skip to main content
10.1145/3647444.3647837acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicimmiConference Proceedingsconference-collections
research-article

Fuzzy Logic Decision Making Approach to identify the maximum influencing factor on productivity

Published: 13 May 2024 Publication History
  • Get Citation Alerts
  • Abstract

    Enhancing productivity is a core objective of any organization whether it is manufacturing or service one. Several factors both technological and human related are responsible for an improved performance. Beyond continuous improvement in process, sound product design and efficient process design, factors related with human aspects are responsible for enhanced performance of any manufacturing organization. Organization structure, ergonomics, motivation and group cohesiveness are significant human related factors. This article has considered those human related factors and applied the multi criteria decision making technique fuzzy logic to rank those factors based on the survey conducted in a small-scale manufacturing industry. The paper ranks those factors by fuzzy scores and identifies the most influencing factor for the organization.

    References

    [1]
    Sammarco, M., Fruggiero, F., Neumann, W. P., & Lambiase, A. (2013). Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance. International Journal of Production Research, 52(3), 633–650. 
    [2]
    Sun, X., Houssin, R., Renaud, J., & Gardoni, M. (2018). A review of methodologies for integrating human factors and ergonomics in engineering design. International Journal of Production Research, 1–16. 
    [3]
    Lee, M. T., & Raschke, R. L. (2016). Understanding employee motivation and organizational performance: Arguments for a set-theoretic approach. Journal of Innovation & Knowledge, 1(3), 162–169. 
    [4]
    Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396. 
    [5]
    Spanemberg, F., Ferreira, A., Silva, M. and Sellitto, M. (2020). Investing in the knowledge of shop floor workforce – a systemic analysis. International Journal of Industrial Engineering: Theory, Practice and Applications. 27(4). Pp 546-557
    [6]
    Müceldili, B., & Erdil, O. (2015). Cultivating Group Cohesiveness: The Role of Collective Energy. Procedia - Social and Behavioral Sciences, 207, 512–518. 
    [7]
    Chen, L., & Wang, P. P. (2002). Fuzzy relation equations (I): the general and specialized solving algorithms. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 6(6), 428–435.
    [8]
    Hsieh, T.-Y., Lu, S.-T., & Tzeng, G.-H. (2004). Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 22(7), 573–584. 
    [9]
    Dursun, M. and Arslan, O. (2020). A combined fuzzy multi-criteria group decision making framework for material selection procedure: integration of fuzzy qfd with fuzzy topsis, International Journal of Industrial Engineering, Theory, Practice and Applications.27(4).pp 585-601.
    [10]
    Mohanty, B. K., & Bhasker, B. (2005). Product classification in the Internet business—a fuzzy approach. Decision Support Systems, 38(4), 611–619. 
    [11]
    Olfat, L., Mahsa Pishdar, M., and Ghasemzadeh, F. (2019). A type-2 fuzzy network data envelopment analysis for fmcg distributors’ performance evaluation with sustainability approach. International Journal of Industrial Engineering:Theory, Practice and Applications. 26(5). Pp 663-687.
    [12]
    Carron, A. V., Bray, S. R., & Eys, M. A. (2002). Team cohesion and team success in sport. Journal of Sports Sciences, 20(2), 119–126. 

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICIMMI '23: Proceedings of the 5th International Conference on Information Management & Machine Intelligence
    November 2023
    1215 pages
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 May 2024

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Artificial intelligence
    2. Knowledge representation and reasoning
    3. Vagueness and fuzzy logic
    4. computing methodologies
    5. ergonomics
    6. fuzzy logic
    7. group cohesiveness
    8. motivation
    9. organizational structure
    10. productivity

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICIMMI 2023

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 7
      Total Downloads
    • Downloads (Last 12 months)7
    • Downloads (Last 6 weeks)2
    Reflects downloads up to 14 Aug 2024

    Other Metrics

    Citations

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format.

    HTML Format

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media