# Smart Manufacturing Application in Precision Manufacturing
## 3 Results
Figure 8a shows a bar graph of the machines' condition mode rate (Equation (1)), which is the ratio of the different machine conditions' mode time against the machines' availability time per month (Equation (2)) for a total of sixteen CNC machines for a period of three years (February 2020 to December 2022). The four machine condition modes status are \"Running\", \"Setup\", \"Idle\" and \"Alarm\". Running and Setup modes occur when the machines are in production, i.e., the machine is either cutting steel or its tools are being setup to perform the required scheduled job. The Idle and Alarm modes status occur when the machines are not in production, i.e., the machine is stopped due to unscheduled downtime or breakdown. The machine availability is the total machines available time calculated based on the total number of days per month the machines in the factory were available for production during the factory opening hours (including day and night shifts) and had production orders scheduled with labor resources to operate the machines. The graph also shows a plot of the machine use rate (Equation (3)), which is the ratio of the machines' time in production mode (Running + Setup) against the total machine availability time. \[\text{Machine Condition Mode Rate}=\sum\left(\frac{\text{Machine Condition Mode}}{\text{Machine Availability}}\right) \tag{1}\]  
\[\text{Machine Availability (per month)}\] \[=\sum((\text{No. of days machines available for production}) \tag{2}\] \[\times(\text{No. of machines available for production})\] \[\times(\text{Factory opening hours per day}))\](3)  
(4)  
Figure 8: Productivity of the CNC machines in the factory over a period of three years (February 2020–December 2022): **(a)** machine condition status; **(b)** productivity map. Figure 8a also shows a line plot of a three-month moving average of the machines' utilization. The machines' utilization rate in 2020 was 37.5% on average. In the first half of the year in 2020, February to June, the machine used rate was the lowest in the full three-year period, with M = 30% (SD = 6%). This was due to the combination of a high non-production mode (Idle) status and a low production mode (Running) status. In the second half of 2020, July to December, the machine use rate had increased with M = 45% (SD = 6%), which was due to a drop in the non-production mode (Idle) status, alongside an increase in the production modes (running and setup) status. In 2021, the machines' utilization rate continued to rise to 52.5% on average. In the first half of 2021, January to June, the machines' utilization rate increased, with M = 51% (SD = 2.4%) but with reduced variance compared to that in 2020. In the second half of 2021, July to December, the machines' utilization rate further increased with M = 54% (SD = 2.4%) whilst maintaining a low variance. In the first half of 2022, the historic machine condition data were not available to be used for the purposes of this study because the data for that period were lost and not saved during a database migration. Historical data availability is crucial for performance analysis and predictive analytics studies; therefore, data storage maintenance is important as big data grow. This is a common challenge faced by SMEs; hence, a dedicated IT team or a cloud database management solution can mitigate such risks. For the remaining half of 2022, July to December, the machines' utilization rate mean further increased to 56% (SD = 2.8%) with a relatively low variance. The data also showed that the production mode (Running) occurred than the non-production mode (Idle) status for the later period of 2022. To look at the improvements made to the machines' utilization rate overtime from another prospective, it was mapped against the machines' availability time. Figure 8b shows a scatter plot productivity map of the machines' utilization rate (Equation (3)) averaged over a three-month period against the machines' availability (Equation (2)) for the full three-year period from February 2020 to December 2022.