On flexibly integrating machine vision inspection systems in PCB manufacture

The objective of this research is to advance computer vision techniques and their applications in the electronics manufacturing industry. The research has been carried out with specific reference to the design of automatic optical inspection (AOI) systems and their role in the manufacture of printed circuit boards (PCBs). To achieve this objective, application areas of AOI systems in PCB manufacture have been examined. As a result, a requirement for enhanced performance characteristics has been identified and novel approaches and image processing algorithms have been evolved which can be used within next generation of AOI systems. The approaches are based on gaining an understanding of ways in which manufacturing information can be used to support AOI operations. Through providing information support, an AOI system has access to product models and associated information which can be used to enhance the execution of visual inspection tasks. Manufacturing systems integration, or more accurately controlled access to electronic information, is the key to the approaches. Also in the thesis methods are proposed to achieve the flexible integration of AOI systems (and computer vision systems in general) within their host PCB manufacturing environment. Furthermore, potential applications of information supported AOI systems at various stages of PCB manufacturing have been studied. It is envisaged that more efficient and cost-effective applications of AOI can be attained through adopting the flexible integration methods proposed, since AOI-generated information can now be accessed and utilized by other processes

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Elastomer-based visuotactile sensor for normality of robotic manufacturing systems

Modern aircrafts require the assembly of thousands of components with high accuracy and reliability. The normality of drilled holes is a critical geometrical tolerance that is required to be achieved in order to realize an efficient assembly process. Failure to achieve the required tolerance leads to structures prone to fatigue problems and assembly errors. Elastomer-based tactile sensors have been used to support robots in acquiring useful physical interaction information with the environments. However, current tactile sensors have not yet been developed to support robotic machining in achieving the tight tolerances of aerospace structures. In this paper, a novel elastomer-based tactile sensor was developed for cobot machining. Three commercial silicon-based elastomer materials were characterised using mechanical testing in order to select a material with the best deformability. A Finite element model was developed to simulate the deformation of the tactile sensor upon interacting with surfaces with different normalities. Additive manufacturing was employed to fabricate the tactile sensor mould, which was chemically etched to improve the surface quality. The tactile sensor was obtained by directly casting and curing the optimum elastomer material onto the additively manufactured mould. A machine learning approach was used to train the simulated and experimental data obtained from the sensor. The capability of the developed vision tactile sensor was evaluated using real-world experiments with various inclination angles, and achieved a mean perpendicularity tolerance of 0.34°. The developed sensor opens a new perspective on low-cost precision cobot machining

Lab-on-a-chip and integrated strategies in tumor immunotheraphy

Background While conventional chemotherapy and radiation therapy have improved the survival of many cancer patients, there are still major disadvantages associated with these treatments such as high toxicity and drug-resistance. The possibility to manipulate the immune system to recognize and kill tumor cells is very attractive despite numerous obstacles remaining to be overcome. In particular, the ability of the immune system to destroy disseminated metastases in a specific way makes immunotherapy an attractive alternative to conventional therapies. Nevertheless, other unconventional technologies emerged in recent years seem to be very promising; in particular the analysis and monitoring of single cell-to-cell interactions and the capability to individually control single cells by Lab-on-a-chip devices have become of great interest in different areas of life sciences. These new technologies, in combination with progresses reached in anti-tumor vaccines, could be useful to improve immune T cell responses against tumor antigen for a more efficient immunotherapy. Aims This thesis focuses on two tumor immunotherapy issues: 1) design, realization and validation of innovative Lab-on-a-chip devices for immune system study, that allows single tumor cell and effector cell interaction, detection and isolation; 2) identification of molecular mechanisms that prevent EBV-associated tumors (e.g. Burkitt’s lymphoma) recognition by T cells and study of their potential correction by specific treatments. The main goal of this study remains indeed the evaluation of an integrated strategy for immunotherapy development enhancing for malignancies treatment. Methods Biocompatibility test, generation of memory CTL cultures, 51Cr release assay, IFN-Elispot, proteasomes purification, western blot assay, enzymatic assay, immunofluorescence, RT-PCR. Main Results As concerns the first part of the thesis, a main achievement was the design of Lab-on-a-chip platform that combined microfluidics and electronics together, consisting in a matrix of up to thousand microwells where living cells can be deposited. Subsequently, different materials have been evaluated to identify the most biocompatible ones for biosensor manufacturing. Once developed Lab-on-a-chip prototype, it has been tested from a functional point of view. In particular, it has been demonstrated that the biosensor is able to isolate and trap single cells inside microwells by dielectrophoresis, that recovered cells are still alive and that their biological functions and gene expression remain unaltered. Furthermore, tumor cell lysis by immune effector cells could be successfully monitored inside device microwells, showing that biosensor could be used for cell to cell interaction studies. Regarding the second aim of this thesis, it has been identified a new epitope-specific T cell response against EBV nuclear antigen 1 (EBNA1). It has also been demonstrated that CTLs specific for another EBNA1-derived epitope (referred as HPV) are detectable in the majority of HLA-B35 individuals, and recognize EBV-transformed B lymphocytes (LCL) but not Burkitt’s lymphoma (BL). Afterwards LCL and BL have been compared for their antigen processing machinery, demonstrating that one of the major differences was at the proteasome level; indeed, proteasomes from BL cells have displayed a far lower chymotryptic and tryptic-like activities. Interestingly, it has also been shown that treatment with proteasome inhibitors partially restored the capacity of BL cells to present the HPV epitope. Conclusions The results achieved in single cell manipulation and cell to cell analysis interaction by Lab-on-a-chip technology, and the findings reached to improve BL immune recognition, represent an implementation of innovative tools that could allow important progresses in cancer diagnosis and immunotherapy

NASA Tech Briefs Index, 1977, volume 2, numbers 1-4

Announcements of new technology derived from the research and development activities of NASA are presented. Abstracts, and indexes for subject, personal author, originating center, and Tech Brief number are presented for 1977

Index to NASA tech briefs, 1971

The entries are listed by category, subject, author, originating source, source number/Tech Brief number, and Tech Brief number/source number. There are 528 entries

Estimation of the PCB Production Process Using a Neural Network

Printed Circuit Boards (PCB) are an integral part of all electronic products, and the production process for printed circuit boards is quite complex. As the life cycle of electronic products becomes shorter and shorter, and the precision and signal bandwidth of electronic products become higher and higher, the manufacturing process of printed circuit boards is further complicated. Therefore, how to pre-evaluate the production difficulty before starting the production will effectively increase the efficiency and quality of printed circuit board production. Gerber file is the most commonly used data format for the printed circuit board industry. This file contains most of the parameters required for the manufacture of printed circuit boards. Therefore, this study uses a neural network to evaluate new PCB products before they are produced through the production parameters that are more influential in the PCB manufacturing process. This makes it possible to evaluate the difficulty and the required production process before the new PCB product is produced. This will be very beneficial for the PCB production schedule, quality control, and cost

Proceedings of the 1977 NASA/ISHM Microelectronics Conference

Current and future requirements for research, development, manufacturing and education in the field of hybrid microelectronic technology were discussed

SDMF based interference rejection and PD interpretation for simulated defects in HV cable diagnostics

Partial Discharge (PD) in cable systems causes deterioration and failure, identifying the presence of PD is crucial to Asset Management. This paper presents methods for interference signals rejection and for PD interpretation for five types of artificial defect in 11 kV ethylene-propylene rubber (EPR) cable. Firstly, the physical parameters of the artificial defects used for PD signal generation are introduced. Thereafter, the sample stress regime, PD testing and detection systems, including IEC 60270 measurement system and High Frequency Current Transformer (HFCT), are outlined. Following on, a novel Synchronous Detection and Multi-information Fusion (SDMF) based signal identification method is developed, to separate PD and interference signals within raw data. Finally, a comparative PD analysis of two detection systems is carried out and several characteristics of insulation related PD signals of EPR cables are reported. The SDMF based data pre-processing and the comparative PD activity analysis contribute to improvement of PD pattern recognition and assist in on-line PD monitoring systems