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- FabGuard Concepts
FabGuard is designed for in situ process monitoring and real-time data analysis. FabGuard collects data from both the tool and advanced sensors; performs endpoint detection, fault detection and classification, and metrology prediction; and finally, sends alarms and results to the tool or the host for process interdiction. FabGuard provides a single, integrated environment for advanced process control (APC).
- FabGuard Concepts
FabGuard is designed for in situ process monitoring and real-time data analysis. FabGuard collects data from both the tool and advanced sensors; performs endpoint detection, fault detection and classification, and metrology prediction; and finally, sends alarms and results to the tool or the host for process interdiction. FabGuard provides a single, integrated environment for advanced process control (APC).
- FabGuard Concepts
FabGuard is designed for in situ process monitoring and real-time data analysis. FabGuard collects data from both the tool and advanced sensors; performs endpoint detection, fault detection and classification, and metrology prediction; and finally, sends alarms and results to the tool or the host for process interdiction. FabGuard provides a single, integrated environment for advanced process control (APC).
- Computer System Requirements
All the things required by the software to run properly.
- FabGuard Concepts
FabGuard is designed for in situ process monitoring and real-time data analysis. FabGuard collects data from both the tool and advanced sensors; performs endpoint detection, fault detection and classification, and metrology prediction; and finally, sends alarms and results to the tool or the host for process interdiction. FabGuard provides a single, integrated environment for advanced process control (APC).
Test 2, Bayron’s workaround using excerpts…
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Test 2, Bayron’s workaround using excerpts with children display
Release Notes
Code Snippet (Code Block)
select c.*,
-- Perform the ct for target WIP calculation using the process time, sample rate, usage rate, utilization factor from the queueing model, and multiplier
-- TCT_sec is based on several input factors (e.g. average lot size) whereas proc_sec is just a historical average of what ran
-- MPU starts with the historical throughput, but then adds on cascading factors
-- Proc_sec (not available by eqp_type) is not available from the capacity model tables so if you use the queueing model method you must use tct_sec,
-- which is reasonable given that the queueing model relies on many capacity model inputs anyway
(case when lb_target_basis = 'MPU' then mpu*avg_qty_per_carr_for_uph when lb_target_basis = 'TCT' then tct_sec_eqp_type / 60 else proc_sec_comp_full_wavg / 60 end )
* least(lb_qmodel_max_xfactor, (est_smp_pct/100) * (est_use_pct/100) * decode(lb_target_method, 'QUEUEING MODEL', est_utilization_factor * variation_factor, 1) * target_wip_multiplier) as ct_mins_for_target_wip_final
from
-- Still one row per facility, route, step, eqp_type
(
select b.*,
-- Calculate the queueing model utilization factor, add 1 to always include process time
round(power(est_utilization_ratio_capped, sqrt(2 * (num_cap_ents + 1)) - 1) / (num_cap_ents * (1 - est_utilization_ratio_capped)), 4) as est_utilization_factor
from
-- This subquery results in one row per facility, route, step, eqp_type
-- Eff mins can be summed since est_use_pct is already factored in
(
select a.*,
eqp_type_eff_mins_per_day/eqp_type_avail_mins_per_days as est_utilization_ratio,
-- Capping the est_utilization_ratio avoids cases where demand exceeds capacity which leads to > exponential increases in the target wip
least(eqp_type_eff_mins_per_day/eqp_type_avail_mins_per_days, 0.95) as est_utilization_ratio_capped
from
(
select base.*, cm_rse.eqp_type, nvl(est_use_pct, 100) as est_use_pct, nvl(tct_sec, tct_sec_rrsp) as tct_sec_eqp_type,
nvl(mpu, 0) as mpu, nvl(num_cap_ents, 1) as num_cap_ents, cap_entity_list, nvl(variation_factor, 1) as variation_factor,
round(sum(nvl(eff_mpw, 0)) over (partition by base.facility, cm_rse.eqp_type), 4) as eqp_type_eff_mpw,
round(sum(nvl(eff_mpw, 0) * wip_qty_rt_rsec / greatest(rt_rsec_ct_days, 0.1)) over (partition by base.facility, cm_rse.eqp_type), 4) as eqp_type_eff_mins_per_day,
nvl(num_cap_ents, 1) * 24 * 60 * nvl(plan_util, 100) / 100 as eqp_type_avail_mins_per_days
from base
-- This join introduces a row per eqp_type used at each facility, route, step
left join cm_p_route_step_eqp cm_rse
on base.facility = cm_rse.facility and base.route = cm_rse.route and base.step = cm_rse.step
left join cm_p_eqp_types cm_et
on base.facility = cm_et.facility and cm_rse.eqp_type = cm_et.eqp_type
where is_staging_step = 'N'
) a
) b
) c
join gp_c_facility f
on c.facility = f.facility
join gen_facilities gf
on f.facility = gf.facility
Table
|
Route |
Route_Section |
Common_Step |
Cycle_Time_to_EOL |
Process_Time |
Current_WIP |
Target_WIP (Calculated) |
WIP_Delta (Calculated) |
|---|---|---|---|---|---|---|---|
|
Flow_90_nm |
Trench_1 |
PreOx_Clean |
60 |
40 |
100 |
41 |
59 |
|
Flow_90_nm |
Trench_1 |
Diff_Ox |
59 |
240 |
150 |
243 |
-93 |
|
Flow_90_nm |
Trench_1 |
Photo_Iline |
58 |
40 |
75 |
41 |
34 |
|
Flow_90_nm |
Trench_1 |
Etch |
57 |
30 |
50 |
30 |
20 |
|
Flow_90_nm |
Trench_1 |
Strip |
56 |
20 |
0 |
20 |
-20 |
|
Flow_90_nm |
Trench_2 |
Imp_MC |
55 |
10 |
100 |
22 |
78 |
|
Flow_90_nm |
Trench_2 |
PreNit_Clean |
54 |
60 |
300 |
132 |
168 |
|
Flow_90_nm |
Trench_2 |
Diff_Nit |
53 |
180 |
150 |
396 |
-246 |
Table Full Width
|
Route |
Route_Section |
Common_Step |
Cycle_Time_to_EOL |
Process_Time |
Current_WIP |
Target_WIP (Calculated) |
WIP_Delta (Calculated) |
|---|---|---|---|---|---|---|---|
|
Flow_90_nm |
Trench_1 |
PreOx_Clean |
60 |
40 |
100 |
41 |
59 |
|
Flow_90_nm |
Trench_1 |
Diff_Ox |
59 |
240 |
150 |
243 |
-93 |
|
Flow_90_nm |
Trench_1 |
Photo_Iline |
58 |
40 |
75 |
41 |
34 |
|
Flow_90_nm |
Trench_1 |
Etch |
57 |
30 |
50 |
30 |
20 |
|
Flow_90_nm |
Trench_1 |
Strip |
56 |
20 |
0 |
20 |
-20 |
|
Flow_90_nm |
Trench_2 |
Imp_MC |
55 |
10 |
100 |
22 |
78 |
|
Flow_90_nm |
Trench_2 |
PreNit_Clean |
54 |
60 |
300 |
132 |
168 |
|
Flow_90_nm |
Trench_2 |
Diff_Nit |
53 |
180 |
150 |
396 |
-246 |
LaTex Equations
Reliability
Mean Time Between Failure - Uptime (MTBFu)
Unknown Attachment
Mean uptime between failures: the average equipment system uptime that the equipment was capable of performing its intended function between failures; uptime divided by the number of failures during that time. Only uptime is included in this calculation. Failures that occur coincident with an attempt to change from NST or SDT to an uptime state are included in this calculation. -SEMI E10
|
Level |
Equation |
|---|---|
|
Entity |
We don't have a way to export this macro. |
|
Tool / Cluster |
We don't have a way to export this macro. |
Where:
-
We don't have a way to export this macro. - Represents the time that the entity or tool spent in the Equipment Uptime states including ENG, SBY or PRD state
-
We don't have a way to export this macro. - The count of UDT Episodes (E.G. Entity level failures)
-
We don't have a way to export this macro. - Start of the time period of observation
-
We don't have a way to export this macro. - End of the time period of observation
-
We don't have a way to export this macro. - Entity level logging
-
We don't have a way to export this macro. - Tool level including the contribution-factor* for the entities for each state.
-
We don't have a way to export this macro. - Episodes when the entire tool is in a failure state considering the contribution-factor* of the tools entities.