■ Feature
►Description:
Zircon mullite brick selected high quality mullite sand and zircon powder as its main raw material. Molded by high pressure and sintered by high temperature , the zircon-mullite brick has such advantages as high bulk density, high strength, good thermal shock resistance, high temperature erosion resistance and good slag resistance. It is mainly used in long-life orifice rings, tank bottom, tank superstructure, perfume-bottle feeder, covers for working tanks and soda lime glass.
►Advantages:
1,High strength;
2,Good thermal shock resistance;
3,High temperature erosion resistance;
4,Good slag resistance.
►Applications:
The zircon mullite brick is mainly used in long-life orifice rings, tank bottom, tank superstructure, isostatically pressed, electrode blocks, perfume-bottle feeder, covers for working tanks and soda lime glass, etc.
Zircon mullite brick selected high quality mullite sand and zircon powder as its main raw material. Molded by high pressure and sintered by high temperature , the zircon-mullite brick has such advantages as high bulk density, high strength, good thermal shock resistance, high temperature erosion resistance and good slag resistance. It is mainly used in long-life orifice rings, tank bottom, tank superstructure, perfume-bottle feeder, covers for working tanks and soda lime glass.
►Advantages:
1,High strength;
2,Good thermal shock resistance;
3,High temperature erosion resistance;
4,Good slag resistance.
►Applications:
The zircon mullite brick is mainly used in long-life orifice rings, tank bottom, tank superstructure, isostatically pressed, electrode blocks, perfume-bottle feeder, covers for working tanks and soda lime glass, etc.
■ Technical Data
►Physical and chemical index:
| Item | ZM-17 | ZM-20 (Zirmul) | ZM-25 (Vista) | ZM-30 | ZM-11 | |
| Chemical composition | Al2O3 | ≥70 | ≥59 | ≥57 | ≥47 | ≥72 |
| ZrO2 | ≥17 | ≥19.5 | ≥25.5 | ≥30 | ≥11 | |
| SiO2 | ≤12 | ≤20 | ≤14.5 | ≤20 | ≤12 | |
| Fe2O3 | ≤0.5 | ≤0.5 | ≤0.5 | ≤0.3 | ≤0.5 | |
| Apparent Porosity％ | ≤17 | ≤17 | ≤17 | ≤18 | ≤17 | |
| Bulk Density g/cm3 | ≥3.15 | ≥2.95 | ≥3.15 | ≥3.10 | ≥3.1 | |
| Cold Crushing Strength Mpa | ≥90 | ≥100 | ≥120 | ≥100 | ≥90 | |
| 0.1Mpa Refractoriness Under Load T0.6 ℃ | ≥1650 | ≥1650 | ≥1650 | ≥1650 | ≥1630 | |
| Permanent Linear Change On Reheating（%）1500℃X2h | ±0.3 | ±0.3 | ±0.3 | ±0.3 | ±0.3 | |
| 20-1000℃ Thermal Expansion % (x 10-6) | 0-0.6 | 0-0.6 | 0-0.6 | 0-0.6 | 0-0.6 | |
| Thermal Conductivity (Average800℃) W / (M.K) | ≤ 2.19 | ≤ 2.19 | ≤ 2.1 | ≤ 2.1 | ≤ 2.19 | |
| Pyrometric Cone Equivalent ℃ SK | 31 | 31 | 31 | 31 | 31 | |
■ About Us
development history »
As adaptive case management (ACM) systems mature, we are moving beyond simple systems that allow knowledge workers to define ad hoc processes, to creating more intelligent systems that support and guide them. Knowledge workers still need to dynami-cally add information, define activities and collaborate with others in order to get their work done, but those are now just the table stakes in a world of big data and intelligent agents. To drive innovation and maintain operational efficiencies, we need to augment case work typically seen as relying primarily on human intelligence with machine intelligence. In other words, we need intelligent ACM.
Factory strength »
As adaptive case management (ACM) systems mature, we are moving beyond simple systems that allow knowledge workers to define ad hoc processes, to creating more intelligent systems that support and guide them. Knowledge workers still need to dynami-cally add information, define activities and collaborate with others in order to get their work done, but those are now just the table stakes in a world of big data and intelligent agents. To drive innovation and maintain operational efficiencies, we need to augment case work typically seen as relying primarily on human intelligence with machine intelligence. In other words, we need intelligent ACM.
Highly predictable work is easy to support using traditional programming techniques, while unpredictable work cannot be accurately scripted in advance, and thus requires the involvement of the knowledge workers themselves. The core element of Adaptive Case Management (ACM) is the support for real-time decision-making by knowledge workers.
As adaptive case management (ACM) systems mature, we are moving beyond simple systems that allow knowledge workers to define ad hoc processes, to creating more intelligent systems that support and guide them. Knowledge workers still need to dynami-cally add information, define activities and collaborate with others in order to get their work done, but those are now just the table stakes in a world of big data and intelligent agents. To drive innovation and maintain operational efficiencies, we need to augment case work typically seen as relying primarily on human intelligence with machine intelligence. In other words, we need intelligent ACM.
Factory strength »
As adaptive case management (ACM) systems mature, we are moving beyond simple systems that allow knowledge workers to define ad hoc processes, to creating more intelligent systems that support and guide them. Knowledge workers still need to dynami-cally add information, define activities and collaborate with others in order to get their work done, but those are now just the table stakes in a world of big data and intelligent agents. To drive innovation and maintain operational efficiencies, we need to augment case work typically seen as relying primarily on human intelligence with machine intelligence. In other words, we need intelligent ACM.
Highly predictable work is easy to support using traditional programming techniques, while unpredictable work cannot be accurately scripted in advance, and thus requires the involvement of the knowledge workers themselves. The core element of Adaptive Case Management (ACM) is the support for real-time decision-making by knowledge workers.
