FabGuard Enterprise

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  • Computer System Requirements

    All the things required by the software to run properly.

  • Computer System Requirements
  • Computer System Requirements
  • Computer System Requirements
  • Computer System Requirements

    All the things required by the software to run properly.

  • 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).

  • 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…

Get Started

  • 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).

  • First Responder Training

    Learn software navigation, data viewing, alarm viewing and clearing, and basic report operations.

Test 2, Bayron’s workaround using excerpts with children display

Release Notes

  • FabGuard v22.06.00

    We are pleased to announce the release of FabGuard v22.06.00. The FabGuard Team has provided significant enhancements to configuration management and data visualization with Control Summary and other improvements.

  • FabGuard v22.03.00

    We are pleased to announce the release of FabGuard v22.03.00. The FabGuard Team has provided significant enhancements to configuration management and data visualization with Control Summary and other improvements.

Code Snippet (Code Block)

SQL
            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.