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Displaying 51 - 75 of 171

HIERARCHICAL DECOMPOSITION OF A MANUFACTURING WORK CELL TO PROMOTE MONITORING, DIAGNOSTICS, AND PROGNOSTICS

June 7, 2017

Author(s)

Brian A. Weiss, Guixiu Qiao

Manufacturing operations are typically complex, especially when considering industrial robot systems. The execution of robot-driven tasks requires the integration of multiple layers of hardware and software. The development and integration of monitoring

Identification of machine tool geometric performance using on-machine inertial measurements

June 6, 2017

Author(s)

Gregory W. Vogl, Radu Pavel, Andreas Archenti, Thomas J. Winnard, Matlock M. Mennu, Brian A. Weiss, Alkan Donmez

Machine tools degrade during operations, yet accurately detecting degradation of machine components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of

Quick Positional Health Assessment for Industrial Robot Prognostics and Health Management (PHM)

June 2, 2017

Author(s)

Guixiu Qiao, Craig I. Schlenoff, Brian A. Weiss

Robot calibration and performance will degrade if proper maintenance isn't performed. There have been challenges for manufacturers to optimize the maintenance strategy and minimize unexpected shutdowns. Prognostics and health management (PHM) can be

Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems

February 10, 2017

Author(s)

Benjamin Y. Choo, Brian Weiss, Jeremy Marvel, Stephen C. Adams, Peter A. Beling

Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. As a rule, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM

Editorial - Special Issue: Smart Manufacturing PHM

December 7, 2016

Author(s)

Brian A. Weiss, Philip Freeman, Jay Lee, Radu Pavel

This Special Issue on Smart Manufacturing PHM contains six outstanding technical papers and one communication that collectively present a diverse range of research and practical application topics within the field of Smart Manufacturing PHM.

Use Case Development to Advance Monitoring, Diagnostics, and Prognostics in Manufacturing Operations

December 6, 2016

Author(s)

Brian A. Weiss, Moneer Helu, Gregory W. Vogl, Guixiu Qiao

Manufacturing operations suffer from degradation as equipment and processes are continually used to generate products. The development and integration of monitoring, diagnostic, and prognostic (collectively known as PHM) technologies can enhance

Inertial Measurement Unit for On-Machine Diagnostics of Machine Tool Linear Axes

October 7, 2016

Author(s)

Gregory W. Vogl, Alkan Donmez, Andreas Archenti, Brian A. Weiss

Machine tools degrade during operations, yet knowledge of degradation is elusive; accurately detecting degradation of machines' components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated, efficient

Present Status and Future Growth of Advanced Maintenance Technology and Strategy in US Manufacturing

September 30, 2016

Author(s)

Xiaoning Jin, Brian Weiss, David Siegel, Jay Lee, Jun Ni

The goals of this paper are to 1) examine the current practices of diagnostics, prognostics, and maintenance employed by United States (U.S.) manufacturers to achieve productivity and quality targets and 2) to understand the present level of maintenance

Advancing Measurement Science to Assess Monitoring, Diagnostics,and Prognostics for Manufacturing Robotics

September 29, 2016

Author(s)

Guixiu Qiao, Brian Weiss

From the moment a robot system is put into service to enable a manufacturing process, the overall process, its constituent sub-systems, and components begin to degrade. Without maintenance, this degradation will lead to faults and/or failures impacting the

Measurement Science Roadmap for Prognostics and Health Management for Smart Manufacturing Systems

September 27, 2016

Author(s)

Joan Pellegrino, Mauricio Justiniano, Anand Raghunathan, Brian Weiss

The National Institute of Standards and Technology (NIST) hosted the Roadmapping Workshop: Measurement Science for Prognostics and Health Management of Smart Manufacturing Systems (PHM4SMS) at its Gaithersburg, MD campus to bring together over 60 PHM

The Current State of Sensing, Health Management, and Control for Small-to-Medium-Sized Manufacturers

June 26, 2016

Author(s)

Moneer Helu, Brian A. Weiss

The development of digital technologies for manufacturing has been challenged by the difficulty of navigating the breadth of new technologies available to industry. This difficulty is compounded by technologies developed without a good understanding of the

The Present Status and Future Growth of Maintenance in U.S. Manufacturing: Results from a Pilot Survey

June 20, 2016

Author(s)

Xiaoning Jin, David Siegel, Brian Weiss, Ellen Gamel, Wei Wang, Ni Jun

A research study was conducted 1) to examine the practices employed by U.S. manufacturers to achieve productivity goals and 2) to understand what level of intelligent maintenance technologies and strategies are being incorporated into these practices. This

A review of diagnostic and prognostic capabilities and best practices for manufacturing

June 9, 2016

Author(s)

Gregory W. Vogl, Brian A. Weiss, Moneer M. Helu

Prognostics and health management (PHM) technologies reduce time and costs for maintenance of products or processes through efficient and cost-effective diagnostic and prognostic activities. PHM systems use real-time and historical state information of