Actual Manufacturing Research Articles

IDENTIFICATION OF CHATTER VIBRATIONS AND ACTIVE VIBRATION CONTROL BY USING THE SLIDING MODE CONTROLLER ON DRY TURNING OF TITANIUM ALLOY (TI6AL4V)

In recent years, with the development of sensor technologies, communication platforms, cyber-physical systems, storage technologies, internet applications and controller infrastructures, the way has been opened to produce competitive products with high quality and low cost. In turning, which is one of the important processes of machining, chatter vibrations are among the biggest problems affecting product quality, productivity and cost. There are many techniques proposed to reduce chatter vibrations for which the exact cause cannot be determined. In this study, an active vibration control based on the Sliding Mode Control (SMC) has been implemented in order to reduce and eliminate chatter vibration, which is undesirable for the turning process. In this context, three-axis acceleration data were collected from the cutting tool during the turning of Ti6Al4V. Finite Impulse Response (FIR) filtering, Fast Fourier Transform (FFT) analysis and integral process were carried out in order to use the raw acceleration data collected over the system in control. The system is modeled mathematically and an active control block diagram is created. It is observed that chattering decreased significantly after the application of active vibration control. The surface quality formed by the amplitude of the graph obtained after active control has been compared and verified with the data obtained from the actual manufacturing result.

Simulation of temperature field and residual stress in high-power laser self-melting welding process of CLF-1 steel medium-thick plate

To mitigate the adverse effects of residual stress and deformation during high-power laser welding, this study established a finite element model based on thermodynamic conditions for high-power laser welding of CLF-1 steel for nuclear fusion applications. The temperature field and residual stress of the weld were simulated by using the composite heat source model together with Gaussian model and conical model. The results showed that the temperature field simulation was in good agreement with the real temperature field. The simulation results of the weld metal (WM) and the heat affected zone (HAZ) in the cross sections were basically consistent with those of the real cross sections. Moreover, the margin of error between the simulation results and the real data was ≤ 1.3% (the largest error ≤0.04 mm). The Von Mises equivalent stress in WM was distributed irregularly, and its largest value was ≤ 220 MPa; the equivalent stress declined with an increase in distance from the center of WM. The transverse stress distribution in the center of WM was in accordance with the vertical stress distribution, which was essentially the same as the experimental data of the vertical stress. The simulation results of deformation in the Z direction of the weld showed that the maximum deformation was about -0.2 mm at the center of the weld corresponding to the length of 300 mm. In summary, the thermal source model, combined with laser welding process parameters, can provide high-precision prediction of stress variations and deformation control during the actual welding manufacturing process of the test blanket module (TBM) structure.

Risk Identification Model for Lean Manufacturing Improvement

Small- and medium-sized manufacturing enterprises (SMEs) were confronted with a variety of difficulties due to the increasingly complex market environment, and many of them could not make enough profits to proceed with their manufacturing tasks. The objective of this study was to develop a model of risk management by integrating several risk tools at manufacturing companies. This study was also intended to improve the decision making by providing quantitative analysis at each step of risk management and improve lean practices. Risk quantitative analysis methods such as failure modes and effects analysis (FMEA) and multi-objective optimization on the basis of ratio analysis (MOORA) were applied in this study to identify the potential risks. Moreover, the risk assessment was used to categorize risks into different severity levels. The manufacturing data obtained from a case study was utilised to calculate the risk priority number (RPN). The risk mitigation actions were formulated to reduce the original RPN and the final RPN value decreased to a normal standard in the end. Overall, this study optimised the risk management of one case study SME and improved lean manufacturing practices. By establishing the risk identification model and applying common lean manufacturing concepts in reducing wastes at actual manufacturing processes, the manufacturing enterprise could manage to optimize the operations and increase the actual manufacturing productivity. The machining and assembly processes of diesel engines were optimized and improved with the decrease of RPN and the selection of the CK6150 CNC lathe that owns the highest MOORA assessment value.

Study of the Transmission Characteristics of the Cycloid Gear Based on a Multi-Objective Optimization Modification

Due to the advantages of high transmission accuracy and high impact resistance, cycloid-pin gear drives are widely used in precision machinery. In the actual manufacturing and use process, a suitable clearance must be left between the cycloid gear and the pin teeth to meet the requirements of assembly lubrication, so the cycloid gear needs to be modified. In order to improve the performance of the cycloid-pin gear drive, this paper proposes a multi-objective optimization modification method which takes into account the maximum transmission error of the cycloid drive on the basis of the compound modification. Firstly, a compound modification function is constructed based on the equations of the cycloid gear. Tooth contact analysis is carried out on the cycloid gear to obtain the equations for calculating the transmission error and return error of the cycloid pinion drive and to solve for the transmission error and return error of a single cycle with different modification coefficients. Then, a multi-objective optimization model is constructed, and the optimum coefficients are solved by genetic algorithm. By analyzing the forces on the cycloid gear under load, the range, the number and the contact force of meshing teeth are calculated for different modification methods. At the end, the cycloid gear is modeled and finite element analyzed after multi-objective optimization modification and compound modification according to the optimal modification coefficients. By finite element analysis, the correctness of the theoretical calculation of the contact force of the modified cycloid gear and the loading transmission error is solved. The contact forces and transmission error of the multi-objective optimization modification are less than the compound modification. The theoretical calculation and finite element analysis indicate that the cycloid profile with the multi-objective optimization modification is better than the profile with the compound modification.

Study on the optimization of high-speed turnout crossing structures based on actual elastic deformation of point and splice rails

In this paper, to address the shortcomings of the crossing structure design based on the elastic bending center method and the lack of related research, an optimization method for high-speed turnout crossing structures was proposed based on the actual elastic deformations of point and splice rails. Based on the finite element theory, the actual loading characteristics and spatial variable section characteristics of point and splice rails were fully considered, and a refined simulation analysis model of the switching system of point and splice rails in crossing areas was established. Moreover, the elastic deformation lines of point and splice rails in the nonworking state were obtained for the first time, which were consistent with actual situations. On this basis, system optimization was performed for the connecting parts of the crossing with a movable point in a high-speed turnout. In the crossing structure simulation model, the length adjustment values of the first–sixth spacer blocks between the branch line–wing and point rails and between the mail line–wing splice rails were ≤1 mm. Moreover, the lengths of the seventh–ninth spacer blocks decreased by gradually increasing amounts, and the length of the ninth spacer block decreased the most (∼6 mm). The length of the second spacer block between the point and splice rails slightly increased, but the length of the third spacer block significantly decreased by 6 mm. The length adjustment value of the distance block between the point and splice rails was smallest (0.7 mm). The calculated optimal lengths of the connecting parts of the crossing were found to be close to the empirical values used in actual manufacturing processes, and the dimension optimization patterns were completely consistent with actual situation, which validates the proposed optimization method. Thus, the proposed method can effectively improve the coordination between rails and connecting parts in crossing areas, substantially reduce internal stresses in crossing systems, and improve their assembly performance and service life. Moreover, the proposed optimization parameters can provide valuable references for the research on next-generation high-speed turnouts (400 km/h) and for improving the designs of existing high-speed turnouts.

Influence analysis of anti-spatter spray on welding process and weld properties

Based on the accumulation situation of anti-spatter spray in actual manufacturing, butt joints are implemented to analyze the state changes of two types of anti-spatter spray and their effect on arc stability, molten pool fluidity, and weld performance. The results show that the fluidity of water-based anti-spatter spray is significantly better than that of oil-based anti-spatter spray in the welding process, resulting in a large accumulation near the arc suppression position. This causes strong fluctuations in the arc and molten pool, while the oil-based anti-spatter spray can reduce the spreadability of the molten pool near the bevel. In terms of weld performance, oil-based anti-spatter spray reduces the plasticity of the weld, and the average elongation of the tensile specimens of the corresponding joint is 37% lower than that of the joint without anti-spatter spray. The rapid evaporation of the water-based anti-spatter spray leads to faster cooling of the weld, resulting in a narrow range of hardened microstructure in the heat-affected zone. Therefore, an apparent increase in microhardness at the corresponding location.

Connection stiffness modeling of rotating dovetailed blade with macro-micro interface topography

The connection stiffness between the dovetailed blade and disk indicates the boundary condition of the blade, directly influencing the dynamic response of the blade-disk assembly and even the structural safety of the whole aero-engine. Due to the limited manufacturing precision, the contact interface of dovetailed joint is rough with macroscopic geometrical deviation inside. However, few researches are reported about the effect of macro-micro interface topography on the connection stiffness. In this paper, a stiffness model of the rotating dovetailed blade with interface topography characteristic is proposed. First, a statistical contact model is established to describe the normal and tangential contact responses of the rough interface in dovetailed joint. Then, by introducing the displacement and angle infinitesimals, the explicit expressions of the connection stiffnesses in different directions are derived out. Finally, based on the presented connection stiffness model, rotational speed, working temperature, macroscopic geometrical deviation, and microscopic topography parameters are investigated in detail. The results show a great influence of interface topography and operating parameters on the connection stiffness. The work in this paper provides a novel way to reveal the inner mechanical relationship between the macro-micro topography and the connection stiffness of dovetailed blade under the work condition, which is meaningful for the actual manufacturing and performance analysis of the aero-engine.

High-performance tooth flank collaborative optimization model for spiral bevel and hypoid gears

The tooth flank collaborative optimization considering both geometric and loaded contact performances is an increasingly significant target in design and manufacturing for spiral bevel and hypoid gears. Recently, numerical loaded tooth contact analysis (NLTCA) is always an important access of mapping of the required performance evaluations and design variables. In addition to the conventional solution to NLTCA, an innovative discrete convolution and fast Fourier transformation (DC-FFT) method focusing on the micro-scale tooth flank topography is developed for high-performance spiral bevel and hypoid gears. Then, combining with accuracy and efficiency, a new top-rem tool modification is proposed to establish a new collaborative optimization model. Where, while the target flank can be prescribed by considering the user needs in the actual manufacturing, a small number of tool parameters are selected as the unknown design variables. It can significantly deal with the strong nonlinearity and coupling effect from the traditional modification and improve the optimization efficiency. Moreover, a top-rem tool modification is used as the optimization strategy to get a high optimization accuracy. The spiral bevel gear set from aerospace industrial applications is exercised to demonstrate the impact of the proposed collaborative optimization model on the tooth flank geometric and loaded contact performances.

A Method for Predicting Surface Finish of Polylactic Acid Parts Printed Using Fused Deposition Modeling

Accurately predicting the surface finish of fused deposition modeling (FDM) parts is an important task for the engineering application of FDM technology. So far, many prediction models have been proposed by establishing a mapping relationship between printing parameters and surface roughness. Each model can work well in its specific context; however, existing prediction models cannot meet the requirements of multi-factor and multi-category prediction of surface finish and cope with imbalanced data. Aiming at these issues, a prediction method based on a combination of the adaptive particle swarm optimization and K-nearest neighbor (APSO-KNN) algorithms is proposed in this paper. Seven input variables, including nozzle diameter, layer thickness, number of perimeters, flow rate, print speed, nozzle temperature, and build orientation, are considered. The printing values of each specimen are determined using an L27 Taguchi experimental design. A total of 27 specimens are printed and experimental data for the 27 specimens are used for model training and validation. The results indicate that the proposed method can achieve a minimum classification error of 0.01 after two iterations, with a maximum accuracy of 99.0%, and high model training efficiency. It can meet the requirements of predicting surface finish for FDM parts with multiple factors and categories and can handle imbalanced data. In addition, the high accuracy demonstrates the potential of this method for predicting surface finish, and its application in actual industrial manufacturing.

Evaluating and Predicting the Long-Term Impact of the COVID-19 Pandemic on Manufacturing Sales within South Africa

Manufacturing sales forecasting is crucial for business survival in the competitive and volatile modern market. The COVID-19 pandemic has had a significant negative impact on the demand and revenue of firms globally due to disruptions in supply chains. However, the effect of the pandemic on manufacturing sales in South Africa (SA) has not been quantified. The progress of the country’s manufacturing sector’s recovery after the pandemic remains unknown or unquantified. This paper uses a Box–Jenkins approach to time series analysis to produce long-term forecasts/projections of potential manufacturing sales, thereby quantifying the effects of the pandemic shock when the projections are compared with actual manufacturing sales. The Box–Jenkins approach is chosen because of its credibility and ability to produce accurate forecasts. Long-term projections enable organisations to plan ahead and make informed decisions, develop successful recovery plans, and navigate through similar economic shocks in the future, thereby ensuring long-term business survival and sustainability of the manufacturing sector. The SARIMA (0,1,1)(0,1,1)12 model best fits the SA manufacturing sales data according to the Akaike information criterion (AIC) and Bayesian information criterion (BIC), as well as the root mean square error (RMSE) and the mean absolute error (MAE). The results indicate that SA’s manufacturing sector was negatively impacted by the COVID-19 pandemic from about April 2020, but by November 2020 manufacturing sales had recovered to levels similar to projected levels had the COVID-19 pandemic not occurred. Long-term forecasts indicate that SA manufacturing sales will continue to increase. The manufacturing sector continues to grow, leading to increased employment opportunities and a boost to the gross domestic product (GDP).

An intelligent digital twin system for paper manufacturing in the paper industry

Based on the rapid development of intelligent technologies in recent years, the digital transformation of the whole industry and society has become increasingly important. Among them, digital twins and artificial intelligence have great potentials in improving industry processes and further enhancing productivity. This paper proposes an Intelligent Digital Twin System (IDTS) based on artificial intelligence and digital twins for the paper industry. The system includes the prediction models for the stirring speed of the dump chest, the water consumption of the deflaker, the supply air pressure of the dryer, and the exhaust air temperature of the dryer. The sensors, 5G network slices, and other equipment collect related data during the papermaking process for generating twin data, and we use the prediction models to analyze the data and monitor important indicators (stirring speeds, water consumptions, supply air pressures, and exhaust air temperatures) for the manufacturing processes, which are used to improve the energy utilization and production efficiency of the paper industry and thus facilitate cost saving. We apply this intelligent digital twin system and its associated prediction models to an actual paper manufacturing factory and show their effectiveness by improving the operational efficiency and saving labor and maintenance costs.

The effect of small orientation deviation from [001] to [011] on high-temperature creep properties of nickel-based single crystal

Having regard to the inherent crystal anisotropy characteristic of nickel-based single crystal and the actual industrial manufacture, and application of the turbine blade, a trade-off between orientation deviation and performance demands that attention should be paid to estimating the influences of orientation deviation from [001] to [011] on the mechanical properties of the nickel-based single crystal. The present study conducted the creep tests of nickel-based single crystals with orientation deviation under 980 °C/260 MPa and 1050 °C/169 MPa. Results show that the orientation deviation effect of nickel-based single crystals under high temperature and low stress gradually decreases with the temperature increase. A crystal plasticity finite element method based on stress, Schmid factor, γ/γ' phase, and dislocation is employed to investigate the orientation-deviation-affected creep mechanisms. The influence of orientation deviation on creep performance is summarized by combining the macroscopic mechanical properties, fracture profile morphology, and crystal plasticity finite element analysis.

Superior sensitive, high-tensile flexible fabric film strain sensor

Developing strain sensor with higher sensitivity and larger monitoring range is urgently needed for meeting the increasing potential applications of high-performance sensors in intelligent electronics, motion signal analysis and human monitoring. Herein, via an advanced and efficient method about embedding silver nanowires on electrospun thermoplastic polyurethane fabric film modified with carbon black, a high-performance flexible strain sensor is fabricated. The strain sensor exhibits excellent electrical response abilities of the superior sensitivity (gauge factor >16,000) with strain of 360%, an ultra-wide strain range (0.1% to 200%) and outstanding durability and reliability (>10,000 cycles) under cyclic stretching-recovering operating. Furthermore, mathematical fitting models about variation of resistance (ΔR/R0) and gauge factor upon the applied strains during the stretching process are proposed, which can quantitatively describe and analysis the variation of conductive pathways and inter-particles distance under the external stimuli. It is expected that such fitting models can be used to predict conductive sensing behaviors of flexible strain sensors for actual manufacturing and improvement of products.

Nonlinear Vibration of Moving Orthotopic Films Under Oblique Support

To reduce product damage caused by the vibration instability phenomenon associated with the commutation of new material films during long-path transportation, the nonlinear vibration of orthotropic films transported under oblique support is investigated. First, on the basis of von Karman’s large deflection theory and D’Alembert’s principle, then through coordinate system transformation, the vibration partial differential equations of the system in an oblique coordinate system are established, taking into account the influence of damping. Next, the equations are discretized by the Galerkin method to obtain the system’s nonlinear vibration ordinary differential equations. Finally, the fourth-order Runge-Kutta method is used to carry out numerical calculations of the system to analyze the effects of the oblique support angle, orthotopic coefficient, and damping on the nonlinear vibration of films in transportation. The research results show that the selection of these three important parameters has an impact on the vibration characteristics of moving orthotopic films, and reasonable suggestions are made based on the parameter range for the stable motion of the system, which will help in structural adjustment and stability control during actual printing and manufacturing.

Accuracy of Intracranial Pressure Monitoring-Single Centre Observational Study and Literature Review.

Intracranial hypertension and adequacy of brain blood flow are primary concerns following traumatic brain injury. Intracranial pressure (ICP) monitoring is a critical diagnostic tool in neurocritical care. However, all ICP sensors, irrespective of design, are subject to systematic and random measurement inaccuracies that can affect patient care if overlooked or disregarded. The wide choice of sensors available to surgeons raises questions about performance and suitability for treatment. This observational study offers a critical review of the clinical and experimental assessment of ICP sensor accuracy and comments on the relationship between actual clinical performance, bench testing, and manufacturer specifications. Critically, on this basis, the study offers guidelines for the selection of ICP monitoring technologies, an important clinical decision. To complement this, a literature review on important ICP monitoring considerations was included. This study utilises illustrative clinical and laboratory material from 1200 TBI patients (collected from 1992 to 2019) to present several important points regarding the accuracy of in vivo implementation of contemporary ICP transducers. In addition, a thorough literature search was performed, with sources dating from 1960 to 2021. Sources considered to be relevant matched the keywords: "intraparenchymal ICP sensors", "fiberoptic ICP sensors", "piezoelectric strain gauge sensors", "external ventricular drains", "CSF reference pressure", "ICP zero drift", and "ICP measurement accuracy". Based on single centre observations and the 76 sources reviewed in this paper, this material reports an overall anticipated measurement accuracy for intraparenchymal transducers of around ± 6.0 mm Hg with an average zero drift of <2.0 mm Hg. Precise ICP monitoring is a key tenet of neurocritical care, and accounting for zero drift is vital. Intraparenchymal piezoelectric strain gauge sensors are commonly implanted to monitor ICP. Laboratory bench testing results can differ from in vivo observations, revealing the shortcomings of current ICP sensors.

A gray correlation based Bayesian network model for fault source diagnosis of multistage process – Small sample manufacturing system

Fault source diagnosis methodology is one of the key technologies of quality control and assurance for multi-source & multi-stage manufacturing processes, especially in small sample manufacturing systems. By analyzing the existing research on fault source diagnosis methods, a Bayesian network-based methodology is proposed. Gray correlation theory and mechanism analysis method are used in the process of Bayesian network model construction to reduce the dependence of sample data size for structure learning in the process of small sample manufacturing of complex products. In addition, two fault source diagnosis methods based on manufacturing principle analysis and reverse Bayesian network respectively are proposed. The strategy of the combined use of the two methods in the actual manufacturing scenes is given to cope with the fault source diagnosis scenario in the real manufacturing process. In the end, an example from an actual factory is provided to validate the effectiveness and efficiency of the proposed model and methodologies.

Design to Reduce Cogging Torque and Irreversible Demagnetization in Traction Hybrid Motor Using Dy-free Magnet

The PMSM (Permanent Magnet Synchronous Motor) is being studied a lot in traction motors for high efficiency and high performance. Usually, magnets containing rare earth elements are used. However, since rare earth elements are not suitable for future industries due to their limited reserves, many studies on magnets excluding rare earth elements are being conducted. Magnets excluding rare earth elements have a low coercive force and are vulnerable to irreversible demagnetization, so their design must be robust. Additionally, the design used for reducing the cogging torque, which is a major variable of traction motors, is also important. Therefore, in this study, a design process for reducing irreversible demagnetization and cogging torque is proposed. There are three methods for this process. The first one is the application of the tapering structure, and the second one is the tapering skew structure. The third one is the application of an asymmetric air hole. As a result of these methods, the target irreversible demagnetization ratio was satisfied and the cogging torque was reduced. This was proven through FEA (Finite Element Analysis) and verified by comparing and analyzing the experimental results and simulation results of actual manufacturing.

Deglycosylation Inactivation Initiated by a Novel Periplasmic Dehydrogenase Complex Provides a Novel Strategy for Eliminating the Recalcitrant Antibiotic Kanamycin.

Biodegradation using enzyme-based systems is a promising approach to minimize antibiotic loads in the environment. Aminoglycosides are refractory antibiotics that are generally considered non-biodegradable. Here, we provide evidence that kanamycin, a common aminoglycoside antibiotic, can be degraded by an environmental bacterium through deglycosylation of its 4'-amino sugar. The unprecedented deglycosylation inactivation of kanamycin is initiated by a novel periplasmic dehydrogenase complex, which we designated AquKGD, composed of a flavin adenine dinucleotide-dependent dehydrogenase (AquKGDα) and a small subunit (AquKGDγ) containing a twin-arginine signal sequence. We demonstrate that the formation of the AquKGDα-AquKGDγ complex is required for both the degradation activity of AquKGD and its translocation into the periplasm. Native AquKGD was successfully expressed in the periplasmic space of Escherichia coli, and physicochemical analysis indicated that AquKGD is a stable enzyme. AquKGD showed excellent degradation performance, and complete elimination of kanamycin from actual kanamycin manufacturing waste was achieved with immobilized AquKGD. Ecotoxicity and cytotoxicity tests suggest that AquKGD-mediated degradation produces less harmful degradation products. Thus, we propose a novel enzymatic antibiotic inactivation strategy for effective and safe treatment of recalcitrant kanamycin residues.

Neutron/Gamma Radial Shielding Design of Main Vessel in a Small Modular Molten Salt Reactor

The SM-MSR (small modular molten salt reactor) has a good prospect for development with regards to combining the superiority of the molten salt reactor and modularization technologies, showing the advantages of safety, reliability, low economic cost and flexibility of site selection. However, because its internal structural parts are not easily replaced, and the outer shielding structure is limited, the lifespan of the reactor vessel and its in-reactor shielding design needs to be addressed. In order to find an optimal shielding model with both high fuel efficiency and strong radiation shielding capability, five different design schemes were proposed in this work, which varied in thickness and boron concentration in inner-shielding materials. The neutron/gamma flux and DPA (displacements per atom)/helium production rates were evaluated to obtain an appropriate scheme. Several beneficial results were obtained. Considering the above factors and the actual manufacturing process, 20 cm-thick boron graphite with a 5 wt% Boron-10 concentration combined with a 1 cm-thick Hastelloy barrel was chosen as the in-reactor shielding structure. Outside the reactor, the neutron flux was reduced to 8.33 × 1010 cm−2 s−1, and the gamma flux was decreased to 1.13 × 1011 cm−2 s−1. The vessel/barrel material could maintain a lifespan of more than 10 years, while the burnup depth was 6.25% lower than that of a model without inner-shielding. The conclusions of this research can provide important references for the shielding design and parameter selections of small molten salt reactors in the future.

RETRACTED ARTICLE: Research on reliability evolutionary optimization of relays device based on Multi-Markov model

As a critical component of the present day power system, a few studies have been conducted on the optimization and future prediction for quality reliability of relay protection devices during their production stage of intelligent testing. Therefore, in this study, a Markov model of multimodal hierarchical spatial states is proposed (1) to calculate the stationary probability and comprehensive availability of different spatial state transfers (2) to predict the quality reliability of the device during production intelligence testing and (3) to infer and calculated the integrated availability of the relay protection device for its future operation during testing. Statistical results from the theoretical findings of this study are highly relevant when compared to the actual operation of relay protection device systems. The correctness of the model calculation method proposed in this study is verified, which provides a feasible method for reliability assessment of relay protection device intelligence tests. In addition, it was also found that the failure rate of the device internal module CPU has a relatively large impact on the comprehensive availability. It is therefore recommended to focus on CPU module detection and timely replacement during the maintenance cycle of on-site operations and maintenance. Finally, the CPU module failure rate threshold for production intelligence testing was amended, which is a valuable indicator for the evolutionary optimization of quality problems in actual smart manufacturing and testing.