Literature DB >> 30820072

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

Gregory W Vogl1, Brian A Weiss1, Moneer Helu1.   

Abstract

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 subsystems and components to provide actionable information, enabling intelligent decision-making for improved performance, safety, reliability, and maintainability. However, PHM is still an emerging field, and much of the published work has been either too exploratory or too limited in scope. Future smart manufacturing systems will require PHM capabilities that overcome current challenges, while meeting future needs based on best practices, for implementation of diagnostics and prognostics. This paper reviews the challenges, needs, methods, and best practices for PHM within manufacturing systems. This includes PHM system development of numerous areas highlighted by diagnostics, prognostics, dependability analysis, data management, and business. Based on current capabilities, PHM systems are shown to benefit from open-system architectures, cost-benefit analyses, method verification and validation, and standards.

Entities:  

Keywords:  Diagnostics; Health management; Maintenance; Manufacturing; Prognostics

Year:  2016        PMID: 30820072      PMCID: PMC6391061          DOI: 10.1007/s10845-016-1228-8

Source DB:  PubMed          Journal:  J Intell Manuf        ISSN: 0956-5515            Impact factor:   6.485


  6 in total

1.  Observations on Developing Reliability Information Utilization in a Manufacturing Environment with Case Study: Robotic Arm Manipulators.

Authors:  Michael Sharp
Journal:  Int J Adv Manuf Technol       Date:  2019       Impact factor: 3.226

2.  Foundations of information governance for smart manufacturing.

Authors:  K C Morris; Yan Lu; Simon Frechette
Journal:  Smart Sustain Manuf Syst       Date:  2020

3.  Assessment of a Novel Position Verification Sensor to Identify and Isolate Robot Workcell Health Degradation.

Authors:  Brian A Weiss; Jared Kaplan
Journal:  J Manuf Sci Eng       Date:  2021-04       Impact factor: 3.033

4.  Risk-Oriented Product Assembly System Health Modeling and Predictive Maintenance Strategy.

Authors:  Fengdi Liu; Yihai He; Yixiao Zhao; Anqi Zhang; Di Zhou
Journal:  Sensors (Basel)       Date:  2019-05-05       Impact factor: 3.576

5.  Smart Prognostics and Health Management (SPHM) in Smart Manufacturing: An Interoperable Framework.

Authors:  Sarvesh Sundaram; Abe Zeid
Journal:  Sensors (Basel)       Date:  2021-09-07       Impact factor: 3.576

6.  Sensitivity Analysis of Sensors in a Hydraulic Condition Monitoring System Using CNN Models.

Authors:  Caroline König; Ahmed Mohamed Helmi
Journal:  Sensors (Basel)       Date:  2020-06-10       Impact factor: 3.576

  6 in total

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