was established to predict the residual-stress relaxation behavior. Finally, the optimized annealing temperature and time were approximately 300℃ and 30 min, respectively.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00367-w

Indirect approach for predicting cutting force coefficients and power consumption in milling process

Kai-Ning Shi, Ning Liu, Cong-Le Liu, Jun-Xue Ren, Shan-Shan Yang, Wei Chit Tan

2022, 10(1): 101-113. doi:10.1007/s40436-021-00370-1

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Accurate energy consumption modeling is an essential prerequisite for sustainable manufacturing. Recently, cutting-power-based models have garnered significant attention, as they can provide more comprehensive information regarding the machining energy consumption pattern. However, their implementation is challenging because new cutting force coefficients are typically required to address new workpiece materials. Traditionally, cutting force coefficients are calculated at a high operation cost as a dynamometer must be used. Hence, a novel indirect approach for estimating the cutting force coefficients of a new tool-workpiece pair is proposed herein. The key idea is to convert the cutting force coefficient calculation problem into an optimization problem, whose solution can be effectively obtained using the proposed simulated annealing algorithm. Subsequently, the cutting force coefficients for a new tool-workpiece pair can be estimated from a pre-calibrated energy consumption model. Machining experiments performed using different machine tools clearly demonstrate the effectiveness of the developed approach. Comparative studies with measured cutting force coefficients reveal the decent accuracy of the approach in terms of both energy consumption prediction and instantaneous cutting force prediction. The proposed approach can provide an accurate and reliable estimation of cutting force coefficients for new workpiece materials while avoiding operational or economic problems encountered in traditional force monitoring methods involving dynamometers. Therefore, this study may significantly advance the development of sustainable manufacturing.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00370-1

A bioinspired path planning approach for mobile robots based on improved sparrow search algorithm

Zhen Zhang, Rui He, Kuo Yang

2022, 10(1): 114-130. doi:10.1007/s40436-021-00366-x

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In this paper, a bioinspired path planning approach for mobile robots is proposed. The approach is based on the sparrow search algorithm, which is an intelligent optimization algorithm inspired by the group wisdom, foraging, and anti-predation behaviors of sparrows. To obtain high-quality paths and fast convergence, an improved sparrow search algorithm is proposed with three new strategies. First, a linear path strategy is proposed, which can transform the polyline in the corner of the path into a smooth line, to enable the robot to reach the goal faster. Then, a new neighborhood search strategy is used to improve the fitness value of the global optimal individual, and a new position update function is used to speed up the convergence. Finally, a new multi-index comprehensive evaluation method is designed to evaluate these algorithms. Experimental results show that the proposed algorithm has a shorter path and faster convergence than other state-of-the-art studies.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00366-x

Machine-vision-based electrode wear analysis for closed loop wire EDM process control

P. M. Abhilash, D. Chakradhar

2022, 10(1): 131-142. doi:10.1007/s40436-021-00373-y

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The purpose of this study was to develop a closed-loop machine vision system for wire electrical discharge machining (EDM) process control. Excessive wire wear leading to wire breakage is the primary cause of wire EDM process failures. Such process interruptions are undesirable because they affect cost efficiency, surface quality, and process sustainability. The developed system monitors wire wear using an image-processing algorithm and suggests parametric changes according to the severity of the wire wear. Microscopic images of the wire electrode coming out from the machining zone are fed to the system as raw images. In the proposed method, the images are pre-processed and enhanced to obtain a binary image that is used to compute the wire wear ratio (WWR). The input parameters that are adjusted to recover from the unstable conditions that cause excessive wire wear are pulse off time, servo voltage, and wire feed rate. The algorithm successfully predicted wire breakage events. In addition, the alternative parametric settings proposed by the control algorithm were successful in reducing the wire wear to safe limits, thereby preventing wire breakage interruptions.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00373-y

Effect of back pressure on the grinding performance of abrasive suspension flow machining

Ming-Hui Fang, Tao Yu, Feng-Feng Xi

2022, 10(1): 143-157. doi:10.1007/s40436-021-00372-z

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Abrasive suspension flow machining (ASFM) is an advanced finishing method that uses an abrasive suspension slurry for grinding and chamfering as well as the finishing of inaccessible components. This study examines the effect of back pressure on the grinding characteristics of an abrasive suspension flow during the grinding of slender holes. A numerical model was developed to simulate the abrasive suspension flow in a slender hole and was verified experimentally using injector nozzle grinding equipment under different grinding pressures and back pressures. It is shown that the ASFM with back pressure not only eliminates the cavitation flow in the spray hole, but also increases the number of effective abrasive particles and the flow coefficient. Increasing the back pressure during the grinding process can increase the Reynolds number of the abrasive suspension flow and reduce the thickness of the boundary layer in the slender hole. Moreover, increasing the back pressure can improve the flow rate of the injector nozzle and its grinding performance.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00372-z

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