THE IMPLICATIONS IMPOSED BY PRESCRIPTIVE MAINTENANCE IMPLEMENTATION INTO THE INDUSTRY 4.0- A CURRENT STATE ANALYSIS

被引:0
|
作者
Pop-Suarasan, Ana-Diana [1 ]
Ungureanu, Nicolae Stelian [1 ]
机构
[1] Tech Univ Cluj Napoca, Fac Engn, Dept Engn & Management, 62A Dr Victor Babes St, Baia Mare 430083, Romania
来源
ACTA TECHNICA NAPOCENSIS SERIES-APPLIED MATHEMATICS MECHANICS AND ENGINEERING | 2023年 / 66卷
关键词
Prescriptive maintenance; Industry; 4.0; Management; Change mechanism; REVOLUTION;
D O I
暂无
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
In the context of an information technology era, digitalization and a fulminant technological evolution, the prescriptive maintenance occupies a crucial place for increased automation and continuous improvement processes. The concepts and technologies of Industry 4.0 can be applied to various industrial models, starting from the production line and continuing to the decision-making act. The automation, design and operationalization of maintenance plans are becoming more and more effective due to technologies based on the processing of the Artificial Intelligence's machine learning algorithms. Concretely, this paper aims to address a method in which an innovative maintenance strategy, such as the prescriptive one, can influence the organizational development. The predictability, the visibility and the efficiency of the prescriptive analytics and the use of technologies such as the Internet of Things and Big Data provide an improved interconnectivity between systems. Thus, the research proposes to achieve a strategy to determine the manner and application degree in which the prescriptive maintenance will be applied depending on the organizational technical characteristics. This paper presents an analysis of the specialized literature in the field of maintenance, which allows the identification of further research directions.
引用
收藏
页码:157 / 164
页数:8
相关论文
共 50 条
  • [21] Study and Analysis of Barriers for Implementation of Industry 4.0 Technologies Using Spherical Fuzzy TOPSIS Method
    Kumar, Akshay
    Krishna, Chimata Murli
    SAGE OPEN, 2025, 15 (01):
  • [22] Exploring the relationships between Industry 4.0 implementation factors through systems thinking and network analysis
    Hoyer, Christian
    Gunawan, Indra
    Reaiche, Carmen Haule
    SYSTEMS RESEARCH AND BEHAVIORAL SCIENCE, 2023, 40 (04) : 723 - 739
  • [23] Process Planning in Industry 4.0-Current State, Potential and Management of Transformation
    Trstenjak, Maja
    Opetuk, Tihomir
    Cajner, Hrvoje
    Tosanovic, Natasa
    SUSTAINABILITY, 2020, 12 (15)
  • [24] Assessing the Barriers to Industry 4.0 Implementation From a Maintenance Management Perspective-Pilot Study Results
    Jasiulewicz-Kaczmarek, Malgorzata
    Antosz, Katarzyna
    Zhang, Chao
    Waszkowski, Robert
    IFAC PAPERSONLINE, 2022, 55 (02): : 223 - 228
  • [25] Implementation Of Industry 4.0 Principles In The Supply Chain: An Umbrella Review On The State of the Art And Challenges
    Palandella, Lucila
    Perea Munoz, Lourdes
    Ruiz, Angel
    PROCEEDINGS OF THE CONFERENCE ON PRODUCTION SYSTEMS AND LOGISTICS, CPSL 2024, 2024, : 666 - 675
  • [26] Digitally enabled circular economy with Industry 4.0 Requirement analysis and implementation vision
    Gruener, Sten
    Gamer, Thomas
    Gitzel, Ralf
    Ulrich, Marco
    ATP MAGAZINE, 2022, (03): : 88 - 96
  • [27] Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review
    Werbinska-Wojciechowska, Sylwia
    Winiarska, Klaudia
    SENSORS, 2023, 23 (03)
  • [28] An Industry 4.0 implementation of a condition monitoring system and IoT-enabled predictive maintenance scheme for diesel generators
    Mohapatra, Ambarish Gajendra
    Mohanty, Anita
    Pradhan, Nihar Ranjan
    Mohanty, Sachi Nandan
    Gupta, Deepak
    Alharbi, Meshal
    Alkhayyat, Ahmed
    Khanna, Ashish
    ALEXANDRIA ENGINEERING JOURNAL, 2023, 76 : 525 - 541
  • [29] Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges
    Bonilla, Silvia H.
    Silva, Helton R. O.
    da Silva, Marcia Terra
    Goncalves, Rodrigo Franco
    Sacomano, Jose B.
    SUSTAINABILITY, 2018, 10 (10)
  • [30] A maturity model for assessing Industry 4.0 implementation using data envelopment analysis and best and worst method approaches
    Abdullah, Ahmad
    Saraswat, Shantanu
    Talib, Faisal
    INTERNATIONAL JOURNAL OF PRODUCTIVITY AND PERFORMANCE MANAGEMENT, 2024,