CASE07 · Manufacturing · Sintering furnaces
Prioritizing efficient sintering furnaces under matched production profiles
Historical glass-sintering data were normalized by the main sintering profiles. Reassigning production to better-performing furnaces was simulated while keeping loading and process conditions comparable.
01 · CASE ANALYSIS
Operating challenge
Energy intensity depends on sintering duration, loading, good-product yield and furnace performance. The study focused on changing operating priority without equipment modifications.
Different products and profiles can obscure equipment differences. The analysis first selected the most frequent process-duration groups before ranking furnaces.
02 · CASE ANALYSIS
Data and simulation method
The source contained 324 days of operation. After excluding abnormal energy and loading records, 118 small-furnace runs and 733 large-furnace runs remained. Main profiles were 151/154 hours for small furnaces and 110/112/114 hours for large furnaces.
UPI was electricity divided by loaded mass. Within the selected profiles, loaded mass showed no clear correlation with electricity per run, so mean kWh/run was used to rank furnaces. Production counts were then assigned preferentially to better-ranked equipment while holding average duration, mass and loading comparable.
| Indicator | Definition or condition |
|---|---|
| UPI | Electricity (kWh) / loaded mass (kg) |
| Equipment ranking | Mean electricity per sintering run within the selected profile |
| Scenario energy | Sum of ranked-furnace mean kWh/run × allocated run count |
03 · CASE ANALYSIS
Modeled operating scenarios
The small- and large-furnace scenarios were evaluated separately and then combined. The source reports 101,145 kWh of modeled savings over the analyzed records, worth approximately KRW 10.92 million at the historical electricity price.
Applying the combined 3.1% rate to approximately 8,015,930 kWh/year gives about 248,494 kWh/year and a maximum estimated KRW 26.83 million/year. These are annualized estimates under ideal scheduling conditions.
04 · CASE ANALYSIS
Measurement and verification
Actual scheduling must respect product profiles, furnace availability, production commitments and quality. Compare electricity and UPI under equivalent profiles before and after changing operating priority.
The reported rates are simulation results from historical data, not post-improvement metered savings. Real scheduling constraints may reduce the achievable financial benefit.
| Boundary | Historical energy / UPI | Scenario energy / UPI | Saving |
|---|---|---|---|
| Small furnaces | 286,527 kWh; 27.99 kWh/kg | 264,191 kWh; 25.81 kWh/kg | 7.8% |
| Large furnaces | 2,983,691 kWh; 11.59 kWh/kg | 2,904,881 kWh; 11.28 kWh/kg | 2.6% |
| Combined | 3,270,218 kWh; 12.22 kWh/kg | 3,169,073 kWh; 11.84 kWh/kg | 3.1% |
05 · CASE ANALYSIS
Engineering lesson
Matched-profile comparison is essential before using equipment rankings. A lower-energy run caused by a different recipe does not establish better furnace performance.
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