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Max K. Ferguson, Yung-Tsun Lee, Anantha Narayanan, Kincho H. Law
Convolutional neural networks are becoming a popular tool for image processing in the engineering and manufacturing sectors. However, managing the storage and distribution of trained models is still a difficult task, partially due to the lack of
Vivian W. Wong, Max K. Ferguson, Kincho H. Law, Yung-Tsun Lee
We present an end-to-end workflow to generate annotated image datasets for object detection. With this workflow, which we call assistive learning, we are able to reduce manual annotation time on two experimental datasets by 79.4% and 83.1%. The
Sanjay Jain, Anantha Narayanan Narayanan, Yung-Tsun Lee
Multi-resolution simulation models of manufacturing system, such as the virtual factory, coupled with analytics offer exciting opportunities to manufacturers to exploit the increasing availability of data from their corresponding real factory at different
The QIF PMI Report (QPR) software generates a spreadsheet from a Quality Information Framework (QIF) file containing Product and Manufacturing Information (PMI). QIF is a unified XML framework standard for computer-aided quality QIF systems, available free
This guide was assembled to aid change agents, such as research and trade organizations, in evaluating potential research and development investments in the manufacturing industry. It includes an overview of the primary methods used for evaluating
For decades, many manufacturers have counted on robots to tirelessly produce parts of predictable quality. One of the key attributes of robots is their repeatability, which means that their tool tip will return to the same pre-programmed location with a
Arvind Shankar Raman, Dustin Harper, Karl Haapala, Barbara S. Linke, William Z. Bernstein, KC Morris
A workshop on Challenges in Representing Manufacturing Processes for Systematic Sustainability Assessments, jointly sponsored by the U.S. National Science Foundation, the U.S. National Institute of Standards and Technology, ASTM International, the American
Karl Haapala, Barbara S. Linke, KC Morris, William Z. Bernstein, Fu Zhao
A workshop on Challenges in Representing Manufacturing Processes for Systematic Sustainability Assessments, jointly sponsored by the U.S. National Science Foundation, the U.S. National Institute of Standards and Technology, ASTM International, the American
Thomas D. Hedberg Jr., Allison Barnard Feeney, Vijay Srinivasan
This paper synthesizes a theory from industrial best practices codified in recent standards. Recent editions of ASME and ISO standards codify the evolving industrial best practices in defining and modeling the information about products made from fibrous
Nestor is a software tool that annotates natural language CSV (comma-separated variable) files, with a UTF-8 encoding, using a process called tagging [1]. The outputted annotated datasets (as either a CSV or .h5 file) can be used for different analysis
This report provides an overview of the US manufacturing industry. There are three aspects of US manufacturing that are considered: (1) how the US industry compares to other countries, (2) the trends in the domestic industry, and (3) the industry trends
Today, data analytics plays an important role in Smart Manufacturing decision making. Domain knowledge is very important to support the development of analytics models. However, in today's data analytics projects, domain knowledge is only documented, but
Luis Hernandez, Mark Walker, Al Salour, Radu Pavel, Brian Weiss
The ASME Subcommittee on Monitoring, Diagnostics, and Prognostics for Advanced Manufacturing has produced this white paper to highlight the rationale and key considerations behind the initiative to develop guidelines for when and where manufacturers should
Under the authority of the Revitalize American Manufacturing and Innovation Act (RAMI) of 2014, the Secretary of Commerce established the Network for Manufacturing Innovation, generally called the Manufacturing USA network. The network, along with its
Mohammad Balapour, Weijin Zhao, Edward Garboczi, Nay Ye Oo, Sabrina Spatari, Grace Hsuan, Peter Billen, Yaghoob Farnam
This study evaluates the potential use of a novel lightweight aggregate (LWA), spherical porous reactive aggregate (SPoRA), which is produced from waste coal bottom ash, for internal curing of concrete. Engineering properties of SPoRA required for concrete
Keith A. Stouffer, Timothy Zimmerman, CheeYee Tang, Michael Pease, Jeffrey Cichonski, Neeraj Shah, Wesley Downard
This guide provides general implementation guidance (Volume 1) and example proof-of-concept solutions demonstrating how available open-source and commercial off-the-shelf (COTS) products could be implemented in manufacturing environments to satisfy the
Keith A. Stouffer, Timothy Zimmerman, CheeYee Tang, Michael Pease, Jeffrey Cichonski, Neeraj Shah, Wesley Downard
This guide provides example proof-of-concept solutions demonstrating how available open-source and commercial off-the-shelf (COTS) products could be implemented in process-based manufacturing environments to satisfy the requirements in the Cybersecurity
Keith A. Stouffer, Timothy Zimmerman, CheeYee Tang, Michael Pease, Jeffrey Cichonski, Neeraj Shah, Wesley Downard
This guide provides example proof-of-concept solutions demonstrating how available open-source and commercial off-the-shelf (COTS) products could be implemented in discrete-based manufacturing environments to satisfy the requirements in the Cybersecurity
Emily Hastings, Thurston Sexton, Michael Brundage, Melinda Hodkiewicz
Maintenance work orders (MWOs) are an integral part of the maintenance workflow. These documents allow technicians to capture vital aspects of a maintenance job: observed symptoms, potential causes, solutions implemented, etc. These MWOs have often been
Fnu Madhusudanan Navinchandran, Michael E. Sharp, Michael P. Brundage, Thurston B. Sexton
Maintenance Work Orders (MWOs) are a useful way of recording semi-structured information regarding maintenance activities in a factory or other industrial setting. Analysis of these MWOs could provide valuable insights regarding the many facets of
Thurston B. Sexton, Melinda Hodkiewicz, Michael P. Brundage
In manufacturing, there is a significant push toward the digitization of processes and decision making, by increasing the level of automation and networking via cyber-physical systems, and machine learning methods that can parse useful patterns from these
Laetitia Monnier, William Z. Bernstein, sebti foufou
The visions of the digital thread and smart manufacturing have boasted the potential of relating downstream data to upstream decisions in design. However, to date, the tools and methods to robustly map across the related data representations is
Smart manufacturing promises to provide significant increases in productivity and effectiveness of manufacturing systems by better connecting the data from people, processes, and things. However, there is no uniform, generalized method for deploying linked
Robert G. Rudnitsky, Michael F. Molnar, Frank W. Gayle, Hong Liang, Lisa J. Fronczek, Said Jahanmir, Zahraha S. Brunner
This annual report documents the progress of the Manufacturing USA program in meeting its goals and describes the major accomplishments of the Manufacturing USA institutes in fiscal year 2018.
Researches have shown that design changes cost more in later stages of product development. Therefore, companies adopt Design-for-X methods to optimize product designs from many aspects in the early design stage. Despite such efforts, they often encounter