Microvia Formation for Multi-Layer PWB by Laser Direct Drilling: Improvement of Hole Quality by Silica Fillers in Build-Up Layer

Microvia formation technology using lasers has become the dominant method for drilling microvia called blind via-holes (BVHs) in printed wiring boards (PWBs). Laser direct drilling (LDD), drilling directly outer copper foil by laser, has attracted attention as a novel method. In particular, when copper and resin with different processing thresholds are drilled at the same time, an overhang defect occurs on the drilled hole. However, the overhang generation mechanism has not been clarified. Therefore, we investigated it by detailed observation of the drilled-hole section. Moreover, the overhang length was estimated using the finite element method (FEM). Influences of surface treatment of outer copper foil and thermal properties of the build-up layer were evaluated experimentally and analytically. Consequently, an experiment with a prototype PWB with silica filler added in the build-up layer was carried out. Using the prototype PWBs, the overhang was reduced as shown in FEM analysis results.

A Bio-Inspired Framework for a Self-Healing Assembly System

Statistical process monitoring and control has been popularized throughout the manufacturing industry as well as various other industries interested in improving product quality and reducing costs. Advances in this field have focused primarily on more efficient ways for diagnosing faults, reducing variation, developing robust design techniques, and increasing sensor capabilities. System level advances are largely dependent on the introduction of new techniques in the listed areas. A unique system level quality control approach is introduced in this paper as a means to integrate rapidly advancing computing technology and analysis methods in manufacturing systems. Inspired by biological systems, the developed framework utilizes immunological principles as a means of developing self-healing algorithms and techniques for manufacturing assembly systems. The principles and techniques attained through this bio-mimicking approach will be used for autonomous monitoring, detection, diagnosis, prognosis, and control of station and system level faults, contrary to traditional systems that largely rely on final product measurements and expert analysis to eliminate process faults.

Energy Consumption Reduction for Sustainable Manufacturing Systems Considering Machines With Multiple-Power States

Due to rapid consumption of world’s fossil fuel resources and impracticality of large-scale application and production of renewable energy, the significance of energy efficiency improvement of current available energy modes has been widely realized by both industry and academia. A great deal of research has been implemented to identify, model, estimate, and optimize energy efficiency of single-machine manufacturing system [1–5], but very little work has been done towards achieving the optimal energy efficiency for a typical manufacturing system with multiple machines. In this paper, we analyze the opportunity of energy saving on the system level and propose a new approach to improve energy efficiency for sustainable production systems considering the fact that more and more modern machines have multiple power states. Numerical case based on simulation model of an automotive assembly line is used to illustrate the effectiveness of the proposed approach.

Standardization of CMM Fitting Algorithms and Development of Inspection Maps for Use in Statistical Process Control

The choice of fitting algorithm in CMM metrology has often been based on mathematical convenience rather than the fundamental GD&T principles dictated by the ASME Y14.5 standard. Algorithms based on the least squares technique are mostly used for GD&T inspection and this wrong choice of fitting algorithm results in errors that are often overlooked and leads to deficiency in the inspection process. The efforts by organizations such as NIST and NPL and many other researchers to evaluate commercial CMM software were concerned with the mathematical correctness of the algorithms and developing efficient and intelligent methods to overcome the inherent difficulties associated with the mathematics of these algorithms. None of these works evaluate the ramifications of the choice of a particular fitting algorithm for a particular tolerance type. To illustrate the errors that can arise out of a wrong choice of fitting algorithm, a case study was done on a simple prismatic part with intentional variations and the algorithms that were employed in the software were reverse engineered. Based on the results of the experiments, a standardization of fitting algorithms is proposed in light of the definition provided in the standard and an interpretation of manual inspection methods. The standardized fitting algorithms developed for substitute feature fitting are then used to develop Inspection maps (i-Maps) for size, orientation and form tolerances that apply to planar feature types. A methodology for Statistical Process Control (SPC) using these i-Maps is developed by fitting the i-Maps for a batch of parts into the parent Tolerance Maps (T-Maps). Different methods of computing the i-Maps for a batch are explored such as the mean, standard deviations, computing the convex hull and doing a principal component analysis of the distribution of the individual parts. The control limits for the process and the SPC and process capability metrics are computed from inspection samples and the resulting i-Maps. Thus, a framework for statistical control of the manufacturing process is developed.

Molecular Dynamics Simulation of AFM-Based Nanomachining Processes

Recently, atomic force microscopy (AFM) has been widely used for nanomachining and fabrication of micro/ nanodevices. This paper describes the development and validation of computational models for AFM-based nanomachining (nanoindentation and nanoscratching). The Molecular Dynamics (MD) technique is used to model and simulate mechanical indentation and scratching at the nanoscale in the case of gold and silicon. The simulation allows for the prediction of indentation forces and the friction force at the interface between an indenter and a substrate. The effects of tip curvature and speed on indentation force and friction coefficient are investigated. The material deformation and indentation geometry are extracted based on the final locations of atoms, which are displaced by the rigid tool. In addition to modeling, an AFM was used to conduct actual indentation at the nanoscale, and provide measurements to validate the predictions from the MD simulation. The AFM provides resolution on nanometer (lateral) and angstrom (vertical) scales. A three-sided pyramid indenter (with a radius of curvature ∼ 50 nm) is raster scanned on top of the surface and in contact with it. It can be observed from the MD simulation results that the indentation force increases as the depth of indentation increases, but decreases as the scratching speed increases. On the other hand, the friction coefficient is found to be independent of scratching speed.

Capillary Force Induced Elastic Deformation on ZnS Nanobeams

In this study, synthesized Wurtzite-structured ZnS nanobelts was investigated using high resolution transmission electron microscope, atomic force microscope, and scanning electron microscope for structural and morphology analyses. Results show that ZnS nanobelts are tens of microns in length, mostly ∼40×50 nm2 in width and thickness. The nanobelts grow along direction [001] and are dislocation free. The distance spacing for (001) plane is 3.19A˚. The capillary force was found strong enough to deform the ZnS nanobeam down to the substrate. Theoretical analysis on small strain elastic deformation was conducted. It was found that as the maximum beam deflection increases, beam elastic energy increases; in the meantime, the surface energy decreases. The net increase in elastic beam energy is less than the net decrease in the surface energy, resulting in total energy decrease. In addition, as the volume of liquid increases, for a certain maximum beam deflection, the total energy increases, this is result of the increase of the surface energy. Furthermore, for a specific nanobeam to be deflected to the underlying surface, the amount of liquid can be calculated.

Comparative Analysis of the Process Mechanics in Micro-Electrical Discharge Machining (EDM) and Reverse Micro-EDM

The objective of this paper is to study the time-evolution of the process mechanics for micro-electrical discharge machining (MEDM) and reverse-micro-electrical discharge machining (R-MEDM), as a function of key system parameters, viz., voltage, capacitance, and threshold of the spark circuit. Full factorial experiments have been performed to quantify the aforementioned system parameters on the MEDM and R-MEDM processes. The process monitoring voltage and current signals, material erosion rate and the surface roughness values are the machining responses of interest. The voltage and current (V-I) signals reveal information about the material erosion rate and the extent of debris-interference associated with the corresponding process. Analysis of the V-I signals shows that R-MEDM is more stable than MEDM and can therefore be operated at aggressive conditions of capacitance and voltage. R-MEDM also results in higher material erosion rates but the resulting surface has a higher surface roughness value than that generated by MEDM. A debris deposition mechanism is proposed for R-MEDM that suggests debris entrapment and subsequent welding to the machined feature to be the reason for the increased surface roughness.

Consideration of Manufacturing Processes and the Supply Chain in Product Design

As efforts continue to incorporate environmental sustainability into product design, struggles persist to concurrently consider the environmental impacts resulting from transportation planning and supply chain network design. In fact, the transportation sector is the second largest contributor to direct greenhouse gas (GHG) emissions in the United States, following electricity generation. To address these concerns and consider environmental issues more holistically during the development of products, Design for X (X: manufacturing, environment, etc.) methods, such as environmentally benign manufacturing (EBM) and life cycle assessment (LCA) continue to be advanced through research. In spite of improving environmental performance through design, supply chain related impacts are not well understood and can be impacted by decisions made during product design. Thus, the aim of this research is to explore how changes to the design of a product affect manufacturing supply chain configurations and, in turn, influence product environmental sustainability. The environmental impacts for producing several three-ring binder design variations are predicted by assuming a given set of suppliers that provide materials and components to the manufacturer. Supply chain transportation impacts are also accounted for in the analysis. Transportation impacts are found to be minor compared to materials and manufacturing impacts.

Study of Microphone Array for Noise Reduction in Sound Based Micro-Tool Wear Monitoring

An experienced technician can usually identify the cutting condition by hearing the sound generated during the cutting and the sound signal can be expected to detect the features closely related to the tool condition. However, the background noise always contaminates the signal obtained by microphone system during cutting and reduces the chance of applying the sound based micro tool condition monitoring system in industry. In order to reduce the noise effect and improve the system performance, a microphone array integrated with Wiener filter was designed and implemented in this study to enhance the noise reduction capability for monitoring system. The experimental results show that the microphone array integrated with Wiener filter provides a better solution than single microphone integrated with Wiener filter or the microphone array without the post filter design in reducing the broadband background noise.

Flow Stress Experimental Determination for Warm-Forming Process

Warm forming is a manufacturing process in which a workpiece is formed into a desired shape at a temperature range between room temperature and material recrystallization temperature. Flow stress is expressed as a function of the strain, strain rate, and temperature. Based on such information, engineers can predict deformation behavior of material in the process. The majority of existing studies on flow stress mainly focus on the deformation and microstructure of alloys at temperature higher than their recrystallization temperatures or at room temperature. Not much works have been presented on flow stress at warm-forming temperatures. This study aimed to determine the flow stress of stainless steel AISI 316L and titanium TA2 using specially modified equipment. Comparing with the conventional method, the equipment developed for uniaxial compression tests has be verified to be an economical and feasible solution to accurately obtain flow stress data at warm-forming temperatures. With average strain rates of 0.01, 0.1, and 1 /s, the stainless steel was tested at degree 600, 650, 700, 750, and 800 °C and the titanium was tested at 500, 550, 600, 650, and 700 °C. Both materials softened at increasing temperatures. The overall flow stress of stainless steel was approximately 40 % more sensitive to the temperature compared to that of titanium. In order to increase the efficiency of forming process, it was suggested that the stainless steel should be formed at a higher warm-forming temperature, i.e. 800 °C. These findings are a practical reference that enables the industry to evaluate various process conditions in warm-forming without going through expensive and time consuming tests.