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Integrated artificial intelligence effect on crisis management and lean production: structural equation modelling frame work

Author

Listed:
  • Alim Al Ayub Ahmed

    (Jiujiang University)

  • Arumugam Mahalakshmi

    (M S Ramaiah Institute of Technology)

  • K. ArulRajan

    (PSG Institute of Management, PSG College of Technology)

  • Joel Alanya-Beltran

    (Universidad Tecnológica del Perú)

  • Mohd Naved

    (Amity University)

Abstract

It is a goal that manufacturing companies strive towards on a regular basis, and it involves enhancing the efficiency and productivity of maintenance operations. It is especially vital to avoid unforeseen breakdowns, which may result in costly charges and production losses if they do not occur in advance. While the execution of an acceptable management plan affects maintenance productivity, it also affects the adoption of proper procedures and tools to help in the assessment processes in this field. This difficulty, among other things, affects a company's capacity to achieve high performance with the equipment it employs, as well as the judgement process and the design of the firm's maintenance plan. In order to achieve this goal, the aim of this paper is to exemplify how intelligent systems can be used to enhance judgement techniques in the implementation of the lean maintenance perspective, allowing for an advancement in the functional capabilities of the industry's technological infrastructure. The reseachers employed artificial intelligence technologies to look for connections between specific operations carried out as part of the deployment of lean maintenance and the findings achieved. The raw set notion, which was used in this situation, was used to determine whether or not the lean maintenance method was being used in this study. The crisis management process carries with it some of the most complex data technology concerns ever encountered. It necessitates, among other items, active information gathering and information transfer efforts, that are used for a range of functions, such as decreasing uncertainty, attempting to measure and manage consequences, and attempting to manage resources in a way that goes beyond what is generally possible to deal with daily problems. It also needs the employment of artificial intelligence technology, among other things, to increase crisis awareness.

Suggested Citation

  • Alim Al Ayub Ahmed & Arumugam Mahalakshmi & K. ArulRajan & Joel Alanya-Beltran & Mohd Naved, 2023. "Integrated artificial intelligence effect on crisis management and lean production: structural equation modelling frame work," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 220-227, February.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-022-01679-1
    DOI: 10.1007/s13198-022-01679-1
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    References listed on IDEAS

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    1. Amit Sookoo & Lalit Garg & Chinmay Chakraborty, 2021. "Improvement of system performance in an IT production support environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 461-479, June.
    2. Reiner, Gerald, 2005. "Customer-oriented improvement and evaluation of supply chain processes supported by simulation models," International Journal of Production Economics, Elsevier, vol. 96(3), pages 381-395, June.
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