# Smart Manufacturing Application in Precision Manufacturing
## 3 Results
The map is also divided into four sections. The \"Loss\" section on the bottom left indicates the area where both machines' availability and machines' utilization were low, defined by figures less than 45%. This section is associated with high losses in the factory due to a major breakdown, for example, production line breakdown as a result of an electric fault. The \"Downtime\" section on the bottom right is the area where machines' availability was high (>45%), and the machines' utilization was low (<45%). This section is associated with low productivity due to high downtime. The \"Resilience\" section on the top left is the area where machines' availability was low (<45%), and the machines' utilization was high (>45%). This section is associated with flexibility and agility due to high productivity despite the low availability of resources such as production orders and labor resources. The \"Growth\" section on the top right is the area where machines were highly available, and the machines' utilization was also high (both >45%). This section is associated with growth due to the high productivity and highly availability of production orders, labor resources, etc. The first two quarters of 2020, January to March and April to June, were both in the middle regions of the \"Downtime\" section of the map. The last two quarters of 2022, July to September and October to December, showed a significant shift towards the border lines of the \"Loss\" section and the \"Resilience\" section of the map. In 2021, all four quarters were in the \"Resilience\" section of the map at the bottom area towards the \"Growth\" borderline. The last two quarters of 2022, July to September and October to December, were in the \"Growth\" section of the map. Figure 9a shows a bar-line graph of the cost savings associated with downtime (i.e., lost productivity) for a total period of four years of actual data from 2019 to 2022 and two further  
predicted years of 2023 and 2024. The graph shows three bars for each year. The efficiency lost costs is the actual total time lost compared to the time set for the production order in its routing. The indirect time lost is the total unscheduled time lost due to non-production-related tasks. The rework time is the time is the time taken to rectify an initially non-conforming product. The associated cost was calculated based on the machining time cost rate, which was set to 60 GBP/h by the factory. For the purpose of this paper's analysis, it was assumed that the machining cost rate remained constant throughout the period analyzed. Figure 9: Productivity, financial, and environmental performance across six-year period (2019–2024): (**a**) total cost of downtime; (**b**) total GHG emissions. Figure 9a also shows a line plot of the total downtime (efficiency lost + indirect time + rework) over the same period. In the year 2019, which was the base year, the total downtime was around GBP 800 K; this reduced significantly to GBP 500 K in 2020 and to GBP 340 K and GBP 380 K for 2021 and 2022, respectively. It was also predicted that the total downtime will be reduced by 12.5% in 2023 to GBP 330 K and further reduce by 6.25% in 2024 to GBP 310 K.  
Figure 9b shows a bar-line graph of the environmental sustainability performance associated with the energy reduction and emissions for a total period of four years, from 2019 to 2022, and two predicted years, 2023 and 2024. The emissions' reduction was calculated based on the GHG emissions in tons of carbon dioxide equivalent (CO2e). It is a KPI that measures the level of environmental emissions that affect the climate such as carbon dioxide (CO2) emissions, which is the dominant one, but other GHGs also include methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6) and nitrogen trifluoride (NF3).