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This paper (Part 2 of 2) aims to expand the previously developed performance assessment model (PAM) into a decision support system (DSS) to produce optimized decisions on rehabilitation of facilities.

The research includes a comprehensive PAM that integrates analytical hierarchy process-multi attribute utility theory methods for the physical, operational, and environmental aspects of the mosque, as described in Part 1 of the study. An optimized intervention tool is added to the PAM to complete the DSS development. The tool determines the optimum maintenance decisions that are in line with the budget and condition criticality. The deterioration measures are created using a deterministic straight-line extrapolation technique, and the intervention actions used in the optimization are specified through literature review and in-depth interviews with 11 experts. The optimization model was simplified into a user-friendly visual basic application and applied to an existing facility case study depicting its useful functionality.

The optimization model recommendation of interventions recovered the overall condition rating index (CRI) of the facility while maintaining budget constraints. The CRI in the first approach (minimum budget to achieve acceptable overall performance) was improved from 6.5 to 7.76, costing 275,850 SAR. While the second approach (Maximum recovery with a selected budget constraint, 300,000 SAR in this case) CRI was improved from 6.5 to 8.3, costing 299,850 SAR.

The presented DSS in this paper offers a tool that enables the rehabilitation and overall management of any facility by its managers. The DSS can also be further customized to fit the facility manager’s specific strategies and achieve desired objectives.

The purpose of this paper (Part 1 of 2) is to develop a systematic performance assessment model (PAM) for measuring facilities condition in terms of physical, environmental and operational impacts on performance.

The methodology entailed a review of literature to identify performance impacting factors (PIFs) of a facility. PIFs were categorized as physical, environmental and operational. Subsequently, 71 experts were interviewed to prioritize the identified PIFs in terms of their impact on facility performance via analytical hierarchy process (AHP) technique. A second round of interviews with 11 experts was conducted to set a utility scoring mechanism for the PIFs via multiattribute utility theory (MAUT) technique, the utility score in correlation to a set scale would describe the level of service(LoS). Finally, AHP and MAUT outputs were mathematically integrated to determine the final condition rating index of all PIFs and the whole facility as a result.

First, PIFs of a case study mosque facility under three scenarios with different groupings of functional spaces were defined. Functional spaces’ prioritization was as follows: prayer hall (57%–65%), wet areas (25%–26%), minaret (9%–10%), and yard/site (7%–8%). Subsequently, each space’s PIFs and its subcategories were assigned weights as well, the first level of PIFs’ relative weights was as follows: physical (68%–73%), operational (19%–20%) and environmental (7%–13%). Physical PIFs weights differed per functional space but structural factor dominated with (38%–71%) relative weight except for the yard/site. Finally, a detailed condition evaluation mechanism for each PIF was defined.

This study contributes to facilities management industry and offers a systematic approach encompassing multiple PIFs that will regulate inspection then maintenance through desired corrective actions by facility managers to achieve desired LoS.