☆ 4.6 Article

Prediction of Maintenance Activities Using Generalized Sequential Pattern and Association Rules in Data Mining

BUILDINGS (2023)

Related references

Note: Only part of the references are listed.

Article Engineering, Industrial

Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines

Mihaela Mitici et al.

Summary: The development of data-driven Remaining Useful Life (RUL) prognostics has been incentivized by the increasing availability of condition-monitoring data for components/systems. However, most studies focus on point RUL prognostics without considering the uncertainty associated with these estimates, limiting their applicability to maintenance planning. In this paper, probabilistic RUL prognostics are developed using Convolutional Neural Networks and integrated into maintenance planning for aircraft turbofan engines. The results indicate that the proposed approach reduces costs and leads to a limited number of failures compared to traditional strategies.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2023)

Add to Collection

Article Computer Science, Artificial Intelligence

Optimal fuzzy repairs' scheduling and sequencing of failure types over multiple periods

Abbas Al-Refaie et al.

Summary: The research proposes optimization models for repairs' scheduling and sequencing to efficiently minimize maintenance costs and maximize the number of failure repairs and shops' utilization. Sensitivity analyses show that these models can effectively achieve the goals of the maintenance department. This contributes significantly to the theory of maintenance planning.

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2022)

Add to Collection

Article Green & Sustainable Science & Technology

The Relationships between the Pillars of TPM and TQM and Manufacturing Performance Using Structural Equation Modeling

Abbas Al-Refaie et al.

Summary: This study examines the relationships between the pillars of total quality management (TQM) and total productive maintenance (TPM) and their effects on manufacturing performance (MPR). The findings suggest that there are variations in the levels of implementation of TPM, TQM, and MPR pillars among firms, and TPM has a greater impact on MPR than TQM. This research provides valuable information for top management in the industrial sector to enhance MPR by identifying important TQM/TPM pillars.

SUSTAINABILITY (2022)

Add to Collection

Article Engineering, Civil

C2FDA: Coarse-to-Fine Domain Adaptation for Traffic Object Detection

Hui Zhang et al.

Summary: This paper proposes a novel category-induced coarse-to-fine domain adaptation approach (C2FDA) for cross-domain object detection, which significantly outperforms the state-of-the-art on multiple domain adaptation scenarios, including synthetic-to-real adaptation, weather adaptation, and cross camera adaptation. The approach consists of three pivotal components: ACGA, attention-induced feature selection module, and CFGA.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)

Add to Collection

Article Green & Sustainable Science & Technology

A data-driven approach for establishing a CO2 emission benchmark for a multi-family housing complex using data mining techniques

Kwangbok Jeong et al.

Summary: South Korea developed new CE benchmarks for buildings in the construction industry using an operational rating system and data mining techniques, improving the reliability and rationality of the conventional CE benchmarks, thereby solving the issues and enhancing the existing operational rating system.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Add to Collection

Review Engineering, Industrial

Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review

Joerg Leukel et al.

Summary: The review of failure prediction in industrial maintenance using ML technology identified issues such as heterogeneity in systems and domains addressed, adoption of up-to-date approaches, lack of performance evaluation to mitigate overfitting, and varying reporting of experimental designs and results. Opportunities for future research include exploring new methods and suggesting ways to facilitate comparison and integration of evidence.

JOURNAL OF MANUFACTURING SYSTEMS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms

Jacinto Carrasco et al.

Summary: The research in anomaly detection lacks a unified definition of what represents an anomalous instance, leading to diverse paradigms in algorithm design and experimentation. Predictive maintenance represents a special case, where anomalies must be prevented to avoid failures. To address these issues, the concept of positive and negative instances has been generalized into intervals for evaluating unsupervised anomaly detection algorithms.

NEUROCOMPUTING (2021)

Add to Collection

Article Computer Science, Theory & Methods

Minimum threshold determination method based on dataset characteristics in association rule mining

Erna Hikmawati et al.

Summary: Association rule mining is a widely used technique in data mining to identify interesting relationships between sets of items in a dataset, with the key to success being the correct setting of thresholds. The proposed adaptive support method can generate rules according to user needs based on dataset characteristics.

JOURNAL OF BIG DATA (2021)

Add to Collection

Article Computer Science, Information Systems

Selective Maintenance on a Multi-State Transportation System Considering Maintenance Sequence Arrangement

Yao Sun et al.

Summary: This paper proposes a new selective maintenance model for a multi-state system, aiming to maximize system reliability by selecting and arranging a subset of maintenance activities. The tailored ant colony optimisation algorithm proves effective in improving system reliability according to two example analyses presented in the paper.

IEEE ACCESS (2021)

Add to Collection

Article Engineering, Industrial

A data mining approach for lubricant-based fault diagnosis

James Wakiru et al.

Summary: This paper develops a maintenance decision support system framework using in-service lubricant data for fault diagnosis. The importance of embedded knowledge explored via knowledge discovery approach is shown, emphasizing the efficacy of embedded knowledge on maintenance DSS. The framework potentially assists maintenance managers in accurately utilizing lubricant data for decision support, providing insights with reduced time and errors.

JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING (2021)

Add to Collection

Article Engineering, Civil

PROPOSED PROCEDURE FOR OPTIMAL MAINTENANCE SCHEDULING UNDER EMERGENT FAILURES

Abbas Al-Refaie et al.

JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT (2020)

Add to Collection

Article Management

Procedure structuring for programming aircraft maintenance activities

Viviane Souza Vilela Junqueira et al.

REGE-REVISTA DE GESTAO (2020)

Add to Collection

Article Management

Designing predictive maintenance systems using decision tree-based machine learning techniques

Shashidhar Kaparthi et al.

INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT (2020)

Add to Collection

Article Engineering, Industrial

Application of data mining for spare parts information in maintenance schedule: a case study

U. C. Moharana et al.

JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT (2019)

Add to Collection

Article Construction & Building Technology

Development of a decision support model for determining the target multi-family housing complex for green remodeling using data mining techniques

Kwangbok Jeong et al.

ENERGY AND BUILDINGS (2019)

Add to Collection

Article Engineering, Industrial

Imperfect corrective maintenance scheduling for energy efficient manufacturing systems through online task allocation method

Tian Yu et al.

JOURNAL OF MANUFACTURING SYSTEMS (2019)

Add to Collection

Article Computer Science, Artificial Intelligence

An integrated approach for aircraft turbofan engine fault detection based on data mining techniques

Hassan Gharoun et al.

EXPERT SYSTEMS (2019)

Add to Collection

Article Engineering, Multidisciplinary

Failure Prediction of Mine Compressors

Johannes A. Jacobs et al.

JOURNAL OF FAILURE ANALYSIS AND PREVENTION (2019)

Add to Collection

Article Computer Science, Information Systems

A Data-Driven Approach to Improve the Operation and Maintenance Management of Large Public Buildings

Qiao Wen et al.

IEEE ACCESS (2019)

Add to Collection

Article Computer Science, Information Systems

A Real-Time Maintenance Policy for Multi-Stage Manufacturig Systems Considering Imperfect Maintenance Effects

Jing Huang et al.

IEEE ACCESS (2018)

Add to Collection

Article Environmental Sciences

Data mining in mining engineering: results of classification and clustering of shovels failures data

Saeid R. Dindarloo et al.

INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT (2017)

Add to Collection

Article Engineering, Manufacturing

Yield Prediction Through the Event Sequence Analysis of the Die Attach Process

Hoyeop Lee et al.

IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING (2015)

Add to Collection

Article Engineering, Aerospace

Direct maintenance cost prediction of civil aircraft

Huawei Wang et al.

AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY (2014)

Add to Collection

Article Engineering, Multidisciplinary

Steady-state availability analysis of repairable mechanical systems with opportunistic maintenance by using Semi-Markov process

Girish Kumar et al.

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT (2014)

Add to Collection

Article Engineering, Civil

Integration of GIS and Data Mining Technology to Enhance the Pavement Management Decision Making

Guoqing Zhou et al.

JOURNAL OF TRANSPORTATION ENGINEERING (2010)

Add to Collection

Article Computer Science, Interdisciplinary Applications

Sequential pattern mining algorithm for automotive warranty data

Jirachai Buddhakulsomsiri et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2009)

Add to Collection

Article Engineering, Industrial

Association rule-generation algorithm for mining automotive warranty data

J. Buddhakulsomsiri et al.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2006)

Add to Collection

© Peeref 2019-2024. All rights reserved.