# Developing a Recommendation Model for the Smart Factory System
## 4 Result of SFS Development
### Constructing Prototype Indicator
\begin{table}
\begin{tabular}{c c} \hline \hline
**Sub-Dimension** & **Indicators** \\ \hline Prediction & SFS can automatically predict the relevant production demand information (e.g., time consumption, ingredients, cost, and expected sales revenue) based on past sales data. \\ \hline Purchasing & SFS can automatically analyze the best ingredient suppliers based on their price and quality. \\ \hline Production & SFS can automatically schedule. \\ \cline{2-3}  & SFS can automatically control ingredients use. \\ \cline{2-3}  & SFS can automatically contact the supplier to order ingredients when running short. \\ \cline{2-3}  & SFS can automatically generate manufacturing progress reports. \\ \hline Quality & SFS can automatically inspect and record the product’s quality (including semi-finished and finished products) in real-time. \\ \cline{2-3}  & SFS can automatically generate quality control reports. \\ \hline Putting In & SFS can automatically deliver finished products to the warehouse. \\ \cline{2-3}  & SFS can perform specific processes depending on product properties (e.g., finished products need to be stored in a warehouse below 0 \({}^{\circ}\)C). \\ \hline Inventory & SFS can keep up with real-time inventory situation. \\ \cline{2-3}  & SFS automatically manages inventory to zero inventory requirements. \\ \hline  & SFS can instantly update all object information (e.g., purchase receipt, ingredients picking and warehousing information) by scanning (e.g., RFID, NFC and barcode) and synchronize data to the Cloud Management System. \\ \cline{2-3}  & SFS can automatically generate reports (such as prediction reports, purchase reports, schedule reports, production progress reports, quality control reports, warehousing reports, maintenance record reports and abnormality record reports) \\ \cline{2-3}  & SFS can immediately display production information and status on dashboards, screens and mobile devices. \\ \cline{2-3} Common & SFS can instantly display machine productivity and production load. \\ \cline{2-3} Functionality & SFS can automatically calculate the best combination of different operating machines to achieve optimal productivity, best quality, and lowest cost. \\ \cline{2-3}  & SFS can record any machine events (e.g., abnormal event records, malfunction records, and regular maintenance records. \\ \cline{2-3}  & SFS can automatically detect machine malfunction and ask for repair. \\ \cline{2-3}  & SFS automatically issues periodic maintenance requests. \\ \cline{2-3}  & SFS has abnormality self-troubleshooting mechanism. \\ \cline{2-3}  & SFS can detect any source of danger and immediately issue an alert (e.g., fire, flood, and earthquake). \\ \cline{2-3}  & SFS automatically analyzes the best business decision-making information. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Sub-dimensions and indicators of SFS function characteristics. On Perceived Risk, this study takes Performance, Psychological, Social, Time, Physical, and Financial Risks; a total of 6 Perceived Risk recommendation indicators make up our SFS recommendation. On UI Design, it takes Efficiency, Memorability, Learnability, Satisfaction and Errors; there are a total of 5 UI Design recommendation indicators that make up our SFS recommendation.