Establishing Multi-level Performance Condition Indices for
Public Schools Maintenance Program Using AHP and Fuzzy Logic
Mohamed MARZOUK1, Ehab AWAD2*
1 Dept. of Structural Engineering, Cairo University,
Giza, 12613, Egypt
* Corresponding author
2 Orascom Construction,
2005 A Corniche El Nil, Cairo, 11221, Egypt
Abstract: This research targets the creation of indices to enforce standard assessment for group of educational buildings and to set common understanding of facilities’ condition among different stakeholders. This model contains four levels of performance assessment that deal with program, facility, package, and element. AHP-fuzzy model is built using linguistic expression to represent condition of asset. The proposed model generates standard indices for three levels (element, package, and facility) which are aggregated to provide realistic condition assessment for a group of facilities (program). For evaluation of this model, a case study is presented with data from 21 schools in Giza governorate-Egypt to provide these indices. Example for assessment of two elements is worked out to illustrate the feasibility of this model. Outputs could be used by management as part of the decision support system.
Keywords: AHP, Fuzzy Logic, Facility Assessment, Educational facilities, Condition index.
CITE THIS PAPER AS:
Mohamed MARZOUK, Ehab AWAD*, Establishing Multi-level Performance Condition Indices for Public Schools Maintenance Program Using AHP and Fuzzy Logic, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(3), pp. 343-352, 2016.
In Egypt, the total number of students attending public schools is 17.990.836 representing 90% of the total student population with 414.258 classrooms (MOE 2016). Managing maintenance of that large network of educational assets requires the built up of necessary measurement standard for assessing building conditions with minimizing the bias of human judgment. This research provides a methodology for establishing multi-levels performance condition indices for public schools maintenance program using AHP and fuzzy logic. The methodology enables the following:
- Setting process for developing and generating four indices with providing proposed action. These condition performance indices can be applied for assessment of group of educational buildings on different levels. These levels are, program which is the highest level which include group of facilities, facility, which includes group of spaces, and Package which consists of elements with similarity in trades like finishing and mechanical. Finally, element like floor or openings which is the lowest level to be assessed; and it is evaluated based on Inspection of its properties.
- Enabling systematic data collection with reducing biasness. This is done by implementing standard steps for evaluation of each element within facility.
- Upon completion of process, different stakeholders like facility user, decision makers, and program managers should have common understanding regarding asset condition and proposed maintenance program main goals.
- ASCE, Report Card for America’s Infrastructure 2013, American Society of Civil Engineers. Aval. at www.infrastruct urereportcard.org (accessed April 1, 2016).
- DOZZI, P., S. M. ABOURIZK, S. L. SCHROEDER, Utility-Theory Model for Bid Markup Decisions, Construction Engineering and Management, vol. 122(2), 1996, pp. 119-124.
- EL CHANATI, H., M. EL-ABBASY, F. MOSLEH, A. SENOUCI, M. ABOUHAMAD, I. GKOUNTIS, T. ZAYED, H. AL-DERHAM, Multi-Criteria Decision Making Models for Water Pipelines, Performance of Constructed Facilities, 30(4), 2016.
- ERMINI, R., R. ATAOUI, Computing a Global Performance Index by Fuzzy Set Approach, Procedia Eng., vol. 70, 2014, pp. 622-632.
- GHARAIBEH,, Y. ZOU, S. SALIMINEJAD, Assessing the Agreement among Pavement Condition Indexes, Transportation Engineering, vol. 136, 2010, pp. 765-772.
- JEONG, K., C. JI, C. KOO, T. HONG, H. PARK, A Model for Predicting the Environmental Impacts of Educational Facilities in the Project Planning Phase, Cleaner Prod., vol. 107, 2015, pp. 538-549.
- MARZOUK, M., A. ABDELATY, BIM-based Framework for Managing Performance of Subway Stations, Automation in Construction, vol. 41(1), 2014, pp. 70-77.
- MARZOUK, M., O. MOSELHI, A Decision Support Tool for Construction Bidding, Construction Innovation, vol. 3(2), 2003, pp. 111-124.
- MITRA, K. J, B. BHATTACHARJEE, Condition Assessment of Corrosion-Distressed Reinforced Concrete Buildings using Fuzzy Logic, Performance of Constructed Facilities, vol. 24(6), 2010, pp. 562-570.
- MOE, Annual Statistics Book 2014-2015, Egypt Ministry of Education, available at http://emis.gov.eg/annual_book.aspx?id=400 (accessed March 15, 2016).
- NACOCU, Terms and Glossary; Facilities and Sustainability Related, National Association of College and Universities, available at http://www. nacubo.org/Documents/business_topics/GlossaryTermsFacilitiesSustainability.pdf (accessed April 30, 2016).
- PODGORSKI, Measuring Operational Performance of OSH Management System – A Demonstration of AHP-based Selection of Leading Key Performance Indicators, Safety Science, vol. 73, 2015, pp.146-166.
- ROBERTS, L., Measuring School Facility Conditions: an Illustration of the Importance of Purpose, Journal of Educational Administration, vol. 47(3), 2009, pp. 368-380.
- SAATY, L., Decision Making with analytic Hierarchy Process, International Journal of Services Sciences, vol. 1(1), 2008, pp. 83-98.
- ŞERBU, R., BORZA S., Achieving Sustainable Competitive Advantage of Romanian Rural Area by Integrating Information Technologies: an Interdisciplinary Approach, Studies in Informatics and Control, vol. 23(2), 2014, pp. 215-222.
- ULINE, C., MOREN, M., The Walls Speak: the Interplay of Quality Facilities, School Climate, and Student Achievement, Educational Administration, vol. 46(1), 2006, pp. 55-73.
- VAVATSKIOS, P., K. P. ANAGNOSTOPOULOS, An AHP Model for Construction Contractor Pre-qualification, International Journal of Op. Research, vol. 6(3), 2006, pp. 333-346.