# Resource-Based Quality Performance Estimation Method for Construction Operations
## 3 Quantitative Quality Performance Estimation System
### System Process
Step 8: The user defines the minimum (\(R_{i}{}^{min}\)) and maximum (\(R_{i}{}^{max}\)) values for each resource input. The simulation clock unit is set to match the simulation time unit with the resource information stored in the datasheet. The simulation time unit can be set in seconds, minutes, and hours. Step 9: The system calculates the total number of simulations (\(ITER\)) by the number (\(SN_{i}\)) of available types (\(S_{i}\)) for each resource (\(i\)) specified in step 7, the range value for each resource (\(R_{i}{}^{min}\) and \(R_{i}{}^{max}\)) set in step 8 using Equation (1). For example, if there are two resources in the simulation model, the possible range of each resource is 1 to 6 and 3 to 20, and the number of available models is 3 and 2, respectively, the system calculates a total simulation iteration (\(ITER\)) of 648. The simulation experiment of [\((6\times 3)\times((20-3+1)\times 2)\)] is executed in the sensitivity analysis module. \[ITER=\sum_{i=1}^{I}\Bigl{(}R_{i}^{max}-R_{i}^{min}+1\Bigr{)}\times SN_{i} \tag{1}\]  
Step 10: The system sets the current simulation iteration \(n\) to 0 and initializes the input resources with the designated resource combinations (number and type of resources) changing for each simulation experiment. After a simulation experiment is finished, the system stores the simulation result data generated from each component. Data, fluctuated by resource flow according to the waiting or work time in each simulation run, is stored in vector format for each modeling component. Step 11: Using the data stored in Step 10, the system calculates the performance of each resource combination (i.e., operation duration, operation cost, and operation quality) is calculated. 1. Operation duration (\(OD_{n}\)) at simulation iteration \(n\) is the same as the system time ended according to the termination rule set in step 6. 2. Operation cost (\(OC_{n}\)) at simulation iteration \(n\) is calculated by Equation (2) using the hourly cost (\(HC_{i}{}^{n}\)), input quantity (\(SN_{i}{}^{n}\)), operation duration (\(OD_{n}\)) of individual resources (\(i\)) at each simulation iteration \(n\) for cyclic resources (i.e., equipment and crew) and input quantity (\(MN_{j}\)), unit quantity per one entity (\(UQ_{j}\)), and unit cost (\(UC_{j}\)) for noncyclic resources (i.e., material). The input quantity of cyclic resource (\(SN_{i}\)) and noncyclic resource (\(MN_{j}\)) is the same number of initialized entity in the simulation system. \[OC_{n}=\sum_{i=1}^{I}(HC_{i}^{n}\times SN_{i}^{n}\times OD_{n})+\sum_{j=1}^{I }\bigl{(}MN_{j}\times UQ_{j}\times UC_{j}\bigr{)}\] (2)
3. Operation quality (\(OQ_{n}\)) at simulation iteration \(n\) is calculated by Equation (3) using the quality weight value (\(W_{i}\)) of the individual resource \(i\) set in step 7, the quality performance index of the resource \(i\) at the \(nth\) simulation (\(Q_{i}{}^{n}\): called from the data sheet). \[OQ_{n}=\sum_{i=1}^{I}(W_{i}\times Q_{i}^{n})\] (3)  
Step 12: The system determines whether the current iteration number of simulation \(n\) has reached the total number of simulation experiment using Equation (4). If it is true, the system proceeds to step 13; otherwise, the system repeats steps 10 and 11. \[n=ITER? \tag{4}\]Figure 1: System process. Step 13: When the sensitivity analysis is completed, the system stores the simulation results (\(OD_{S}\), \(OC_{S}\), and \(OQ_{S}\)) to the matrix, \(SR\) (Simulation Result) for each resource combination. The system identifies the interval values of the simulation results for all resource combinations (\(OD_{min}\), \(OC_{min}\), \(OQ_{min}\), \(OD_{max}\), \(OC_{max}\), and \(OQ_{max}\)). \[\text{SR}=\left| \begin{array}{ccc}OD_{1}&OC_{1}&OQ_{1}\\ OD_{2}&OC_{2}&OQ_{2}\\ \vdots&\vdots&\vdots\\ OD_{S}&OC_{S}&OQ_{S}\end{array} \right| \tag{5}\]  
Step 14: After executing the sensitivity analysis, the user can set it by specifying the limitation(s) of each or all performances (\(OD_{u}\), \(OC_{u}\), \(OQ_{u}\)).