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Forecasting Repair Schedule for Building Components Based on Case-Based Reasoning and Fuzzy-AHP

Author

Listed:
  • Sojin Park

    (Department of Architectural Engineering, Hanyang University, Ansan 1588, Korea)

  • Nahyun Kwon

    (Department of Architectural Engineering, Hanyang University, Ansan 1588, Korea)

  • Yonghan Ahn

    (Department of Architectural Engineering, Hanyang University, Ansan 1588, Korea)

Abstract

Building maintenance is closely related to the performance and sustainability of buildings. However, existing approaches to maintenance are limited in terms of estimating required repairs. Therefore, this study proposes a case-based reasoning (CBR)-based model for estimating the time when the first repair will be needed after the completion of construction, even in phases where maintenance-related information is scarce. CBR and fuzzy-analytic hierarchy process (AHP) were employed as research methodologies. A database was established by collecting 257 cases related to maintenance of apartment buildings, and attributes were extracted through literature reviews and expert interviews. Then, attributes were weighted by fuzzy-AHP and case similarities were computed by measuring the Euclidean distance. Similar cases were retrieved based on similarity scores. The model was validated via a comparison of 20 randomly selected test cases with the output of retrieved cases. The results showed that the average case similarities of 3-, 5-, 7-, and 10-nearest neighbors (NN) were 98.05%, 97.86%, 97.73%, and 97.59%, respectively, and mean absolute percentage errors for 3-, 5-, 7-, and 10-NN were mostly lower than 20%, confirming the applicability of the proposed model. The proposed method will help in the preliminary estimation of the repair time of building components.

Suggested Citation

  • Sojin Park & Nahyun Kwon & Yonghan Ahn, 2019. "Forecasting Repair Schedule for Building Components Based on Case-Based Reasoning and Fuzzy-AHP," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7181-:d:298172
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    References listed on IDEAS

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    1. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
    2. Sanghyo Lee & Yonghan Ahn, 2018. "Analyzing the Long-Term Service Life of MEP Using the Probabilistic Approach in Residential Buildings," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
    3. Nahyun Kwon & Kwonsik Song & Moonseo Park & Youjin Jang & Inseok Yoon & Yonghan Ahn, 2019. "Preliminary Service Life Estimation Model for MEP Components Using Case-Based Reasoning and Genetic Algorithm," Sustainability, MDPI, vol. 11(11), pages 1-17, May.
    4. Soyeon Park & Yonghan Ahn & Sanghyo Lee, 2018. "Analyzing the Finishing Works Service Life Pattern of Public Housing in South Korea by Probabilistic Approach," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    5. Kim, Sungil & Kim, Heeyoung, 2016. "A new metric of absolute percentage error for intermittent demand forecasts," International Journal of Forecasting, Elsevier, vol. 32(3), pages 669-679.
    6. Nahyun Kwon & Joosung Lee & Moonsun Park & Inseok Yoon & Yonghan Ahn, 2019. "Performance Evaluation of Distance Measurement Methods for Construction Noise Prediction Using Case-Based Reasoning," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    7. I. M. Shohet & M. Puterman & E. Gilboa, 2002. "Deterioration patterns of building cladding components for maintenance management," Construction Management and Economics, Taylor & Francis Journals, vol. 20(4), pages 305-314.
    8. Kaya, Tolga & Kahraman, Cengiz, 2010. "Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul," Energy, Elsevier, vol. 35(6), pages 2517-2527.
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    Cited by:

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    2. Youngduk Cho & Sanghyo Lee & Joosung Lee & Jaejun Kim, 2021. "Analysis of the Repair Time of Finishing Works Using a Probabilistic Approach for Efficient Residential Buildings Maintenance Strategies," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    3. Robert Bucoń & Agata Czarnigowska, 2021. "Sequential Model for Long-Term Planning of Building Renewal and Capital Improvement," Sustainability, MDPI, vol. 13(17), pages 1-22, August.

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