Configuration Tool Research Articles

Robust estimation of clinch joint characteristics based on data-driven methods

Given a steadily increasing demand on multi-material lightweight designs, fast and cost-efficient production technologies, such as the mechanical joining process clinching, are becoming more and more relevant for series production. Since the application of such joining techniques often base on the ability to reach similar or even better joint loading capacities compared to established joining processes (e.g., spot welding), few contributions investigated the systematic improvement of clinch joint characteristics. In this regard, the use of data-driven methods in combination with optimization algorithms showed already high potentials for the analysis of individual joints and the definition of optimal tool configurations. However, the often missing consideration of uncertainties, such as varying material properties, and the related calculation of their impact on clinch joint properties can lead to poor estimation results and thus to a decreased reliability of the entire joint connection. This can cause major challenges, especially for the design and dimensioning of safety-relevant components, such as in car bodies. Motivated by this, the presented contribution introduces a novel method for the robust estimation of clinch joint characteristics including uncertainties of varying and versatile process chains in mechanical joining. Therefore, the utilization of Gaussian process regression models is demonstrated and evaluated regarding the ability to achieve sufficient prediction qualities.

Shaping of the Fresnel lens array on roller molds by 6-axis diamond machining

The Fresnel lens arrays are rapidly developing with the increasing demand for better optical performances and capabilities. For the roll-to-roll embossing of optical films, direct diamond machining of the Fresnel lenses on roller molds has been realized by installing an additional goniometer on the 5-axis ultra-precision machine tool in the previous study. However, this method owns two shortcomings, i.e., the communication delay between the machine tool and the goniometer and the poor positioning accuracy of the goniometer. In this paper, a 6-axis diamond shaping method is proposed to fabricate the Fresnel lens array on the roller periphery by utilizing a commercial 6-axis ultra-precision machine tool. It is ensured that the side cutting edge of the diamond tool matches the Fresnel lenses profiles during shaping. Also, the tool rake face is always perpendicular to both the roller tangent plane at the cutter location point and the cutting velocity relative to the roller via the synchronized rotations of the A-, B- and C-axes to avoid the tool–workpiece interference. The process to calibrate installation errors is introduced and utilized. The tool path is generated according to the cutting tool geometry, the lens parameters and the machine tool configuration. Experiments are carried out by machining the designed Fresnel lens array on a roller mold, which consists of lenses with different feature heights. The surface qualities of the lens arrays are evaluated and the influence of the block time to run the CNC code are also analyzed. The experimental results verify that the proposed method is effective and flexible for machining of the Fresnel lens array on roller molds.

Determining the influence of different process parameters on the versatile self-piercing riveting process using numerical methods

Owing to the increasing use of multi-material construction and the resulting material incompatibilities, mechanical joining technologies are gaining importance. The reasons for this are the variety of joining possibilities as well as the high joint load-bearing capacities. However, the currently rigid tool systems cannot react flexibly to changing process conditions, such as varying sheet thicknesses or strengths as they require a change in the tool configuration. Therefore, a novel, versatile self-piercing riveting process (V-SPR) is proposed to improve the applicability of joining several sheet material combinations by considering only one rivet-die combination. Although previous studies have demonstrated the potential of V-SPR for joining equal materials, the present understanding of the process lacks detailed investigations regarding optimal tool configurations and sheet-joining tasks, such as varying the total and individual blank thicknesses. In this regard, a systematic parameter study in combination with statistical analyses is conducted to determine the applicability and feasibility of V-SPR using EN AW-6014 as an example. The process recommendations and limitations discussed in this paper pave the way for meaningful use of novel rivet geometry in versatile process chains.

Selection of cutting tool for desired surface finish in milling Machine using Taguchi optimization methodology

In this paper, Taguchi's method for optimisation has been showcased to select a cutting tool on vertical milling machine when processing with (i) carbide insert tool and (ii) polycrystalline diamond tool, subjected to specify surface finish i.e., Ra 1.6 maximum. The milling machine parameters are validated for Depth of Cut (DOC), Feed Rate, and Cutting speed with tools configuration. The experiment results show that the different cutting tool with optimal milling parameter combinations provides variable surface finish values. After obtaining variable data, the analysis was conducted with the team's support and decided the best suitable tool for machining, providing a surface finish under a controlled limit. A comparative experiment has been shown to optimise the tool selection for procurement. A comparative study is being conducted between two tools one is of carbide and the second one is of polycrystalline diamond Analysis.of.Variance (ANOVA) is being applied to analyse the adverse effect of process parameters on the machining process. This work helps in the procurement during Design For Manufacturing (DFM) process. For this, the Taguchi methodology is being utilised to optimise tool selection. The research concludes that the Taguchi methodology is optimum for solving the nth issues with minimum trials and helps to select the tool.

Investigation of the Surface Roughness and Surface Uniformity of a Hybrid Sandwich Structure after Machining.

The parameters of surface roughness Ra, Rz and Rmax as well as surface topography Sa, Sz, Sp and Sv of the two-layer sandwich structure composed of an AW-2024 T3 aluminum alloy (Al) and a carbon-fiber-reinforced polymer (CFRP) were measured to determine an impact of the machining configuration (arrangement of the materials forming a sandwich structure) and the type of tool (presence of the tool coating) on the quality of the surface obtained through circumferential milling. The measurements revealed that milling produced different values of surface roughness for the aluminum alloy and the CFRP composite with values of 2D and 3D surface roughness being higher for the composite layer. The highest value of Ra of 1.10 µm was obtained for the surface of the CFRP composite using the CFRP/Al configuration and a TiAlN-coated tool. The highest values of the Rz (6.51 µm) and Rmax (8.85 µm) surface roughness parameters were also obtained for the composite layer using the same machining configuration and type of tool.

Tool Positioning Error Minimization during Robotic Milling Based on the Genetic Algorithm Technique

Compared to CNC machines, robotic milling has performance limitations such as accuracy and quality. The main source of the robot’s inaccuracy during machining is the flexibility of its parts (body or joints). This error disturbs the movement of the end effector, affecting the part’s surface finish. In order to improve the robot’s accuracy and minimize the positioning error of the end effector during the milling operation, this paper presents, first, a method based on the elasto-static model to predict the Cartesian deflection of the end effector of a three DOF redundant planar robot, and second, optimization techniques with original objective functions based on the single and multi-objective genetic algorithm, which will be presented and compared. The programming of the two methods and the results of the study will be done using MATLAB software. The analysis of simulation results of the two optimization techniques GA and MOGA revealed that the tool configuration and cutting parameters used for robotic milling have a direct influence on the robot's path accuracy and milling performance. Whereas for a φ0=69.6, φf=72.43 the maximum tool deviation in its path is Δxmax ≈ |0.125| mm with a maximum roughness profile height Ra = 1600 μm. While the positioning error is said to be minimal Δxmin ≈ |0.025| when φ0= -38.67, φf = -35.92, and the roughness Ra= 25 μm.

MobyDeep: A lightweight CNN architecture to configure models for text classification

Nowadays, trends in deep learning for text classification are addressed to create complex models to deal with huge datasets. Deeper models are usually based on cutting edge neural network architectures, achieving good results in general but demanding better hardware than shallow ones. In this work, a new Convolutional Neural Network (CNN) architecture (MobyDeep) for text classification tasks is proposed. Designed as a configurable tool, resultant models (MobyNets) are able to manage big corpora sizes under low computational costs. To achieve those milestones, the architecture was conceived to produce lightweight models, having their internal layers based on a new proposed convolutional block. That block was designed and customized by adapting ideas from image to text processing, helping to squeezing model sizes and to reduce computational costs. The architecture was also designed as a residual network, covering complex functions by extending models up to 28 layers. Moreover, middle layers were optimized by residual connections, helping to remove fully connected layers on top and resulting in Fully CNN. Corpus were chosen from the recent literature, aiming to define real scenarios when comparing configured MobyDeep models with other state-of the-art works. Thus, three models were configured in 8, 16 and 28 layers respectively, offering competitive accuracy results.

A Comparative Study of Mechanical and Microstructural Behavior for Metal Active Gas and Friction Stir Welded Micro-Alloyed Structural Steel

Manufacturing tiny components into gigantic structures seems unimaginable without welding connections, whether it is for materials, parts, structures, or equipment. In the recent competitive market scenario, manufacturing industries are desperately looking for a viable alternative to fusion-based conventional material joining technologies, to improve upon cost-effectiveness along with performance. The present investigation is to evaluate the performance of structural steel thick plate joints prepared by advanced solid-state friction stir welding (FSW) over conventional metal active gas welding (MAG). The FSW experiments were carried out with different tool designs and configurations. The outcomes were evaluated in terms of microstructural integrity and mechanical joint resistance. Impressive results were obtained with FSW joints, characterized by an almost defect-free microstructure with a leaner heat-affected zone and higher joint resistance as compared to conventional MAG-welded joints.

Practical Method for Optimizing Capacities of Private Generators Installed in Hospital Buildings During Power Outages

Abstract In stand-alone operations, on-site generators must balance and meet demand at any time for second-by-second fluctuations in output and load demand. However, the previous optimization tool for private generator configuration in hospital buildings did not consider demand sufficiency. Herein, this qualitative electricity problem was solved by proposing a new optimization method that considers the balance of power supply and demand in the stand-alone operation of on-site generators during power outages. As a demand sufficiency condition, a power balance simulator obtained available configurations of private generators that can be operated within the standard alternating current (AC) frequency range of 49–51 Hz. We also compared case study results by applying these constraints to the findings of earlier studies. The same case study from an earlier paper reported that the optimal amount of photovoltaic systems installed is approximately the upper limit (set at 600 m2 in this calculation) and the optimal solution. In contrast, the optimization results with additional constraints to keep frequency fluctuations within specified limits yielded an optimal value significantly less than the previous optimization; one case study showed that the optimal installation amount of photovoltaics was 0 m2. However, the key equipment in this study was the emergency diesel generator. The emergency generator compensates for power shortages and balances supply and demand under power outages. The results suggest that case studies with demand-satisfying conditions tend to select equipment configurations that effectively improve the expected power shortage rate.

ReMo3D – an open-source Python package for 2D and 3D simulation of normal and lateral resistivity logs

An open-source Python package is presented, ReMo3D, which allows the generation of synthetic normal and lateral resistivity logs for 2D and 3D models. The package is built around a finite element mesh generator Gmsh and a high-performance multiphysics finite element software Netgen/NGSolve and supports distributed-memory parallel computation. The examples included in the paper show that the developed software can accurately simulate the measurement process and produce detailed synthetic normal and lateral resistivity logs. In addition, basic information about normal and lateral tools such as tool configurations, measurement principles, nomenclature and a brief history of utilization is included in the paper.

Деформации в нестационарной стадии прессования прутка из алюминиевого сплава с малым коэффициентом вытяжки

Introduction. It is noted that extrusion is the main procurement process in the aluminum alloys forming operations. At the same time, the process has such a disadvantage as the nonstationarity of the metal plastic flow. The work aim is to establish the inhomogeneity deformation level of the pressed rod front part by numerical simulation using the finite element method. The study objectives are to formulate the extrusion process boundary conditions, to obtain a solution and to evaluate the inhomogeneity degree. Research methods: the finite element method was used to evaluate the deformed state. The actions sequence included the creation of primary deformation zone shape and the tool configuration. The mutual movement of the tool and the deformable material is set using the appropriate boundary conditions. The deformable medium is a ductile material with power-law hardening, the physical and mechanical properties correspond to the aluminum alloy of the 6000 series. Results and discussion: It is revealed that the strain degree in the pressed rod front part is extremely nonuniform distributed; differences above 300% are recorded. The strain degree distribution dependences in the rod cross sections are constructed depending on the distance from the front end at different relative radial coordinates. It is revealed that the rod central layers acquire a constant level of the strain degree earlier than the peripheral layers. The stationary process is achieved with less metal motion. The work result application scope is the technological study of rational metal cutting of aluminum alloys at the extrusion final stage in order to use recyclable waste more rationally. Conclusions. In the extrusion process with a low elongation ratio, the strain degree is distributed nonuniform both along the press rod cross and along its length. The rod front part remains weakly deformed both at the periphery and in the center in the nonstationary initial extrusion stage. It often forces to send for remelting due to the insufficiently developed metal structure. At the same time, if the limits on the minimum possible degree of deformation are set, then using the results of the calculation by the finite element method, the minimum length of the metal to be removed can be set, thereby reducing the mass of waste sent for remelting.

An Investigation on the Total Thickness Variation Control and Optimization in the Wafer Backside Grinding Process.

The wafer backside grinding process has been a crucial technology to realize multi-layer stacking and chip performance improvement in the three dimension integrated circuits (3D IC) manufacturing. The total thickness variation (TTV) control is the bottleneck in the advanced process. However, the quantitative analysis theory model and adjustment strategy for TTV control are not currently available. This paper developed a comprehensive simulation model based on the optimized grinding tool configuration, and several typical TTV shapes were obtained. The relationship between the TTV feature components and the spindle posture was established. The linear superposition effect of TTV feature components and a new formation mechanism of TTV shape were revealed. It illustrated that the couple variation between the two TTV feature components could not be eliminated completely. To achieve the desired wafer thickness uniformity through a concise spindle posture adjustment operation, an effective strategy for TTV control was proposed. The experiments on TTV optimization were carried out, through which the developed model and TTV control strategy were verified to play a significant role in wafer thickness uniformity improvement. This work revealed a new insight into the fine control method to the TTV optimization, and provided a guidance for high-end grinding tool and advanced thinning process development.

PSO-X: A Component-Based Framework for the Automatic Design of Particle Swarm Optimization Algorithms

The particle swarm optimization (PSO) algorithm has been the object of many studies and modifications for more than 25 years. Ranging from small refinements to the incorporation of sophisticated novel ideas, the majority of modifications proposed to this algorithm have been the result of a manual process in which developers try new designs based on their own knowledge and expertise. However, manually introducing changes is very time consuming and makes the systematic exploration of all the possible algorithm configurations a difficult process. In this article, we propose to use automatic design to overcome the limitations of having to manually find performing PSO algorithms. We develop a flexible software framework for PSO, called PSO-X, which is specifically designed to integrate the use of automatic configuration tools into the process of generating PSO algorithms. Our framework embodies a large number of algorithm components developed over more than 25 years of research that have allowed PSO to deal with a large variety of problems, and uses <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">irace</monospace> , a state-of-the-art configuration tool, to automatize the task of selecting and configuring PSO algorithms starting from these components. We show that <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">irace</monospace> is capable of finding high-performing instances of PSO algorithms never proposed before.

Real-time and high-sensitivity refractive index sensing with an arched optofluidic waveguide

Refractive index (RI) sensing plays an important role in analytical chemistry, medical diagnosis, and environmental monitoring. The optofluidic technique is considered to be an ideal tool for RI sensor configuration for its high integration, high sensitivity, and low cost. However, it remains challenging to achieve RI measurement in real time with high sensitivity and low detection limit (DL) simultaneously. In this work, we design and fabricate a RI sensor with an arched optofluidic waveguide by monitoring the power loss of the light passing through the waveguide, which is sandwiched by the air-cladding and the liquid-cladding under test, we achieve RI detection of the sample in real time and with high sensitivity. Furthermore, both numerical simulation and experimental investigation show that our RI sensor can be designed with different geometric parameters to cover multiple RI ranges with high sensitivities for different applications. Experimental results illustrate that our sensor is capable to achieve a superior sensitivity better than -19.2 mW/RIU and a detection limit of 5.21×10-8 RIU in a wide linear dynamic range from 1.333 to 1.392, providing a promising solution for real-time and high-sensitivity RI sensing.

S-ProvFlow. Storing and Exploring Lineage Data as a Service

Abstract We present a set of configurable Web service and interactive tools, s-ProvFlow, for managing and exploiting records tracking data lineage during workflow runs. It facilitates detailed analysis of single executions. It helps users manage complex tasks by exposing the relationships between data, people, equipment and workflow runs intended to combine productively. Its logical model extends the PROV standard to precisely record parallel data-streaming applications. Its metadata handling encourages users to capture the application context by specifying how application attributes, often using standard vocabularies, should be added. These metadata records immediately help productivity as the interactive tools support their use in selection and bulk operations. Users rapidly appreciate the power of the encoded semantics as they reap the benefits. This improves the quality of provenance for users and management. Which in turn facilitates analysis of collections of runs, enabling users to manage results and validate procedures. It fosters reuse of data and methods and facilitates diagnostic investigations and optimisations. We present S-ProvFlow's use by scientists, research engineers and managers as part of the DARE hyper-platform as they create, validate and use their data-driven scientific workflows.

Puskesmas Medical Record Information System (Case Study: Gedangan Health Center, Sidoarjo Regency)

Puskesmas Gedangan, Sidorajo District, in recording Medical Record and administration of patient visit and data processing to patient still manual, so administrative process takes a little time, either in handling patient, or in case of making report. Medical Record Information System of Gedangan Public Health Center of Sidoarjo Regency, Medical Record Tool, Patient Data, Drug Data, Action Data, Doctor Data, and admin configuration, but the system is not built all the services in Puskesmas Gedangan Sidoarjo District. In this research used the Waterfall method, where the means to analyze the problems that occurred in Gedangan Public Health Center of Sidoarjo Regency and a Medical Record Information system which was immediately implemented in the form of computer based application. The results of research on the application of Medical Record Information System, at Public Health Center of Gedangan Kabuaten Sidoarjo, on the guided performance of the employees, so that the process of health services to the community can be done quickly and avoid the mistakes in making the patient's Medical Record report.

On the Configuration of More and Less Expressive Logic Programs

AbstractThe decoupling between the representation of a certain problem, that is, its knowledge model, and the reasoning side is one of main strong points of model-based artificial intelligence (AI). This allows, for example, to focus on improving the reasoning side by having advantages on the whole solving process. Further, it is also well known that many solvers are very sensitive to even syntactic changes in the input. In this paper, we focus on improving the reasoning side by taking advantages of such sensitivity. We consider two well-known model-based AI methodologies, SAT and ASP, define a number of syntactic features that may characterise their inputs, and use automated configuration tools to reformulate the input formula or program. Results of a wide experimental analysis involving SAT and ASP domains, taken from respective competitions, show the different advantages that can be obtained by using input reformulation and configuration.

Target Chase, Wall Building, and Fire Fighting: Autonomous UAVs of Team NimbRo at MBZIRC 2020

The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020 posed diverse challenges for unmanned aerial vehicles (UAVs). We present our four tailored UAVs, specifically developed for individual aerial-robot tasks of MBZIRC, including custom hardwareand software components. In Challenge 1, a target UAV is pursued using a high-efficiency, onboard object detection pipeline to capture a ball from the target UAV. A second UAV uses a similar detection method to find and pop balloons scattered throughout the arena. For Challenge 2, we demonstrate a larger UAV capable of autonomous aerial manipulation: Bricks are found and tracked from camera images. Subsequently, they are approached, picked, transported, and placed on a wall. Finally, in Challenge 3, our UAV autonomously finds fires using LiDAR and thermal cameras. It extinguishes the fires with an onboard fire extinguisher. While every robot features task-specific subsystems, all UAVs rely on a standard software stack developed for this particular and future competitions. We present our mostly open-source software solutions, including tools for system configuration, monitoring, robust wireless communication, highlevel control, and agile trajectory generation. For solving the MBZIRC 2020 tasks, we advanced the state of the art in multiple research areas like machine vision and trajectory generation. We present our scientific contributions that constitute the foundation for our algorithms and systems and analyze the results from the MBZIRC competition 2020 in Abu Dhabi, where our systems reached second place in the Grand Challenge. Furthermore, we discuss lessons learned from our participation in this complex robotic challenge.

Functionally Graded Al2O3-CTZ Ceramics Fabricated by Spark Plasma Sintering.

We studied the fabrication of functionally graded Al2O3–CeO2-stabilized-ZrO2 (CTZ) ceramics by spark plasma sintering. The ceramic composite exhibits a gradual change in terms of composition and porosity in the axial direction. The composition gradient was created by layering starting powders with different Al2O3 to CTZ ratios, whereas the porosity gradient was established with a large temperature difference, which was induced by an asymmetric graphite tool configuration during sintering. SEM investigations confirmed the development of a porosity gradient from the top toward the bottom side of the Al2O3–CTZ ceramic and the relative pore volume distributed in a wide range from 0.02 to 100 µm for the samples sintered in asymmetric configuration (ASY), while for the reference samples (STD), the size of pores was limited in the nanometer scale. The microhardness test exhibited a gradual change along the axis of the ASY samples, reaching 10 GPa difference between the two opposite sides of the Al2O3–CTZ ceramics without any sign of delamination or cracks between the layers. The flexural strength of the samples for both series showed an increasing tendency with higher sintering temperatures. However, the ASY samples achieved higher strength due to their lower total porosity and the newly formed elongated CeAl11O18 particles.

AMALGAMATION OF INDIRECT GAMIFICATION INTO DEVELOPMENT AND OPERATIONS (DEVOPS) COURSE TEACHING

The work investigates the effect of indirect Gamification in Development and Operations (DevOps) Course teaching. The software development team consisting of multiple contributors coordinates in the collaborative work environment to achieve specific predefined goals in a regulated and controlled fashion. In DevOps Course, the Installation and configuration of the various software tools are useful in the context of application development. To teach DevOps Tools precisely to achieve the learning outcome is a skilled task for a trainer. From the perspective of the learner, the learning environment has to be encouraging and exciting. Pedagogical techniques and ICT tools play an essential role during the knowledge transfer process. The motivation and reward to the Student are essential in achieving the learning outcomes of the Course. The author used the third-party Competition as an indirect Gamification technique to achieve the learning outcomes of the Course. The author encouraged the students to participate in the Hacktoberfest Competition to use the practical skills learned in the Course. The Under Graduate (UG) and Post Graduate (PG) Students have gone through the regular sessions of DevOps. For the participation purpose, both groups of students communicated on one platform. The students who succeeded faster during the GitHub Pull Request (PR) submission shared their experiences with other participants. The PG students participated 68.75% higher than UG students. Minimum of four PR submissions on GitHub and acceptance by the repository maintainer are the task completion criteria. The active participation of the small number of UG students became a motivational factor for the PG students. The Gaussian distribution on the marks obtained by the experimental group shows the absence of outliers. The research shows that the effectiveness of indirect Gamification depends on the age group, level, course content, and learning environment. The participation of a faculty member in the Competition during the learning activity boosts the desire of the Student to complete the task. The experimental group of 15 Students has outperformed in terms of the marks obtained compared to the control group of 52 students.