# Resource-Based Quality Performance Estimation Method for Construction Operations
## 2 Status of Quality Estimation and Simulation Methods in Construction Management
### Research Scope  
Preceding studies have emphasized the importance of quantification, measurement, and detailed analysis of construction quality. However, these existing studies do not provide a method for quantitative estimation of construction quality at a detailed level. To overcome these limitations, the Discrete Event Simulation technique-based method is presented to quantitatively estimate the construction quality, which enables us to model and analyze construction process simulation models at a detailed level. This study focuses on applying and calculating the numerical value in the simulation model after the quality performance indicators (i.e., quality weight and score) of each resource are derived. Data  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multicolumn{4}{c}{**Analyzed Performances**} \\ \cline{2-5}  & & **Title** & **Cost** & **Environ.** & **Quality** \\ \hline Floating caissons & \(\bullet\) & Real world applications of construction process simulation & \(\surd\) & - & - & - \\ Steel fabrication & \(\bullet\) & Virtual shop model for experimental planning of steel & \(\surd\) & - & - & - \\ Bridge re-decking & \(\bullet\) & Sensitivity analysis of construction simulation using & & & & \\  & cell-devs and microcyclone & \(\surd\) & \(\surd\) & - & - \\ Pile installation & \(\bullet\) & Stochastic productivity assessment of continuous flight & \(\surd\) & \(\surd\) & - & - \\ Road construction & \(\bullet\) & Exploring the environmental modeling of road construction & & & & \\  & operations using discrete-event simulation & \(\surd\) & - & \(\surd\) & - \\ Crane selection & \(\bullet\) & oductivity and CO\({}_{2}\) emission analysis for tower crane & \(\surd\) & - & \(\surd\) & - \\  & \(\bullet\) & utilization on high-rise building projects & & & & \\  & \(\bullet\) & Importance of operational efficiency to achieve energy & & & & \\ Earth moving & \(\bullet\) & efficiency and exhaust emission reduction of construction & \(\surd\) & \(\surd\) & \(\surd\) & - \\  & \(\bullet\) & Stochastic carbon emission estimation method for & & & & \\  & construction operation & \(\surd\) & \(\surd\) & \(\surd\) & - \\ \hline \hline \end{tabular}
\end{table}
Table 3: Application cases and analyzed performance criteria.  
collection and analysis methods (e.g., big data, deep learning, artificial intelligence, etc.) to derive the quantitative performance indicators of diverse construction resources can be further applied. The methodology was developed to support finding an optimal resource deployment plan by analyzing the impact on the quality performance according to the type of resources deployed to the construction simulation models. By executing sensitivity analysis in the system, construction practitioners can efficiently search for optimal resource combinations considering site constraints and priorities for efficient decision-making. The construction operation's quality performance is estimated by utilizing quality indexes and quality weights assigned to the individual resource (e.g., materials, equipment, laborers, etc.) in the simulation model. The system presents a sensitivity analysis to compare different performance indicators according to various resource combinations during the construction simulation experiments considering duration, cost, and quality performance.