# Modelling Prefabricated Construction Safety
## 3 Results and Discussion
### Injuries in Prefabricated Construction Accidents
#### 3.6.2 Causes of Injuries  
As shown in Figure 11, overall, the most common cause for injury was 'lifting/carrying/strain' with 33%, followed by 'unknown source' (26%), with the rest in ascending order as 'puncture' (13%), 'loss balance/personal control' (11%), 'work property/characteristics' (9%), and 'object coming loose/shifting' (7%). However, in comparison of the weightage of the most common cause of injury from onsite to offsite--referring to Figure 11--it is four times higher for 'unknown source' (27%), three times for 'lifting/carrying/strain' (24%), five times for 'puncture' (16%), four times for 'loss balance/personal control' (12%), five times for 'object coming loose/shifting' (11%), and four times 'work property/characteristics' (10%).  
Figure 12 shows the number of accidents under each cause of injury for PCC. The X-axis represents the years, and the y-axis represents the percentages of occurrence. It seems that the top two known causes are similar in both offsite and onsite construction environments. 'Lifting/carrying/strain' is relatively more significant for Wood_S, Alum, Metal_S, and Wood_P. Most injuries have no clarity around cause for Conc and Metal_P. The least common cause of injury is 'object coming loose/shifting' for Wood_S, Conc, and Alum. However, it is different for Metal_S, with 'loss balance/personal control', and Metal_P, with 'work property/characteristics'. In the last five years, there is a higher fluctuation in accident frequency observed for 'lifting/carrying/strain' and 'puncture'. However, there is a relative decline for 'work property/characteristics' and 'object coming loose/shifting'. Furthermore, there is a slight increasing trend for 'loss balance/personal control' for all types of PCC.  
Injury causes were modelled with simplistic equations to determine the weightage of each cause under each classification. This helps to determine the recurring causes that lead to accidents, and is also helpful for risk assessment for prefab operations.  
\[\text{Injury cause (Wood\_S) = 33 \times Lifting/carrying/strain + 15 \times Puncture + 10 \times Loss balance/personal}\] \[\text{control + 9 \times Work property/characteristics + 8 \times Object coming loose/shifting + 25 \times Others}\] \[\text{Injury cause (Conc) = 22 \times Lifting/carrying/strain + 10 \times Puncture + 13 \times Loss balance/personal}\] \[\text{control + 11 \times Work property/characteristics + 10 \times Object coming loose/shifting + 33 \times Others} \tag{23}\]  
Figure 11: Comparison of number of accidents by most common injury causes (2017–2022).  
In this section, accident frequency is forecast for the injury causes. Table 5 and Figure 13 show the optimized ARIMA models for each injury cause.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Stats**} & \multirow{2}{*}{\begin{tabular}{c} **Lifting/** \\ **Carrying/Strain** \\ \end{tabular} } & \multirow{2}{*}{**Puncture**} & \multirow{2}{*}{\
\begin{tabular}{c} **Object Coming** \\ **Loose/Shifting** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Work Property/** \\ **Characteristics** \\ \end{tabular} } \\ \hline ARIMA Model & 1, 1, 1 & 0, 0, 0 & 0, 0, 0 & 1, 1, 0 \\ \hline MAPE & 3.845 & 17.734 & 11.048 & 5.362 \\ \hline MAE & 18.671 & 50.829 & 18.524 & 10.263 \\ \hline R\({}^{2}\) & 0.565 & 0.408 & 0.750 & 0.802 \\ \hline RMSE & 87.417 & 73.965 & 28.055 & 21.621 \\ \hline BIC & 10.229 & 9.204 & 7.266 & 7.113 \\ \hline \hline \end{tabular}
\end{table}
Table 5: ARIMA models for accident forecasting by injury causes.  
Figure 12: Number of accidents by injury cause in prefabricated construction (2017–2022).  
The main trend is that 'object coming loose/shifting' is declining, but the rest are somehow increasing. Understanding of causes of accidents helps in the identification of safety risks associated to activities involved in PC [24]. Furthermore, workforce awareness of potential causes leading to the accidents can help avoid hazardous situations.