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Design and Implement Low-Cost Industry 4.0 System using Hybrid Six Sigma Methodology for CNC Manufacturing Process

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253820" target="_blank" >RIV/61989100:27240/23:10253820 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10314511" target="_blank" >https://ieeexplore.ieee.org/document/10314511</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ACCESS.2023.3331818" target="_blank" >10.1109/ACCESS.2023.3331818</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Design and Implement Low-Cost Industry 4.0 System using Hybrid Six Sigma Methodology for CNC Manufacturing Process

  • Original language description

    The mechanical components manufacturing industry is carried out through turning processes using CNC machines. Improving productivity and improving product quality in the CNC process is necessary. Automating operations at the CNC process with Industry 4.0 technology at low cost is a direction in the right direction with the development trend of Industry 4.0 technology. Making decisions to improve CNC processes at operations and implementing continuous improvement is an urgent activity. Industry 4.0 technology helps connect data between customer companies, business sectors, and supply chain partners in a more specific and simple way. Commonly connected data between companies helps decision-makers at each company have a common source of analytical data to make more effective production and business development decisions. Industry 4.0 technologies are the subject of much research, but it is important to consider how to integrate them into the manufacturing world in the most efficient and effective way possible. Manufacturers will benefit from this article&apos;s additional insights to solve their problems more effectively. This paper proposes a Hybrid Six Sigma methodology based on Fuzzy TOPSIS and PLS-SEM methods. First, the Fuzzy TOPSIS method helps decision-makers to select problem points for improvement in an unknown environment to implement continuous improvement. Second, the PLS-SEM method evaluates the impact factors of the results of continuous improvement at the mechanical component factory. The Industry 4.0 technology is proposed to be designed, tested, and installed in the CNC manufacturing process. As a result of this study, the product length dimensional error rate decreased from 54.90% per month to zero defects, saving $9593 in annual production costs. Research machines are semi-automatic and cannot increase or digitize their performance because of studies on the application of low-cost Industry 4.0 technology systems to increase the capacity of industrial processes. This study contributes by using Industry 4.0 technology&apos;s low-cost way to improve manufacturing processes using the Hybrid DMAIC method in Six Sigma methodology. This hybrid approach is adaptable and can be used with different business process improvement models. Authors

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Access

  • ISSN

    2169-3536

  • e-ISSN

  • Volume of the periodical

    11

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    1

  • Pages from-to

    1

  • UT code for WoS article

    001118709500001

  • EID of the result in the Scopus database

    2-s2.0-85177042889