Maintenance Service Configuration Optimization for Complex Equipment

Zhou, Chunliu; Ye, Shan; Wang, Hongjun; Cao, Jiannong; Gao, Zhenhua

doi:10.3390/systems11010032

Cited by 4 publications

(1 citation statement)

References 23 publications

(27 reference statements)

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“…Zhu, et al comprehensively considered various kinds of operation, shift preparation, and other factors, and obtained the standard staffing number of vehicle service systems, which provided a theoretical basis for operating enterprises to reserve personnel in advance [12]. Wang found that the reasonable allocation of the hospital's own medical equipment maintenance technical force is an important means to improve the comprehensive benefits of the hospital [13]. Ma et al use the casebased reasoning method and introduce relevant principles and methods of BP neural network in the case retrieval process to calculate the demand for equipment maintenance personnel from past practical experience.…”

Section: Introductionmentioning

confidence: 99%

A Method for Determining the Requirements of Electronic Equipment Maintenance Personnel Based on FAHP and Queuing Theory

Cheng,

Liu,

Xin

2024

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The high technological content of electronic equipment and the increased difficulty of failure maintenance make the battlefield emergency repair tasks of electronic equipment complex and heavy in wartime. It is very important for decision-makers to determine the wartime maintenance personnel requirements of electronic equipment to meet the task requirements and avoid the waste of maintenance resources. Based on the fuzzy analytical hierarchy process (FAHP), the relevance evaluation of maintenance professional types was first carried out, and then the degree of the professional type irreplaceability was evaluated, and the technical level for maintenance personnel was determined successfully. Based on accompanied maintenance and fixed points maintenance, the optimal maintenance personnel quantity model is established by the queuing theory model. Finally, taking a new electronic reconnaissance vehicle as an example, the maintenance requirements of the reconnaissance system of the vehicle are analyzed. The results show that the model proposed in this paper provides technical support and a quantitative analysis method for the determination of electronic equipment maintenance requirements during wartime. The paper also puts forward some interesting research directions for the future.

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Section: Introductionmentioning

confidence: 99%

A Method for Determining the Requirements of Electronic Equipment Maintenance Personnel Based on FAHP and Queuing Theory

Cheng,

Liu,

Xin

2024

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NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking

Kabashkin

2024

Algorithms

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The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) for digital twin management in aviation, with a focus on component lifecycle tracking. The proposed approach uses NFTs to create unique, immutable digital representations of physical aviation components capturing real-time records of a component’s entire lifecycle, from manufacture to retirement. This paper outlines detailed workflows for key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership and leasing, technical documentation, and quality assurance. This paper introduces a class of algorithms designed to manage the complex relationships between physical components, their digital twins, and associated NFTs. A unified model is presented to demonstrate how NFTs are created and updated across various stages of a component’s lifecycle, ensuring data integrity, regulatory compliance, and operational efficiency. This paper also discusses the architecture of the proposed system, exploring the relationships between data sources, digital twins, blockchain, NFTs, and other critical components. It further examines the main challenges of the NFT-based approach and outlines future research directions.

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A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing

Lee

2023

Processes

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In the evolving landscape of manufacturing, the integration of intelligent control theory stands as a pivotal advancement, driving both process optimization and the paradigm of smart manufacturing. This review delves into the multifaceted applications of intelligent control theory, emphasizing its role in equipment, operations, and controls optimization. With a focus on three primary methodologies—fuzzy logic, neural networks, and genetic algorithms—the paper elucidates their biological parallels and their significance in simulation, modeling, and optimization. The transformative potential of smart manufacturing, synonymous with Industry 4.0, is also explored, highlighting its foundation in data, automation, and artificial intelligence. Drawing from a comprehensive analysis of recent literature, the review underscores the growing interest in this domain, as evidenced by the surge in publications and citations over the past decade. The overarching aim is to provide contemporary discourse on the applications and implications of intelligent control theory in the realms of process optimization and smart manufacturing.

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Maintenance Service Configuration Optimization for Complex Equipment

Cited by 4 publications

References 23 publications

A Method for Determining the Requirements of Electronic Equipment Maintenance Personnel Based on FAHP and Queuing Theory

A Method for Determining the Requirements of Electronic Equipment Maintenance Personnel Based on FAHP and Queuing Theory

NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking

A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing

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