Search Results - "Quality engineering"

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  1. 1

    Quality 4.0-the challenging future of quality engineering by Zonnenshain, Avigdor, Kenett, Ron S.

    Published in Quality engineering (01-10-2020)
    “…Quality is a crucial dimension of products and processes. It is considered a competitive advantage for companies and organizations in the global market…”
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    Journal Article
  2. 2

    Nonparametric (distribution-free) control charts: An updated overview and some results by Chakraborti, S., Graham, M. A.

    Published in Quality engineering (02-10-2019)
    “…Control charts that are based on assumption(s) of a specific form for the underlying process distribution are referred to as parametric control charts. There…”
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    Journal Article
  3. 3

    Network based credit risk models by Giudici, Paolo, Hadji-Misheva, Branka, Spelta, Alessandro

    Published in Quality engineering (02-04-2020)
    “…Peer-to-Peer lending platforms may lead to cost reduction, and to an improved user experience. These improvements may come at the price of inaccurate credit…”
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    Journal Article
  4. 4

    How generative AI models such as ChatGPT can be (mis)used in SPC practice, education, and research? An exploratory study by Megahed, Fadel M., Chen, Ying-Ju, Ferris, Joshua A., Knoth, Sven, Jones-Farmer, L. Allison

    Published in Quality engineering (02-04-2024)
    “…Generative Artificial Intelligence (AI) models such as OpenAI's ChatGPT have the potential to revolutionize Statistical Process Control (SPC) practice,…”
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    Journal Article
  5. 5

    Space-filling designs for computer experiments: A review by Joseph, V. Roshan

    Published in Quality engineering (02-01-2016)
    “…Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using…”
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    Journal Article
  6. 6

    An improved approach for failure mode and effect analysis involving large group of experts: An application to the healthcare field by Liu, Hu-Chen, You, Xiao-Yue, Tsung, Fugee, Ji, Ping

    Published in Quality engineering (02-10-2018)
    “…Failure mode and effect analysis (FMEA) is a team-based technique for prospectively identifying and prioritizing failure modes of products, processes, and…”
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    Journal Article
  7. 7

    Reinforcement learning for dynamic condition-based maintenance of a system with individually repairable components by Yousefi, Nooshin, Tsianikas, Stamatis, Coit, David W.

    Published in Quality engineering (02-07-2020)
    “…In this article, a reinforcement learning approach is used to develop a new dynamic maintenance policy for multi-component systems with individually repairable…”
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    Journal Article
  8. 8

    Reliability Meets Big Data: Opportunities and Challenges by Meeker, William Q., Hong, Yili

    Published in Quality engineering (02-01-2014)
    “…Reliability field data such as that obtained from warranty claims and maintenance records have been used traditionally for such purposes as generating…”
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    Journal Article
  9. 9

    Dynamic maintenance model for a repairable multi-component system using deep reinforcement learning by Yousefi, Nooshin, Tsianikas, Stamatis, Coit, David W.

    Published in Quality engineering (02-01-2022)
    “…Using artificial intelligence for maintenance planning is useful for many industries to have a smart decision-making tool that delivers the best maintenance…”
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    Journal Article
  10. 10

    Advanced FMEA method based on interval 2-tuple linguistic variables and TOPSIS by Li, Guo-Fa, Li, Yi, Chen, Chuan-Hai, He, Jia-Long, Hou, Tian-Wei, Chen, Jing-Hao

    Published in Quality engineering (01-10-2020)
    “…Failure mode and effects analysis (FMEA) is a widely used technique for identifying, evaluating, and eliminating potential failures in production, system, and…”
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    Journal Article
  11. 11

    Rethinking control chart design and evaluation by Woodall, William H., Faltin, Frederick W.

    Published in Quality engineering (02-10-2019)
    “…We discuss some practical issues involving the control of the number of false alarms in process monitoring. This topic is of growing importance as the number…”
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    Journal Article
  12. 12

    Redefining software reliability modeling: embracing fault-dependency, imperfect removal, and maximum fault considerations by Samal, Umashankar, Kumar, Ajay

    Published in Quality engineering (02-07-2024)
    “…Software reliability is a critical aspect of ensuring the quality and dependability of software systems. However, existing software reliability models often…”
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    Journal Article
  13. 13

    Monitoring univariate processes using control charts: Some practical issues and advice by Zwetsloot, Inez M., Jones-Farmer, L. Allison, Woodall, William H.

    Published in Quality engineering (02-07-2024)
    “…We provide an overview and discussion of some issues and guidelines related to monitoring univariate processes with control charts. We offer some advice to…”
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    Journal Article
  14. 14

    Early fault diagnosis based on reinforcement learning optimized-SVM model with vibration-monitored signals by Zhao, Wenqin, Lv, Yaqiong, Liu, Jialun, Lee, Carman K. M., Tu, Lei

    Published in Quality engineering (02-10-2023)
    “…Effective fault diagnosis maximizes economic benefits by ensuring the stability of machinery systems. Detecting the faults of the key components in machinery,…”
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    Journal Article
  15. 15

    Toward a concept of digital twin for monitoring assembly and disassembly processes by Verna, Elisa, Puttero, Stefano, Genta, Gianfranco, Galetto, Maurizio

    Published in Quality engineering (02-07-2024)
    “…Quality is one of the key factors in the customer's selection process between competing products. Producing high-quality, defect-free products that meet…”
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    Journal Article
  16. 16

    Applying Lean Six Sigma methods to reduce length of stay in a hospital's emergency department by Furterer, Sandra L.

    Published in Quality engineering (03-07-2018)
    “…Operational excellence is critical to throughput and patient flow in an emergency department. This case study applied the Lean Six Sigma DMAIC methodology to…”
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    Journal Article
  17. 17

    I-optimal or G-optimal: Do we have to choose? by Walsh, Stephen J., Lu, Lu, Anderson-Cook, Christine M.

    Published in Quality engineering (02-04-2024)
    “…When optimizing an experimental design for good prediction performance based on an assumed second order response surface model, it is common to focus on a…”
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    Journal Article
  18. 18

    A review of critical success factors for the successful implementation of Lean Six Sigma and Six Sigma in manufacturing small and medium sized enterprises by Stankalla, Roland, Koval, Oksana, Chromjakova, Felicita

    Published in Quality engineering (03-07-2018)
    “…Organizations embarking on implementation of Lean Six Sigma and Six Sigma improvement initiatives need to overcome substantial barriers to ensure effectiveness…”
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    Journal Article
  19. 19

    Lifetime performance-qualified sampling system under a Weibull distribution with failure-censoring by Shu, Ming-Hung, Wu, Chien-Wei, Hsu, Bi-Min, Wang, To-Cheng

    Published in Quality engineering (03-07-2021)
    “…Reducing the warranty cost to increase profit is a major focus for most businesses. To achieve this goal, the acceptance sampling plan (ASP) can be an…”
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    Journal Article
  20. 20

    Reevaluating the performance of control charts based on ranked-set sampling by Woodall, William H., Haq, Abdul, Mahmoud, Mahmoud A., Saleh, Nesma A.

    Published in Quality engineering (02-04-2024)
    “…Nearly one hundred types of control charts have been proposed that incorporate ranked-set sampling (RSS) methods. The performance of these charts has been…”
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    Journal Article