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Weekly UpdatesThe Output Interface
The Output Interface provides the user with the analyses and results of the facility in question on a variety of topics: economic, performance, risk, maintenance policy setting, and sources of labor. This interface implements inductive reasoning, i.e., the policy setting and output parameters are deduced from the component to system layer; the latter layers are then incorporated into the analysis of the building and facility. In this interface, the user begins with the results of the analyses conducted in the Reasoning Evaluator and Predictor interface. The Output Interface is subdivided into two phases: the first phase of the Output Interface (Phase D) deals with particular data for the facility, including economic (e.g., projected Annual Maintenance Expenditure), performance (e.g., projected level of performance), and risk (e.g., projected level of risk) aspects, which are divided into the following four layers: Components Evaluation, Systems Analysis, Building Analysis, and Facility Analysis (Layers 8 to 11). The second phase (Phase E) compares the facility's main Key Performance Indicators with other facilities, and includes Policy Setting for maintenance and sources of labor for each of the systems and buildings in the facility (Layer 12).
Two principles outline the design of the proposed IHFMM, as follows:
1. The architecture of the database is object-oriented, enabling adaptability to diverse healthcare facilities and buildings. This attribute makes the model flexible and capable of receiving information about different types of healthcare buildings, according to particular configurations; and
2. The model links the six core issues of strategic healthcare FM. Although the developed modules deal simultaneously with aspects related to maintenance, performance and risk of healthcare facilities, future development will expand to include energy and operations, business management, and development aspects.
The following paragraphs outline the rationale behind selecting four main procedures out of the 15 specified in this research for in-depth analysis, namely the facility coefficient, the projected performance, the Maintenance Efficiency Indicator, and actual risk, drawn from the Reasoning Evaluator and Predictor Interface (Figure 2). The facility coefficient is key for determining projected maintenance and actual maintenance efficiency; and projected performance is associated with the projection of future performance and risk in the facility. Being able to correctly predict maintenance efficiency, future performance and actual risk forms the basis of healthcare FM's contribution to overall organizational efficiency.
Facility Coefficient
The facility coefficient determines projected maintenance and assesses actual maintenance efficiency. This procedure assumes that annual maintenance expenditure is affected by four independent variables: (1) category of environment in which the facility is located (marine vs. in-land); (2) level of occupancy (number of patient-beds per 1,000 sq-m built, with standard occupancy being 10 patient-beds per 1,000 sq-m.); (3) actual age of the buildings in the facility (years since completion of construction); and (4) designation of built areas in the building, such as hospitalization wards, offices, laboratories, clinics, and utility areas (the more complex the building the higher the maintenance demands) (Lavy and Shohet, 2007a). It should also be stressed that this coefficient refers merely to the projected expenditure for maintenance. (1)
The facility coefficient procedure is an economic coefficient used in computing the Annual Maintenance Expenditure, by adjusting a coefficient for each of the surveyed buildings in the facility, and for the entire facility. This economic coefficient expresses the maintenance resources required for implementing a preventive maintenance policy based on the facility's level of occupancy, type of environment, age of buildings, and the components included in the buildings.
As mentioned above, the assumption made in the development of this procedure is that the facility coefficient is affected by the four main variables in the following manner: (1) age of the building dictates the replacement of building components; (2) category of environment (marine or in-land) affects the deterioration of exterior building components, as seen in Table 1; (3) average occupancy level of the facility (defined as the number of patient beds per 1,000 sq-m, where 10 patient-beds per 1,000 sq-m are characterized as standard 100% occupancy) affects the deterioration of interior building components, as seen in Table 1; and (4) the configuration of each building (e.g., hospitalization wards require different building systems and components than warehouses). The model assumes that the type of environment and the level of occupancy variables are statistically independent. Occupancy level affects the life cycle of a component, or its annual maintenance costs, or both--particularly in the case of indoor components that are exposed to intensive or moderate service conditions (Table 1). Marine environment affects the life cycle of a component and its annual maintenance costs, particularly in the case of outdoor components that are exposed to severe environmental conditions (Building Performance Group Ltd., 1999; Construction Audit Ltd., 1999). In addition, each component is assumed to be replaced at the end of its life cycle, unless the residual service life of the building is less than half of the component's Designed Life Cycle. In that case, the component continues to serve the building until the end of the building's life cycle (Allweil, 1989).
The facility coefficient is an adjusting coefficient for the maintenance of the actual facility, compared to a standard hospitalization building
at standard service conditions used as a reference case. The standard service conditions are defined to be in-land environment and standard level of occupancy (100%). The facility coefficient represents an annual snapshot indication--an increase or decrease in the required maintenance resources; it is thus calculated on a yearly basis. A facility coefficient of 1.25, for example, represents an increase of 25% in the annual maintenance resources compared with a standard hospital building, under standard service conditions (occupancy and environment). It does not mean that in general, the cost of maintenance is 25% higher for one type of environment or occupancy level as measured against the standard; however, does indicate that additional resources are required for the particular year for which the coefficient is calculated. The facility coefficient for any building changes during the service life of the building, based on its unique configuration of systems and components. The facility coefficient provides an analytical means for service life planning of facilities; this coefficient can be used to allocate resources to the maintenance of the facility from a long-term service life planning perspective.
The facility coefficient is used in the projection of annual maintenance resources required by healthcare facilities. The coefficient enables the delineation of resources required for replacement and maintenance activities; based on this outline, an annual maintenance plan can be created. This coefficient is also used in the Maintenance Efficiency Indicator to evaluate the actual efficiency with which maintenance activities are implemented. Most assumptions used for developing the facility coefficient procedure are parametric, and as a result, they can be modified and adapted for other types of buildings and situations. The facility coefficient procedure uses the Life-Cycle Costs analysis, and applies it to different environmental and occupancy conditions over a designed life cycle of 75 years (Figure 3 and Appendix B). The figure was produced from simulations of the building's maintenance under six combinations of environmental and occupancy service conditions. Figure 3 depicts that the cumulative effect of marine environment and high occupancy adds up to an increase of 19% in maintenance life cycle costs. Conversely, light service conditions, i.e. low occupancy, lead to a 10% decrease in the cumulative facility coefficient. These findings are explained by statutory regulatory requirements for preventive maintenance of most of the electro-mechanical systems within the building, even under partial occupancy conditions. Comparison of the cumulative coefficient for standard occupancy and marine vs. in-land environment reveals that the effect of marine environments accumulates to only 2.1%. The cumulative effect of high occupancy is found to be as high as 14%.
[FIGURE 3 OMITTED]
Projected Performance Procedure
Projected performance is associated with the projection of future performance and risk in the facility. This procedure projects the performance score for each component and system, used to compute the projected performance indicator for each surveyed building, as well as for the entire facility. This procedure provides a projection of the physical performance score of buildings' components and systems, measured on a 100-point scale, based on their actual physical performance.
The deterioration pattern of each component in the structural system is assumed to be non-linear (Bentur et al., 1997), as found in a field survey conducted during an earlier phase of this research (Equation 1):
y = 124.29 * exp(-0.08139 * [t.sup.0.5289]) 8 [less than or equal to] t [less than or equal to] 63 (1)
This equation represents the deterioration in performance, where y is the projected performance score for year t. The correlation coefficient of this equation was found to be [R.sup.2] = 0.65, representing structural components in an in-land environment, between 8 and 63 years of age. During this period of time, performance decreases exponentially from 97.33 points to 60 points. A similar analysis was conducted for buildings in a marine environment.
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