bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Strengthening and Dragging Characteristics of Dilute Sn Solders Designed for Electronic Packages
Authors: Guo Zhenfeng , Gher Thomas J. , Sarafids Cynthia T. , Lucey George K. 
Published: July 2023

Abstract
The monotonic plastic flow behavior and deformation kinetics of solder joints in shear at room temperature were determined for some dozen dilute Sn solders designed for Pb-free alternatives in electronic packages. In, Bi, Ag and Cu elements were involved in alloys based on Sn. The Bi solute atoms (s.a) in the Sn host lattice were found to be a significant species in solid solution strengthening and the In s.a. a significant species in impeding recovery. The Bi solute strengthening process was in accord with Labusch’s statistical model (Labusch, 1970). The model relation otherwise predicted a Bi and In interaction strengthening. The rate-controlling mechanisms in recovery were speculated to be an In-solute-viscous-dragging and glide-controlled creep and a Bi-solute-dragging and climb-controlled creep in the corresponding alloys. The actions of electron concentration (e/a) were noted.
An Introduction to Predict the Fatigue Lifetime and Strengthening Directions of Solder Joint in Electronic Packages
Authors: Guo Zhenfeng 
Published: July 2023

Abstract
An overview was given to Coffin-Manson (C-M) methodology, fracture mechanics technology, and their applications to the fatigue lifetime prediction of solder joints in electronic packages, and their limitations were analyzed as well. An empirical relation of fatigue cracked area growth rate vs hysteresis energy rate was introduced to predict the fatigue lifetime and the strengthening directions of solder joints. To predict the strengthening directions was to predict the failure mechanisms. The predicted fatigue failure rate-controlled factors tell us that the TMF failure of Pb-Sn solder joints is determined by Sn matrix fracture capacity associated with subgrain structure and persistent slip bands. The Pb-phase fracture capacity is smaller as indicated by the propensity of Pb-phase cracking at me intermediate temperatures. The fatigue cracking resistance of the grain and interphase boundaries is high at higher temperatures and larger strain ranges. A fatigue lifetime prediction system was in perspective.
Significance of Quill Motion for Efficiency and Accuracy in Jig Grinding With Electro-Deposit CBN Wheel
Authors: Matsuo T. , Sakamoto H. , Touge M. 
Published: July 2023

Abstract
Jig grinding is well known as a precision internal machining process for high precision products such as dies and fixtures. Jig grinders are usually used for grinding holes and various contour holes to accurate size and location. In this research, an investigation to realize high productivity and high accuracy in Jig grinding was performed on a hardened die steel with electro-deposit CBN grinding wheels under different grinding conditions. In special, the effects of quill motion and wheel speed on grinding characteristics have been clarified. Grinding forces (Ft, Fn), surface roughness, and accuracy (roundness) were measured, and also the machining mechanism in Jig grinding was discussed from the result of SEM observations. A clear reduction of grinding forces was found by an application of quill motion, and also better surface finish was obtained. The reason for this is related with the fracture of the grain corners. Increasing wheel speed was also very effective for decreasing grinding force and roughness.
Surface Analysis of Zirconia-Toughened Alumina Lapped With Polycrystalline Diamond Powders
Authors: Marinescu Ioan D. , Turco Marc D. 
Published: July 2023

Abstract
Flat lapping of zirconia-toughened alumina with diamond powders was performed to investigate the influence of contact pressure and abrasive size on the surface profile. Scanning electron microscopy, profilometry and interferometry were used to analyze the surface finish and surface profiles obtained. The wear mechanisms that occur are discussed and related to the surface finish and profiles produced. Results showed that the amount and action of deformation-controlled and micro-fracture controlled wear differ with respect to contact pressure and abrasive size. Interactions occur differently between wear mechanisms resulting in optimum loads or contact pressures with respect to surface finish within the parameters used for this research. The interaction between wear mechanisms can also result in producing surfaces that are similar in finish but have different profiles.
Thermal Simulation and Model-Based Adaptive Control of Plasma-Arc Processing on Metal Plates
Authors: Doumanidis Charalabos C. , Fourligkas Nikolaos 
Published: July 2023

Abstract
This article addresses real-time control of the temperature distribution in a wide class of thermal processing operations on metal plates. A generic plasma-arc experimental workstation and a flexible numerical simulation of the heat flow is developed for this purpose. However, the inherent nonlinearity of heat transfer mechanisms and the limitations of infrared thermal sensing lead to the establishment of a linearized multiple-input, multiple-output model, with in-process identification of its parameters. This real-time thermal model serves in a Smith-predictor scheme as a reference to the adaptive controller. The thermal regulation system adjusts the power and guides the motion of the torch to the part region with the largest deviation from a desired temperature distribution, using an in-process thermal optimization method based on a moving complex pattern. Besides off-line validation of the models, the closed-loop thermal control strategy is tested both in simulation and in the laboratory on elementary metal processing related to thermal rapid prototyping applications.
Finite Element Analysis of Electromagnetic Forming of Tubes With Fittings
Authors: Mahanian Saba , Blackwell David B. 
Published: July 2023

Abstract
Thousands of feet of tubing are used in building a complex vehicle like an airplane and therefore, it is imperative to have an efficient process to form and connect various tubes together. Electromagnetic expansion forming is a high energy rate forming process which uses an electrical coil inside a tube to produce high pressures (10,000 to 30,000 psi) in short time period (about 20 micro seconds). The pressures are used to expand the aluminum tube against a metal die, in this case another aluminum fitting. The explicit, nonlinear, finite element program, DYNA2D was used to make an axisymmetric model of this forming process. The process involves considerable geometrical as well as material nonlinearity. The effects of the geometrical parameters of the fitting, such as the number of grooves, their depths and their widths, were studied. The effects of process parameters, such as the magnitude and shape of the pressure pulse, were also studied. To test the performance of the forming process, the tubes were subjected to axial loads in order to determine the force it takes to pull the tube out of the fitting. Finite element analysis was performed to simulate this removal process as well. The finite element analysis of the electromagnetic forming process was a key factor in shortening the process design cycle by drastically reducing the number of trial and errors and preventing premature electromagnetic coil failures.
On the Role of Interstand Tension in the Chatter of Rolling Mills
Authors: Cherukuri H. P. , Johnson R. E. 
Published: July 2023

Abstract
Asymptotic methods are used to study the role of interstand tension in the chatter of rolling mills. A two-stand mill is considered and the effect of interstand tension on the vibrations of the second stand is considered. The interstand tension is also the exit tension in the sheet at the exit point of the first stand and therefore, is determined by the rolling parameters of the first stand. The steady part of the interstand tension is shown to cause the effective spring coefficient of the second stand to be very small under some operating conditions. The dynamic part is shown to act as a forcing function to the vibrations of the second mill. The conditions under which interstand tension leads to self-excited vibrations and resonance in the second stand are extracted from the model.
Simulation and Optimization of Assembly Processes Involving Flexible Parts
Authors: Hsieh Ching C. , Oh Kong Ping 
Published: July 2023

Abstract
A method is described for the simulation and optimization of assembly processes involving flexible parts. The method, which can be applied to a wide range of assembly problems, combines traditional elastostatic structural analysis with techniques used to evaluate statistics of system with stochastic parameters. Results from an illustrative sample problem demonstrate the potential of this method in controlling the dimensional variation of the finished product.
Manipulating Machining Temperature for Chip Breaking Improvement
Authors: Hong Shane Y. , Ding Y. 
Published: July 2023

Abstract
Low carbon steel AISI 1008 is known to be difficult for chip breaking in conventional machining. This paper presents an environmentally safe cryogenic machining approach to improve the material properties for easy chip breaking. The ductile-brittle transition temperature for AISI 1008 was experimentally determined to be between −50°C and −120°C. To achieve this temperature in chips, liquid nitrogen was selectively injected to the chip forming area in the cutting process. Finite element analysis was used to predict the temperature distribution under various cutting conditions. Accordingly, the liquid nitrogen spray pattern was fine-tuned so the chip would reach the ductile-brittle transition temperature at chip breaking area. This approach minimizes the consumption of liquid nitrogen, making the process economical and practical. It also avoids the negative effect of increasing the cutting force due to hardness and shear strength increase of the workpiece material at cryogenic temperatures. Cutting tests performed on a CNC turning center showed significant improvement of chip breakability for a given range of feeds and speeds.
Dimensional Measurement Data Analysis: Part I — A Zone Fitting Algorithm
Authors: Choi Woncheol , Kurfess Thomas R. 
Published: July 2023

Abstract
Measured data taken from Coordinate Measuring Machines are Cartesian coordinates of points from the surface of a geometric solid. These points need to be placed in the same coordinate reference frame as the design model to yield deviations from target (design) geometry. Currently, data fitting techniques such as least squares fit or min-max fit are employed to the localize the measured points with respect to the design model. Tolerance verification is accomplished by determining whether the deviations of the measured points are within tolerance limits. If the tolerance is represented by tolerance zones, such data fitting techniques may not fulfill the desired verification objective.
This paper describes a zone fitting algorithm that determines whether a set of points fits into a given tolerance zone. If the point set fits into the zone, it returns a rigid body transformation that places the points inside the zone. If the criterion of a pass/fail decision is to verify whether the measured points fit into the tolerance zone, an approach employing the proposed zone fit yields a more accurate verification result than least squares or min-max approaches as shown in a number of examples in this paper. A subsequent paper (part II) addresses the determination of a minimum zone that extends inspection from a pass fail mode to a quality analysis operation.
Propagating Topological Tolerances for Rapid Prototyping
Authors: Peters T. J. , Demurjian S. A. , Needham D. M. , Peters R. J. , Dorney S. M. 
Published: July 2023

Abstract
Rapid prototyping technologies permit timely inclusion of experimental verification within an iterative design process. This work introduces topological tolerances as a tool for retaining desired design invariance during the production of successively refined prototypes. These topological tolerances are applied to the supporting geometric data representations for rapid prototyping.
At each successive local modification of the geometric data, these topological tolerances must be dynamically updated. These updates are modeled by object-oriented propagations, leading to investigation of efficient algorithms to re-compute these local topological tolerances. Relevant industrial examples will be discussed.
Software to compute topological tolerances has been fully implemented and tested, and one purpose of this paper is to report that development. Another emphasis of this paper is to report upon software prototyping of performance enhancements to adapt this code to support iterative re-design within a rapid prototyping environment. The final emphasis is to report upon our use of object-oriented propagations within our software engineering environment ADAM to model appropriate change notification upon a decision to alter the supporting geometry data structures for rapid prototyping.
Knowledge Intensive Maintenance and Soft Machines: New Approaches Toward Advanced Maintenance
Authors: Tomiyama Tetsuo , Umeda Yasushi , Sakao Tomohiko , Shimomura Yoshiki 
Published: July 2023

Abstract
Maintenance is one of the least automated areas in a product life cycle. This paper proposes the concepts of knowledge intensive maintenance and soft machines to address this issue.
Knowledge intensive maintenance is an applied concept of knowledge intensive engineering, which aims at generating more added-value with intensively accumulated life cycle knowledge, to maintenance. It even includes upgrading, reconfiguring, and renewing activities into maintenance. Soft machines aim at yielding more added-value such as longer life, easy maintainability, and robustness against faults through reconfiguration, self-maintenance, and self-organization, based on design concepts including modularity, intelligence, and autonomy. These features are crucial for environment-conscious manufacturing to avoid too early retirement and replacement and to reduce production volume.
The paper reports a computational framework for knowledge intensive engineering called a knowledge intensive engineering framework. It also describes examples of soft machines including two types of self-maintenance machines and a cellular machine.
The Development of Machine Fault Detection Using Artificial Neural Network and Fuzzy Logic Technologies
Authors: Chow Mo-yuen , Lee Yuan-Shin 
Published: July 2023

Abstract
Machine fault detection has been attracting significant attention from industry. The early detection of faults in rotating machines can significantly enhance the safety, reliability, and economic issues of industrial operations. With the emerging technology of artificial neural networks and fuzzy logic, the machine fault detection problem can be solved using an innovative approach based on easy accessible measurements, without the need for expensive equipment or accurate mathematical models that are required from conventional fault detection techniques. This paper will describe the advantages and the challenge of using the technology of artificial neural networks to solve machine fault detection problems, and also highlights parts of the research results obtained by the authors. A case study of motor fault detection is presented in this paper.
New High-Order Neural Network and its Application in Multiple Faults Simultaneous Diagnosis for Rotating Machine
Authors: Binglin Zhong , Yongyong He , Minping Jia 
Published: July 2023

Abstract
To overcome limitations of the standard feedforward neural networks, a novel high-order neural networks (i.e. ellipsoidal unit networks), which is very available for pattern classification applications due to its bounded generalization and extrapolation, has been proposed recently. In this paper, the theory and structure of such networks are described. A method for initializing hyperellipsoids and the training algorithm based on the standard backpropagation algorithm are proposed. Then, a Hierarchical Diagnosis Artificial Neural Networks (HDANN) based on the ellipsoidal unit networks is put forward with respect to multiple faults simultaneous diagnosis for rotating machines, which consists of several subnetworks and aims at dividing a large pattern space into several smaller subspaces. The subnetworks can be trained in subspaces respectively and the whole network is capable of multiple faults simultaneous diagnosis. Finally, typical fault samples of rotating machines are tested in the network. The research results show that HDANN can obtain more accurate and efficient diagnosis results and is available for real-time condition monitoring and on-line diagnosis of rotating machines.
Diagnosis of Multiple Fixture Faults in Panel Assembly
Authors: Shi Jianjun , Apley Daniel W. 
Published: July 2023

Abstract
This paper presents a modeling procedure and diagnostic algorithm for fixture related faults in panel assembly. From geometric information about the panel and fixture, a fixture fault model can be constructed off-line. Combining the fault model with in-line panel dimensional measurements, the algorithm is capable of detecting and classifying multiple fixture faults. The algorithm, which relies heavily on the fault model, is based on least squares estimation. Consequently, the test is of relatively simple form and is easily implemented and analyzed. A theoretical analysis demonstrates the performance of the test, in terms of probability of detecting faults and probability of false alarms.
A Method for Rapid Characterization of the Volumetric Error of Multi-Axis Machines
Authors: Mou J. 
Published: July 2023

Abstract
In this paper, an innovative approach is proposed to integrate both neural networks and kinematics based models for machine error characterization. First, a method was presented for rapid characterizing the accuracy of multi-axis machines. Detailed derivation of a generalized error model was given. Second, a neural networks model is then implemented to map the nonlinear relationship among the positioning error, tool position, and temperature profile of the machine structure. The output of the neural networks model is the predicted coefficients for a kinematics based error model. The kinematics based model with the predicted coefficients is then used to compute the time-variant positioning error that relates to structural, kinematic, and thermally induced errors at any point within the workspace. In determining the error model coefficients, there is no measured data is available for direct comparison with the neural networks output. Instead, the difference between the predicted errors from kinematics based model and the measured errors is used to train the neural networks. Therefore, a new training algorithm is derived for this integrated error modeling system by adopting the gradient-decent method.
Gear Pitting and Chipping Assessment via Model-Based Algorithms: A Case Study
Authors: Li C. J. , Limmer J. , Yoo J. 
Published: July 2023

Abstract
Several different vibration-based gear diagnostic algorithms are compared for their ability to assess tooth surface pitting and chipped teeth. Existing algorithms include spectrum analysis, various Figures of Merit, energy operator analysis, narrow band demodulation, wide band demodulation and the Choi-Williams time-frequency distribution. These methods are compared with recently developed modeling/prediction error analysis methods.
Pitting assessment is tested using vibration measurements taken from a 350hp, 4-square gear testing setup at different times during a long term gear test in which frosting (i.e., micro-pitting) develops as documented by digital images of the pinion tooth surface. Examining the images of all the teeth, we found that frosting develops evenly throughout the pinion and the extent of frosting grows with time. Chipped tooth detection is evaluated using data from a setup where defects of different sizes were artificially seeded. It is found that model prediction error analysis and other existing methods work reasonably well on the chipped tooth gear. Prediction error analysis is the most accurate indicator of pitting, while wide band demodulation, FM4 and NA4 show some promise that requires further testing.
Detection and Isolation of Faults in the Stamping Process
Authors: Koh Christopher K. H. , Shi Jianjun , Williams William J. , Ni Jun 
Published: July 2023

Abstract
The sheet metal drawing operation is a complex manufacturing process involving more than forty process variables. A fault is said to occur when any of these process variables deviate beyond their specified limits. Current detection schemes based on this principle have exceptionally high false alarms rates. They are also unable to detect frequency or phase shifted fault signals whose amplitudes remain within specifications; nor do they provide information about the multiplicity1 or location2 of the faults. A method of overcoming these limitations is proposed in this paper. It is based on the orthogonal Haar transform which is used to generate a set of detection signals for the different fault conditions.
A Collaborative Process and Data Management Framework for Concurrent Product and Process Development
Authors: Chen Yuh-Min , Ho Cheng-Ter , Hsiao Yun-Tau 
Published: July 2023

Abstract
This paper presents a collaborative process and data management framework which is capable of supporting information sharing in concurrent product and process development by providing functions for process control and data management. Establishing this framework involves: (i) identification of functional requirements for computer-aided concurrent product and process development, with an emphasis on net shape processes, (ii) use of system engineering and object-oriented modeling techniques for development of the proposed framework.
A Research Agenda for Capacity Driven Systems Design
Authors: Meinert Timothy S. , Taylor G. Don 
Published: July 2023

Abstract
In many manufacturing settings, the design of products, processes, material handling and logistics systems, and plant layouts are not fully integrated and are evaluated using varied performance metrics. The research agenda presented herein seeks to develop a general set of tools and design guidelines to aid in the integration of these design functions and seeks to measure the effectiveness of these tools using a common set of performance criteria. The most unique aspect of the research is a holistic integration focus which includes explicit consideration of capacity issues as well as capability concerns. The effectiveness of system design guidelines will be evaluated using generalized settings as well as case studies with actual manufacturing systems and data. A research agenda to support capacity driven system design is put forth in this paper to demonstrate the depth and breadth of current research considerations.