98 silica bricks is a new type silica bricks with high quality for glass kiln which was developed on the basis of 97 silica brick technologies.
Because of a calcium silicon phase (CaO·SiO2), formed by SiO2 and CaO, the study found that calcium silicon phase (CaO·SiO2) in the silica brick is the major cause of silica brick erosion, this combination is vulnerable to erosion of alkaline substances such as NaOH. The reaction between Calcium silicon phase and NaOH will form glass phase in silica bricks, and will slowly dissolve SiO2 particles.
98 silica bricks ensures high temperature strength, at the same time, improves the SiO2 content and reduces the content of CaO, which makes the products with further improved erosion resistance, especially in the daily output of the larger modern glass kiln, the effect is more apparent. The production technology is stable and the products has the best performance.
|
superior silica bricks for glass kiln |
BG-97 |
BG-98 |
|
|
SiO2 ≥ |
97 |
98 |
|
|
Fe2O3 ≤ |
0.8 |
0.8 |
|
|
|
0.4 |
0.35 |
|
|
|
1685 |
1690 |
|
|
|
22 |
22 |
|
|
Cold crushing strength(MPa) |
Unit weight＜20kg ≥ |
35 |
35 |
|
Unit weight ≥ 20kg ≥
|
30 |
30 |
|
|
|
2.34 |
2.34 |
|
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.
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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.
