345 GHz Band-Pass Filter Using Ultra-Precision Machining Technology

This paper presents a terahertz（THz）band-pass filter using ultra-precision machining technology based on Chebyshev filter prototype.This iris inductive window coupled waveguide filter was designed by using 8 resonant cavities with a center frequency of 345 GHz and a 7% bandwidth.The final design fulfills the desired specifications and presents the minimum insertion loss of 1.55 d B and the return loss of less than 15 d B at 345 GHz.The stop-band rejection is50 d B off the center frequency about 30 GHz,which means it has a good performance of high stop-band suppression.Compared with the recent development of THz filters,this filter possesses the characteristic of simple structure and is easy to machining.

Research of Digital Manufacturing Technology Application on Ultra-precision Optical Workpiece Machining

Digital manufacturing technology can be used in optical field to solve many problems caused by traditional machining. According to the characters of digital manufacturing and the practical applications of ultra-precision machining,the process of digital ultra-precision machining and its technical contents were presented in this paper. In the conclusions,it was stated that the digitalization of ultra-precision machining will be an economical and efficient way for the production of new sorts of optical workpieces.

Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

INFLUENCE OF WHEEL STRUCTURAL PARAMETERS ON MACHINING ACCURACY OF ULTRA-PRECISION PLANE HONING

A new idea for designing wheel patterns is presented so as to solve theproblems about machining accuracy of workpiece and wear of honing wheel in ultra-precision planehoning. The influence factors on motion principle and pattern structures are analyzed andoptimization machining parameters are obtained. By calculating effective cutting length on thesurface of workpiece cut by wheel's abrasive and the orbit of one point on the surface of workpiececontacting with wheel, the wear coefficient of different kinds of wheels and accuracy coefficient ofworkpiece machined by corresponding wheels are obtained. Furthermore, the simulation results showthat the optimal pattern structure of wheel turns out to have lower wheel wear and higher machiningaccuracy.

Study of material removal behavior on R-plane of sapphire during ultra-precision machining based on modified slip-fracture model

In this paper, the modified slip/fracture activation model has been used in order to understand the mechanism of ductile-brittle transition on the R-plane of sapphire during ultra-precision machining by reflecting direction of resultant force. Anisotropic characteristics of crack morphology and ductility of machining depending on cutting direction were explained in detail with modified fracture cleavage and plastic deformation parameters. Through the analysis, it was concluded that crack morphologies were mainly determined by the interaction of multiple fracture systems activated while, critical depth of cut was determined by the dominant plastic deformation parameter. In addition to this, by using proportionality relationship between magnitude of resultant force and depth of cut in the ductile region, an empirical model for critical depth of cut was developed.

Mesoplasticity Approach to Studies of the Cutting Mechanism in Ultra-precision Machining

There have been various theoretical attempts by researchers worldwide to link up different scales of plasticity studies from the nano-, micro- and macro-scale of observation, based on molecular dynamics, crystal plasticity and continuum mechanics. Very few attempts, however, have been reported in ultra-precision machining studies. A mesoplasticity approach advocated by Lee and Yang is adopted by the authors and is successfully applied to studies of the micro-cutting mechanisms in ultra-precision machining. Traditionally, the shear angle in metal cutting, as well as the cutting force variation, can only be determined from cutting tests. In the pioneering work of the authors, the use of mesoplasticity theory enables prediction of the fluctuation of the shear angle and micro-cutting force, shear band formation, chip morphology in diamond turning and size effect in nano-indentation. These findings are verified by experiments. The mesoplasticity formulation opens up a new direction of studies to enable how the plastic behaviour of materials and their constitutive representations in deformation processing, such as machining can be predicted, assessed and deduced from the basic properties of the materials measurable at the microscale.

Systematic analysis of error sources during ultra-precision machining

During ultra-precision machining, machining accuracy is determined by many factors and interaction of these factors. Error sources are systematically analyzed for ultra-precision machine tools, and the influencing degree of each factor is presented to provide orientation for error reduction and error compensation.

Elbow precision machining technology by abrasive flow based on direct Monte Carlo method

The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.

Dynamic Accuracy Design Method of Ultra-precision Machine Tool

Ultra-precision machine tool is the most important physical tool to machining the workpiece with the frequency domain error requirement, in the design process of which the dynamic accuracy design(DAD) is indispensable and the related research is rarely available. In light of above reasons, a DAD method of ultra-precision machine tool is proposed in this paper, which is based on the frequency domain error allocation.The basic procedure and enabling knowledge of the DAD method is introduced. The application case of DAD method in the ultra-precision flycutting machine tool for KDP crystal machining is described to show the procedure detailedly. In this case, the KDP workpiece surface has the requirements in four different spatial frequency bands, and the emphasis for this study is put on the middle-frequency band with the PSD specifications. The results of the application case basically show the feasibility of the proposed DAD method. The DAD method of ultra-precision machine tool can effectively minimize the technical risk and improve the machining reliability of the designed machine tool. This paper will play an important role in the design and manufacture of new ultra-precision machine tool.

Leveraging Geospatial Technology for Smallholder Farmer Credit Scoring

According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food consumed there;their farming activities are therefore critical to the economies of their countries and to the global food security. However, these farmers face the challenges of limited access to credit, often due to the fact that many of them farm on unregistered land that cannot be offered as collateral to lending institutions;but even when they are on registered land, the fear of losing such land that they should default on loan payments often prevents them from applying for farm credit;and even if they apply, they still get disadvantaged by low credit scores (a measure of creditworthiness). The result is that they are often unable to use optimal farm inputs such as fertilizer and good seeds among others. This depresses their yields, and in turn, has negative implications for the food security in their communities, and in the world, hence making it difficult for the UN to achieve its sustainable goal no.2 (no hunger). This study aimed to demonstrate how geospatial technology can be used to leverage farm credit scoring for the benefit of smallholder farmers. A survey was conducted within the study area to identify the smallholder farms and farmers. A sample of surveyed farmers was then subjected to credit scoring by machine learning. In the first instance, the traditional financial data approach was used and the results showed that over 40% of the farmers could not qualify for credit. When non-financial geospatial data, i.e. Normalized Difference Vegetation Index (NDVI) was introduced into the scoring model, the number of farmers not qualifying for credit reduced significantly to 24%. It is concluded that the introduction of the NDVI variable into the traditional scoring model could improve significantly the smallholder farmers’ chances of accessing credit, thus enabling such a farmer to be better evaluated for credit on the basis of the health of their crop, rather than on a traditional form of collateral.

Implementing an innovated liver ex-situ machine perfusion technology:The 2018 Joint International Congress of ILTS,ELITA and LICAGE

The 2018 Joint International Congress of ILTS,ELITA and LICAGE were held in Lisbon,Portugal on May 23–26,2018.The exciting and innovative program brought together 1144 experts in liver transplantation(LT)such as surgeons,physicians or basic scientists from 61 countries.The presentations included 110 invited speakers,181 oral presentations,and 545 posters.This editorial highlights some of the most innovative and impactful presentations in

3D printing for ultra-precision machining:current status,opportunities,and future perspectives

Additive manufacturing,particularly 3D printing,has revolutionized the manufacturing industry by allowing the production of complex and intricate parts at a lower cost and with greater efficiency.However,3D-printed parts frequently require post-processing or integration with other machining technologies to achieve the desired surface finish,accuracy,and mechanical properties.Ultra-precision machining(UPM)is a potential machining technology that addresses these challenges by enabling high surface quality,accuracy,and repeatability in 3D-printed components.This study provides an overview of the current state of UPM for 3D printing,including the current UPM and 3D printing stages,and the application of UPM to 3D printing.Following the presentation of current stage perspectives,this study presents a detailed discussion of the benefits of combining UPM with 3D printing and the opportunities for leveraging UPM on 3D printing or supporting each other.In particular,future opportunities focus on cutting tools manufactured via 3D printing for UPM,UPM of 3D-printed components for real-world applications,and post-machining of 3D-printed components.Finally,future prospects for integrating the two advanced manufacturing technologies into potential industries are discussed.This study concludes that UPM is a promising technology for 3D-printed components,exhibiting the potential to improve the functionality and performance of 3D-printed products in various applications.It also discusses how UPM and 3D printing can complement each other.

Is the Genie of Artificial Intelligence Technology Out of the Bottle and Control?(A Short Review)

In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.

Cervical Cancer Prediction Empowered with Federated Machine Learning

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

Dynamic modeling of ultra-precision fly cutting machine tool and the effect of ambient vibration on its tool tip response

The dynamic performances of an ultra-precision fly cutting machine tool(UFCMT)has a dramatic impact on the quality of ultra-precision machining.In this study,the dynamic model of an UFCMT was established based on the transfer matrix method for multibody systems.In particular,the large-span scale flow field mesh model was created;and the variation in linear and angular stiffness of journal and thrust bearings with respect to film thickness was investigated by adopting the dynamic mesh technique.The dynamic model was proven to be valid by comparing the dynamic characteristics of the machine tool obtained by numerical simulation with the experimental results.In addition,the power spectrum density estimation method was adopted to simulate the statistical ambient vibration excitation by processing the ambient vibration signal measured over a long period of time.Applying it to the dynamic model,the dynamic response of the tool tip under ambient vibration was investigated.The results elucidated that the tool tip response was significantly affected by ambient vibration,and the isolation foundation had a good effect on vibration isolation.

Active vibration control of spindle in ultra-precision turning machine

In order to minimize vibration and improve rotary precision of spindle, we apply active vibration control technique to ultra-precision turning machine based on the analysis of vibration characteristic of aerostatic bearing spindle. Using aerostatic bearing itself as actuator, the vibration of spindle is controlled by adjusting admission pressure respectively and by changing pressure distribution in the bearing. The experiments and simulations prove that this method can minimize the vibration of spindle effectively.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

Technological requirements of profile machining

The term ‘profile machining’ is used to refer to the milling of vertical surfaces described by profile curves. Profile machining requires higher precision (1/1000 mm) than regular 3D machining (1/100 mm) with the erosion of sharp vertices should being especially avoided. Although, profile machining is very essential for making trimming and flange dies, it seldom brought into focus. This paper addresses the technological requirements of profile machining including machining width and depth control, minimizing toolware, and protecting sharp vertices. Issues of controller alarms are also addressed.

Leveraging Geospatial Technologies for Resource Optimization in Livestock Management

Geospatial technologies can be leveraged to optimize the available resources for better productivity and sustainability. The resources can be human, software and hardware equipment and their effective management can enhance operational efficiency through better and informed decision making. This review article examines the application of geospatial technologies, including GPS, GIS, and remote sensing, for optimizing resource utilization in livestock management. It compares these technologies to traditional livestock management practices and highlights their potential to improve animal tracking, feed intake monitoring, disease monitoring, pasture selection, and rangeland management. Previously, animal management practices were labor-intensive, time-consuming, and required more precision for optimal animal health and productivity. Digital technologies, including Artificial Intelligence (AI) and Machine Learning (ML) have transformed the livestock sector through precision livestock management. However, major challenges such as high cost, availability and accessibility to these technologies have deterred their implementation. To fully realize the benefits and tremendous contribution of these digital technologies and to address the challenges associated with their widespread adoption, the review proposes a collaborative approach between different stakeholders in the livestock sector including livestock farmers, researchers, veterinarians, industry professionals, technology developers, the private sector, financial institutions and government to share knowledge and expertise. The collaboration would facilitate the integration of various strategies to ensure the effective and wide adoption of digital technologies in livestock management by supporting the development of user-friendly and accessible tools tailored to specific livestock management and production systems.

Research and test of the adaptive quadrature demodulation technology for silicon micro-machined gyroscope

A program of adaptive quadrature demodulation is proposed to supply the gaps in the traditional analog detection technology of a silicon micro-machined gyroscope (SMG). This program is suitable for digital phase locked loop (DPLL) drive technology that proposed in other papers. In addition the program adopts an adaptive filtering algorithm, which selects the in-phase and quadrature components that are outputs of the DPLL of the SMG's drive mode as reference signals to update the amplitude of the in-phase and quadrature components of the input signal by iteratively. An objective of the program is to minimize the mean square error of the accurate amplitudes and the estimated amplitudes of SMG's detection mode. The simulation and test results prove the feasibility of the program that lays the foundation for the further improvement of the SMG's system performance and the implementation of the SMG system's self-calibration and self-demarcation in future.