Automation and robotics for the National Space Program

The emphasis on automation and robotics in the augmentation of the human centered systems as it concerns the space station is discussed. How automation and robotics can amplify the capabilities of humans is detailed. A detailed developmental program for the space station is outlined

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project

In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site

Simulation-based Planning of Machine Vision Inspection Systems with an Application to Laser Triangulation

Nowadays, vision systems play a central role in industrial inspection. The experts typically choose the configuration of measurements in such systems empirically. For complex inspections, however, automatic inspection planning is essential. This book proposes a simulation-based approach towards inspection planning by contributing to all components of this problem: simulation, evaluation, and optimization. As an application, inspection of a complex cylinder head by laser triangulation is studied

Mixed Reality Toolset For Onsite Processes In Construction and Manufacturing Industries

In traditional and labour-intensive industries, such as construction and manufacturing, every time a task must be repeated, it not only affects the schedule but also increases costs. Site visits to collect information, during the early stages of the project, are very crucial as this information is used to create plans and budgets. Furthermore, a large percentage of the existing factories and buildings are not digitally documented. Many buildings may also have outdated 2D designs. Therefore, a key problem during site planning is the collection of accurate data. Evidently, there is a lack of modern technological tools that ensure that the reality is consistent with the virtual planning data. Augmented Reality (AR) technology can digitalise the process of site information collection and related tasks such as visualisation of 3D designs. Various other capabilities of AR, with smart glasses such as Microsoft HoloLens, include scanning, measurement, interactions of virtual objects with the real world and location aware textual notes. This thesis explores the capabilities of AR with smart glasses such as HoloLens, by first understanding the needs of the industries along with identifying ways in which AR can digitalise industry processes and developing necessary tools to enable the same. The Unity3D engine is used to carry out the development work and the resultant tools are implemented on HoloLens. These functionalities are developed keeping in mind principles of user experience. They allow the user to capture the space around them as a 3D mesh, measure distances between objects in that space or with virtual objects that have been placed, interact with various models by moving them or even slicing them to meet the user’s requirements and creating annotations in different parts of the working space. The developed tools were then tested in the industry case study with Fortum. Here it was verified that the newly developed tools met most of the requirements. However, each company may have their own set of requirements and may need more customised AR solutions to fix them. This observation resulted in the development of an AR toolset that provides different functionalities to the user. This enabled the leveraging of user knowledge of the situation and maximising the strength of AR technology while solving the problem

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

Volumetric Data Analysis for Reverse Engineering and Solid Additive Manufacturing: A Framework for Geometric Metrological Analysis

Poor geometric quality is one of the main constraints that hinders the wide adoption of reverse engineering (RE) and additive manufacturing (AM). RE models from a single scan will most likely generate inaccurate representations of the original design due to the uncertainties existing in individual parts and scanning procedures. On the other hand, metrological methodologies for AM significantly differ from those for the traditional manufacturing processes. Conventional statistical methodologies overlook these three-dimensional (3D) feature-independent processing techniques. In this dissertation, we develop a novel statistical data analysis framework---volumetric data analysis (VDA)---to deal with the uniqueness of both technologies. In general, this framework also addresses the rising analytical needs of 3D geometric data. Through VDA, we can simultaneously analyze the measured points on the outer surfaces and their relationships to acquire manufacturing knowledge. The main goal of this dissertation is to apply the proposed framework in multiple RE and AM applications related to their geometric quality characteristics. First, we demonstrate a novel estimator to increase the precision of RE-generated models. We built a Bayesian model with prior domain knowledge to model the landmarks’ uncertainty. We also proposed a bi-objective optimization model to answer the RE process-planning questions, e.g., how many scans and parts are required to achieve the precision requirements. The second major contribution is a study of tolerance estimation procedure for the re-manufacturing of legacy parts. We propose a systematic geometric inspection methodology for the RE and AM systems. Moreover, based on the domain knowledge in production-process design and planning, we developed methods to estimate empirical tolerances from a small batch of legacy parts. The third major contribution of this dissertation is to design an automated variance modeling algorithm for 3D scanners. The algorithm utilizes a physical object’s local geometric descriptors and Bayesian extreme learning machines to predict the landmarks’ variances. Lastly, we introduce the VDA framework to AM-oriented experimental analysis. Specifically, we propose a high-dimensional hypothesis testing procedure to statistically compare the geometric production accuracy under two AM process settings. We present new visualization tools for deviation diagnostics to aid in interpreting and comparing the process outputs

Reusable modelling and simulation of flexible manufacturing for next generation semiconductor manufacturing facilities

Automated material handling systems (AMHS) in 300 mm semiconductor manufacturing facilities may need to evolve faster than expected considering the high performance demands on these facilities. Reusable simulation models are needed to cope with the demands of this dynamic environment and to deliver answers to the industry much faster. One vision for intrabay AMHS is to link a small group of intrabay AMHS systems, within a full manufacturing facility, together using what is called a Merge/Diverge link. This promises better operational performance of the AMHS when compared to operating two dedicated AMHS systems, one for interbay transport and the other for intrabay handling. A generic tool for modelling and simulation of an intrabay AMHS (GTIA-M&S) is built, which utilises a library of different blocks representing the different components of any intrabay material handling system. GTIA-M&S provides a means for rapid building and analysis of an intrabay AMHS under different operating conditions. The ease of use of the tool means that inexpert users have the ability to generate good models. Models developed by the tool can be executed with the merge/diverge capability enabled or disabled to provide comparable solutions to production demands and to compare these two different configurations of intrabay AMHS using a single simulation model. Finally, results from simulation experiments on a model developed using the tool were very informative in that they include useful decision making data, which can now be used to further enhance and update the design and operational characteristics of the intrabay AMHS

Component-based control system development for agile manufacturing machine systems

It is now a common sense that manufactures including machine suppliers and system integrators of the 21 st century will need to compete on global marketplaces, which are frequently shifting and fragmenting, with new technologies continuously emerging. Future production machines and manufacturing systems need to offer the "agility" required in providing responsiveness to product changes and the ability to reconfigure. The primary aim for this research is to advance studies in machine control system design, in the context of the European project VIR-ENG - "Integrated Design, Simulation and Distributed Control of Agile Modular Machinery"