SnT2015 Poster No. T4.1-P02 Failure Mode and Effect ...
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PREPARATORY COMMISSION Disclaimer The views expressed on this poster are those of the author and do not necessarily reflect the view of the CTBTO SnT2015 Poster No. T4.1-P02 Failure Mode and Effect Analysis (FMEA) of the IMS radionuclide stations in the years 2013 and 2014 Bernd Wernsperger , Matthias Auer, Theo Juurlink PTS, IMS Division, Engineering and Development Section, Vienna International Center, A-1400 Vienna Failure Modes in the IMS RADIONUCLIDE PARTICULATE NETWORK Failure mode and effect analysis was carried out for the IMS particulate network from 2013/10/01 to 2014/10/31. In this period 63 radionuclide particulate stations were under certified operation achieving a network data availability of 85.5%. Out of 24760 days of expected data In the considered period the particulate stations suffered from a total downtime of 3598 days. The main contribution to the reduction of data availability results from problems related to station equipment (11.2%). Other downtime categories contribute no more than 1% each to the total downtime (see Figure 1). With regard to station equipment failures the major part of downtime (72.6%) is caused by problems related to the detection system: detector related problems alone reduce the particulate network data availability by 8.7% in the considered period. The second largest contributions to network downtime are created by problems related to station power (reducing the data availability by 0.9%) and by the computer system (data availability reduction by 0.8%). Figure 1: Available and non available data (%) for IMS particulate network 2013/10/01-2014/10/31 Failure Modes in the IMS NOBLE GAS NETWORK – SPALAX Stations In the years 2013 and 2014 the SPALAX noble gas network grew from two to nine certified stations. In a period between 2013/01/01 and 2015/01/31 there were 4965 days of data expected from the SPALAX network. 1311 days of downtime reduced the network data availability by 26.7% whereas the major contribution (23.9%) to downtime results from failures related to the station equipment. Looking at station equipment 46% of downtime is related to the HPGe-detector system and 32.6% to organizational issues with regard to detector replacement (shipping time and quality, setup of new detectors). It is pointed out that with regard to the SPALAX network detector related downtime reflects rather single incidents at single stations with excessively long downtimes than a statistical distribution among many stations. Nevertheless, with regard to the HPGe detection system the same problems like in the radionuclide particulate network are found here and, the same three areas of improvements must be focused on. Data Available 73.7% Sta0on Equipment 23.9% Power Outage 1.7% Planned Ac0vity 0.3% Other 0.5% SPALAX Data Availability 1 Jan 2013 31 Jan 2015; 9 cer<fied SPALAXs 4965 days of data expected Total Down Time: 1311 days Data Available Sta0on Equipment Human Error Power Outage Environment Planned Ac0vity Third Party GCI/ISN Other Air Sampling 4.2% Organisa0onal issues related to detector replacement 32.6% Detec0on System 46.0% Sample Processing System 5.4% Hardware/Control Electronics 9% SoPware 1.7% Sta0on Infrastructure 7.1% Distribu<on of equipment failures causing down <me SPALAX 1 Jan 2013 31 Jan 2015 Total DT by Sta<on equipment failures: 1187 days Air Sampling Organisa0onal issues related to detector replacement Detec0on System Sample Processing System Gas Quan0fica0on System Hardware/Control Electronics SoPware System Power Management Anciliiary Data Acquisi0on System Sta0on Infrastructure Computer, 6.9% Data Flow, 5.2% Detec0on System, 77.8% Filter Management, 1.1% Sta0on Power, 7.8% Sampler, 1.2% Distribu<on of Sta<on Equipment related Failures (%) 1 Oct 2013 31 Oct 2014; 63 sta<ons Total Down<me related to Sta<on Equipment: 2775 days Computer Data Flow Detec0on System Filter Management Sta0on Power Sampler Infrastructure Data available, 85.5% Equipment failure, 11.2% Power outage, 0.4% Planned ac0vity, 0.5% Human error, 0.6% Environment, 1.0% Third party, 0.2% GCI / ISN, 0.2% unspecified, 0.4% Available and non available data (%) 1 Oct 2013 31 Oct 2014; 63 radionuclide sta<ons 24760 days of data expected Total Down <me: 3598 days Data available Equipment failure Power outage Planned ac0vity Human error Environment Third party GCI / ISN unspecified FAILURE MODES OF HPGE-DETECTION SYSTEMS High Purity Germanium detection system are used at IMS particulate stations and by SPALAX noble gas systems. Failure Mode and Effect Analysis of IMS stations in the years 2013 and 2014 has shown that the HPGe detection systems are the most sensitive component of IMS radionuclide stations. Therefore, a specific analysis of failure modes of detection systems was carried out for the operational period 2013/01/01 – 2014/10/31 when 72 IMS detection systems were in certified operation at 63 particulate stations and 9 SPALAX noble gas stations. In this period 101 incidents related to the detection systems and 14 infrastructure related problems caused a total of 115 incidents resulting in detector downtime of 3146 days (out of total 45953 days, i.e. 6.8%). Figure 7 shows the distribution of downtime over the problem categories related to the detection system. Besides equipment related problems it is seen that in the considered period a significant contribution to detector downtime (15%) was added due to delays in detector setup procedures (i.e. issues with calibration, background measurements, data format, communication,…) and by third parties causing additional downtime (24.2%). The latter was related mainly to broken detectors after bad shipments or caused by organizational delays in the provision of detectors by the suppliers. A significant contribution to downtime (18.4%) was identified also by failures of station infrastructure which resulted in broken detection systems. The main reason for infrastructure failures were failing power systems (357 days) and air condition systems (215 days). Vacuum problems (13.0%) and broken preamplifiers (12.8%) still created significant downtimes as these problems required replacement of detectors. Broken FETs (3.9%) occurred rarely. Problems with MCAs and Cooling systems (6.4% each) occurred often, but downtimes were kept low due to the fact that these parts were available as on-site spares. Bascially, due to cost considerations only some selected components of detection system (such as MCA, specific electrical coolers, cooler controllers) are stored as on-site spares at the station. Full back-up detection systems are available only at very few IMS stations, where this is justified by the remoteness of the site. Figures 7a and 7b show the distribution of downtimes and incidents for Ortec detection systems. Here, the main contributions to downtime result from preceding infrastructure failures, delayed setup times and third party delays, as well as from vacuum problems requiring whole detector replacements. Notably, many incidents with MCAs and coolers result in comparably low downtime due to the fact that spare parts were available at the station. Figure 7c and 7d show the respective distributions for Canberra detectors. Again, main contribution to downtime come from the same problem categories (infrastructure, setup times, third party, preamplifier problems requiring full detector replacement). Figure 8 shows the averaged downtime per incident grouped according to the problem categories. It can be seen that breaking components which are stored at the station (cooling equipment, MCAs) result in much less downtime than detector components which require component replacement including shipping procedures. This is also underlined in Table 1 below where the averaged downtime for an incident with an on-site spare part is 7.9 days, whereas an average of 111.8 days of downtime was experienced when spare parts and/or detector had to be shipped to the station. Failure Modes in the IMS NOBLE GAS NETWORK – SAUNA Stations The SAUNA noble gas network consisted of 10 stations throughout the years 2013 to 2014. The SAUNA network reached a data availability of 90.1% from 2013/01/01 to 2015/01/31. SAUNA’s data availability is reduced mainly by failures of Station Equipment (7.0%). The equipment related downtime is distributed equally among different system components. It is pointed out though that downtime of a certain station component (like for example infrastructure) is often driven by single incidents at single stations. Downtime related to certain system components have been already investigated thoroughly with a view to upgrading the system. In fact, improvement of the SAUNA system is already underway by installing upgrades. The upgrade of SAUNA consists of further developed components in the detection system (memory-free beta cells, digital signal processing in the detector electronics), improved sampling traps, new PCs, an improved design of the processing system, replacement of the gas chromatograph, and an sample archiving system extended to 7 days. Furthermore, the motor of the QC-source which sometimes caused downtime is being re-engineered. Data Available 90.1% Sta0on Equipment 7.0% Planned Ac0vity 1.3% GCI/ISN 0.1% Other/Unspecified 1.5% SAUNA Data Availability 1 Jan 2013 31 Jan 2015; 10 SAUNA sta<ons 7194 days of data expected Total Down<me: 715.5 days Data Available Sta0on Equipment Human Error Power Outage Environment Planned Ac0vity Third Party GCI/ISN Other/Unspecified Air Sampling 12.0% Sample Processing System 0.8% Nuclear Detec0on System 14.5% Gas Quan0fica0on System 21.2% Hardware/Control Electronics 2.3% SoPware 11.2% System Power Management 19.5% Sta0on Infrastructure 18.4% Distribu<on of down<me causes related to equipment failures SAUNA 1 Jan 2013 31 Jan 2015; 10 sta<ons Total DT related to Sta<on equipment failures: 507 days Air Sampling Sample Processing System Nuclear Detec0on System Gas Quan0fica0on System Hardware/Control Electronics SoPware System Power Management Anciliiary Data Acquisi0on System Sta0on Infrastructure 0 20 40 60 80 100 120 140 160 180 Averaged Down<me/Incident Total days of detec0on system related Down0me 2567 days Total number of detec0on system reated Incidents 101 Average down0me/incident 25.4 days Total Down0me for incidents requiring spare part shipment 1900 days Number of Incidents requiring spare part shipment 17 Average down0me/Incident requiring spare part shipment 111.8 days Total Down0me for incidents when spare part was onsite 667 days Number of Incidents when spare part was onsite 84 Average down0me/Incident when spare part was onsite 7.9 days Figure 2: Distribution of equipment related downtime for IMS particulate network 2013/10/01-2014/10/31 Figure 3: Data availability and downtime contribution for IMS SPALAX noble gas network 2013/01/01-2015/01/31 Figure 4: Distribution of equipment related downtime for SPALAX noble gas network 2013/01/01-2015/01/31 Figure 5: Data availability and downtime contribution for IMS SAUNA noble gas network 2013/01/01-2015/01/31 Figure 6: Distribution of equipment related downtime for SAUNA noble gas network 2013/01/01-2015/01/31 Figure 7: Distribution of downtime related to HPGe detection system components (2013/01/01-2015/10/31) STRATEGIES FOR IMPROVING DETECTION SYSTEM UPTIME 1. SPARING POLICY: In order to improve the detector supply, more regional depots should be established in order to shorten distances and increase flexibilities of supply. The number of stations having on-site spare detectors could be increased. With regard to on-site spares appropriate quality control and assurance measures must be in place to avoid failing of operating and spare systems at the same time. 2. STREAMLINING AND ENFORCING OF DETECTOR SETUP PROCEDURES: A process of streamlining the detector setup procedure at the PTS is already in place since a short time. Related to this, communication and instructions to the station operators must be enforced and station operator must be following timely. 3. TECHNOLOGY IMPROVEMENT IN COOPERATION WITH SUPPLIERS: Intensified cooperation with detector suppliers to improve detector reliability has started in the second half of 2014. In parallel liquid nitrogen (LN2) cooled detectors are still explored as an option. LN2 generators could be a possibility to make LN2 available independent from third suppliers. Such equipment is tested at the moment. 4. IMPROVED SHIPMENT PROCEDURES: The PTS has started to cooperate with detector suppliers on improvements in this area, specifically the packaging of detection systems will be made even more ruggedized and will be standardized for the IMS network. 5. IMPROVEMENT OF STATION INFRASTRUCTURE: Stable station air conditioning and power systems are a key factor for operation of HPGe detection systems. Failures in the power system and the air conditioning can result in significant downtimes as was seen in the past period. Therefore, engineering projects to improve station power have started already for several stations. With regard to the station air conditioning, a special focus is put on this issue, too, because the quality of the station climate control is directly linked to the detector systems as well. Figure 8: averaged downtime per incident grouped according Detection system problem category Table 1: Comparison of averaged downtimes per incident depending on on-site availability of spare parts. Figure 7a: Downtimes of Ortec detection systems Figure 7b: Incidents causing downtime of Ortec detection systems Figure 7d: Incidents causing downtime of Canberra detection systems Figure 7c: Downtimes of Canberra detection systems Cooling System 5.0% Electronics FET 5.0% Electronics MCA 20.0% Electronics Preamplifier 20.0% Temperature sensor 10.0% Vacuum problem (cryostat, sieves…) 5.0% DT caused by Third Party 15.0% Delayed Detector setup <me 5.0% Infrastructure failure causing detector DT 15.0% Distribu<on of Incidents with down<me of Canberra detector components Cooling System Electronics FET Electronics MCA Electronics Preamplifier Temperature sensor Vacuum problem (cryostat, sieves…) DT caused by Third Party Delayed Detector setup 0me Infrastructure failure causing detector DT Cooling System 0.3% Electronics FET 0.4% Electronics MCA 1.6% Electronics Preamplifier 27.3% Temperature sensor 0.5% Vacuum problem (cryostat, sieves…) 3.4% DT caused by Third Party 43.5% Delayed Detector setup <me 13.3% Infrastructure failure causing detector DT 9.6% Distribu<on of down<me of Canberra detector components Cooling System 26.3% detailed info missing... 2 Electronics FET 3.2% Electronics MCA 45.3% Electronics Preamplifier 3.2% Vacuum problem (cryostat, sieves…) 4.2% DT caused by Third Party 1.1% Delayed Detector setup <me 3.2% Infrastructure failure causing detector DT 11.6% Distribu<on of incidents with down<me of Ortec detector components Cooling System detailed info missing/not documented Electronics FET Electronics MCA Electronics Preamplifier Vacuum problem (cryostat, sieves…) DT caused by Third Party Delayed Detector setup 0me Infrastructure failure causing detector DT Cooling System 9.5% detailed info missing/not documented 10.1% Electronics FET 5.7% Electronics MCA 8.8% Electronics Preamplifier 5.5% Vacuum problem (cryostat, sieves…) 17.9% DT caused by Third Party 7.7% Delayed Detector setup <me 12.1% Infrastructure failure causing detector DT 22.8% Distribu<on of down<me of Ortec detector components Vacuum problem (cryostat, sieves…) 13.0% Cooling System 6.4% Electronics FET 3.9% Electronics MCA 6.4% Electronics Preamplifier 12.8% Temperature sensor 0.2% DT caused by Third Party 24.2% Delayed Detector setup <me 12.5% detailed info missing/not documented 6.7% Infrastructure failure causing detector DT 18.4% Distribu<on of down<me related to problems with the HPGedetec<on system Affected system components in the period 2013/01/01 2014/10/31 Total down<me related to detec<on systems: 3146 days (115 incidents) Vacuum problem (cryostat, sieves…) Cooling System Getechnology (leakage current) Electronics Cooler controller Electronics FET Electronics High Voltage Electronics HV filter Electronics MCA Electronics Preamplifier Temperature sensor Mechanical issue (contact…) DT caused by Third Party Delayed Detector setup 0me Other Human error (window broken, mistreatment…) detailed info missing/not documented Infrastructure failure causing detector DT
Transcript of SnT2015 Poster No. T4.1-P02 Failure Mode and Effect ...
P R E PA R ATO RY CO M M I S S I O N DisclaimerThe views expressed on this poster are those of the author and do not necessarily reflect the view of the CTBTO
SnT2015 Poster No. T4.1-P02 Failure Mode and Effect Analysis (FMEA) of the IMS radionuclide stations in the years 2013 and 2014Bernd Wernsperger , Matthias Auer, Theo JuurlinkPTS, IMS Division, Engineering and Development Section, Vienna International Center, A-1400 Vienna
Failure Modes in the
IMS RADIONUCLIDE PARTICULATE NETWORK Failure mode and effect analysis was carried out for the IMS particulate network from 2013/10/01 to 2014/10/31. In this period 63 radionuclide particulate stations were under certified operation achieving a network data availability of 85.5%. Out of 24760 days of expected data In the considered period the particulate stations suffered from a total downtime of 3598 days. The main contribution to the reduction of data availability results from problems related to station equipment (11.2%). Other downtime categories contribute no more than 1% each to the total downtime (see Figure 1). With regard to station equipment failures the major part of downtime (72.6%) is caused by problems related to the detection system: detector related problems alone reduce the particulate network data availability by 8.7% in the considered period. The second largest contributions to network downtime are created by problems related to station power (reducing the data availability by 0.9%) and by the computer system (data availability reduction by 0.8%).
Figure 1: Available and non available data (%) for IMS particulate network 2013/10/01-2014/10/31
Failure Modes in the
IMS NOBLE GAS NETWORK – SPALAX Stations
In the years 2013 and 2014 the SPALAX noble gas network grew from two to nine certified stations. In a period between 2013/01/01 and 2015/01/31 there were 4965 days of data expected from the SPALAX network. 1311 days of downtime reduced the network data availability by 26.7% whereas the major contribution (23.9%) to downtime results from failures related to the station equipment. Looking at station equipment 46% of downtime is related to the HPGe-detector system and 32.6% to organizational issues with regard to detector replacement (shipping time and quality, setup of new detectors). It is pointed out that with regard to the SPALAX network detector related downtime reflects rather single incidents at single stations with excessively long downtimes than a statistical distribution among many stations. Nevertheless, with regard to the HPGe detection system the same problems like in the radionuclide particulate network are found here and, the same three areas of improvements must be focused on.
Data Available 73.7%
Sta0on Equipment 23.9%
Power Outage 1.7%
Planned Ac0vity 0.3%
Other 0.5%
SPALAX Data Availability 1 Jan 2013 -‐ 31 Jan 2015; 9 cer<fied SPALAXs 4965 days of data expected Total Down Time: 1311 days Data Available
Sta0on Equipment
Human Error
Power Outage
Environment
Planned Ac0vity
Third Party
GCI/ISN
Other
Air Sampling 4.2%
Organisa0onal issues related to detector
replacement 32.6%
Detec0on System 46.0%
Sample Processing System 5.4%
Hardware/Control Electronics
9%
SoPware 1.7%
Sta0on Infrastructure 7.1%
Distribu<on of equipment failures causing down <me -‐ SPALAX 1 Jan 2013 -‐ 31 Jan 2015 Total DT by Sta<on equipment failures: 1187 days
Air Sampling
Organisa0onal issues related to detector replacement Detec0on System
Sample Processing System
Gas Quan0fica0on System
Hardware/Control Electronics
SoPware
System Power Management
Anciliiary Data Acquisi0on System
Sta0on Infrastructure
Computer, 6.9%
Data Flow, 5.2%
Detec0on System, 77.8%
Filter Management, 1.1% Sta0on Power,
7.8% Sampler, 1.2%
Distribu<on of Sta<on Equipment related Failures (%) 1 Oct 2013 -‐ 31 Oct 2014; 63 sta<ons Total Down<me related to Sta<on Equipment: 2775 days Computer
Data Flow
Detec0on System Filter Management Sta0on Power
Sampler
Infrastructure
Data available, 85.5%
Equipment failure, 11.2%
Power outage, 0.4%
Planned ac0vity, 0.5% Human error, 0.6% Environment, 1.0%
Third party, 0.2%
GCI / ISN, 0.2%
unspecified, 0.4%
Available and non available data (%) 1 Oct 2013 -‐ 31 Oct 2014; 63 radionuclide sta<ons 24760 days of data expected Total Down <me: 3598 days
Data available
Equipment failure
Power outage
Planned ac0vity
Human error
Environment
Third party
GCI / ISN
unspecified
FAILURE MODES OF HPGE-DETECTION SYSTEMSHigh Purity Germanium detection system are used at IMS particulate stations and by SPALAX noble gas systems. Failure Mode and Effect Analysis of IMS stations in the years 2013 and 2014 has shown that the HPGe detection systems are the most sensitive component of IMS radionuclide stations. Therefore, a specific analysis of failure modes of detection systems was carried out for the operational period 2013/01/01 – 2014/10/31 when 72 IMS detection systems were in certified operation at 63 particulate stations and 9 SPALAX noble gas stations. In this period 101 incidents related to the detection systems and 14 infrastructure related problems caused a total of 115 incidents resulting in detector downtime of 3146 days (out of total 45953 days, i.e. 6.8%).
Figure 7 shows the distribution of downtime over the problem categories related to the detection system. Besides equipment related problems it is seen that in the considered period a significant contribution to detector downtime (15%) was added due to delays in detector setup procedures (i.e. issues with calibration, background measurements, data format, communication,…) and by third parties causing additional downtime (24.2%). The latter was related mainly to broken detectors after bad shipments or caused by organizational delays in the provision of detectors by the suppliers. A significant contribution to downtime (18.4%) was identified also by failures of station infrastructure which resulted in broken detection systems. The main reason for infrastructure failures were failing power systems (357 days) and air condition systems (215 days). Vacuum problems (13.0%) and broken preamplifiers (12.8%) still created significant downtimes as these problems required replacement of detectors. Broken FETs (3.9%) occurred rarely. Problems with MCAs and Cooling systems (6.4% each) occurred often, but downtimes were kept low due to the fact that these parts were available as on-site spares. Bascially, due to cost considerations only some selected components of detection system (such as MCA, specific electrical coolers, cooler controllers) are stored as on-site spares at the station. Full back-up detection systems are available only at very few IMS stations, where this is justified by the remoteness of the site. Figures 7a and 7b show the distribution of downtimes and incidents for Ortec detection systems. Here, the main contributions to downtime result from preceding infrastructure failures, delayed setup times and third party delays, as well as from vacuum problems requiring whole detector replacements. Notably, many incidents with MCAs and coolers result in comparably low downtime due to the fact that spare parts were available at the station.Figure 7c and 7d show the respective distributions for Canberra detectors. Again, main contribution to downtime come from the same problem categories (infrastructure, setup times, third party, preamplifier problems requiring full detector replacement).
Figure 8 shows the averaged downtime per incident grouped according to the problem categories. It can be seen that breaking components which are stored at the station (cooling equipment, MCAs) result in much less downtime than detector components which require component replacement including shipping procedures. This is also underlined in Table 1 below where the averaged downtime for an incident with an on-site spare part is 7.9 days, whereas an average of 111.8 days of downtime was experienced when spare parts and/or detector had to be shipped to the station.
Failure Modes in the
IMS NOBLE GAS NETWORK – SAUNA Stations
The SAUNA noble gas network consisted of 10 stations throughout the years 2013 to 2014. The SAUNA network reached a data availability of 90.1% from 2013/01/01 to 2015/01/31. SAUNA’s data availability is reduced mainly by failures of Station Equipment (7.0%). The equipment related downtime is distributed equally among different system components. It is pointed out though that downtime of a certain station component (like for example infrastructure) is often driven by single incidents at single stations. Downtime related to certain system components have been already investigated thoroughly with a view to upgrading the system. In fact, improvement of the SAUNA system is already underway by installing upgrades. The upgrade of SAUNA consists of further developed components in the detection system (memory-free beta cells, digital signal processing in the detector electronics), improved sampling traps, new PCs, an improved design of the processing system, replacement of the gas chromatograph, and an sample archiving system extended to 7 days. Furthermore, the motor of the QC-source which sometimes caused downtime is being re-engineered.
Data Available 90.1%
Sta0on Equipment 7.0%
Planned Ac0vity 1.3%
GCI/ISN 0.1%
Other/Unspecified 1.5%
SAUNA Data Availability 1 Jan 2013 -‐ 31 Jan 2015; 10 SAUNA sta<ons 7194 days of data expected Total Down<me: 715.5 days
Data Available
Sta0on Equipment
Human Error
Power Outage
Environment
Planned Ac0vity
Third Party
GCI/ISN
Other/Unspecified
Air Sampling 12.0%
Sample Processing System 0.8% Nuclear Detec0on System
14.5%
Gas Quan0fica0on System 21.2%
Hardware/Control Electronics
2.3%
SoPware 11.2%
System Power Management
19.5%
Sta0on Infrastructure 18.4%
Distribu<on of down<me causes related to equipment failures -‐ SAUNA 1 Jan 2013 -‐ 31 Jan 2015; 10 sta<ons Total DT related to Sta<on equipment failures: 507 days
Air Sampling
Sample Processing System
Nuclear Detec0on System
Gas Quan0fica0on System
Hardware/Control Electronics
SoPware
System Power Management
Anciliiary Data Acquisi0on System
Sta0on Infrastructure
0 20 40 60 80
100 120 140 160 180
Averaged Down<me/Incident
Total days of detec0on system related Down0me 2567 days Total number of detec0on system reated Incidents 101
Average down0me/incident 25.4 days Total Down0me for incidents requiring spare part shipment 1900 days
Number of Incidents requiring spare part shipment 17 Average down0me/Incident requiring spare part shipment 111.8 days Total Down0me for incidents when spare part was on-‐site 667 days
Number of Incidents when spare part was on-‐site 84 Average down0me/Incident when spare part was onsite 7.9 days
Figure 2: Distribution of equipment related downtimefor IMS particulate network 2013/10/01-2014/10/31
Figure 3: Data availability and downtime contributionfor IMS SPALAX noble gas network 2013/01/01-2015/01/31
Figure 4: Distribution of equipment related downtimefor SPALAX noble gas network 2013/01/01-2015/01/31
Figure 5: Data availability and downtime contributionfor IMS SAUNA noble gas network 2013/01/01-2015/01/31
Figure 6: Distribution of equipment related downtimefor SAUNA noble gas network 2013/01/01-2015/01/31
Figure 7: Distribution of downtime related to HPGe detection system components (2013/01/01-2015/10/31)
STRATEGIES FOR IMPROVING DETECTION SYSTEM UPTIME
1. SPARING POLICY: In order to improve the detector supply, more regional depots should be established in order to shorten distances and increase flexibilities of supply. The number of stations having on-site spare detectors could be increased. With regard to on-site spares appropriate quality control and assurance measures must be in place to avoid failing of operating and spare systems at the same time.
2. STREAMLINING AND ENFORCING OF DETECTOR SETUP PROCEDURES:A process of streamlining the detector setup procedure at the PTS is already in place since a short time. Related to this, communication and instructions to the station operators must be enforced and station operator must be following timely.
3. TECHNOLOGY IMPROVEMENT IN COOPERATION WITH SUPPLIERS:Intensified cooperation with detector suppliers to improve detector reliability has started in the second half of 2014. In parallel liquid nitrogen (LN2) cooled detectors are still explored as an option. LN2 generators could be a possibility to make LN2 available independent from third suppliers. Such equipment is tested at the moment.
4. IMPROVED SHIPMENT PROCEDURES:The PTS has started to cooperate with detector suppliers on improvements in this area, specifically the packaging of detection systems will be made even more ruggedized and will be standardized for the IMS network.
5. IMPROVEMENT OF STATION INFRASTRUCTURE:Stable station air conditioning and power systems are a key factor for operation of HPGe detection systems. Failures in the power system and the air conditioning can result in significant downtimes as was seen in the past period. Therefore, engineering projects to improve station power have started already for several stations. With regard to the station air conditioning, a special focus is put on this issue, too, because the quality of the station climate control is directly linked to the detector systems as well.
Figure 8: averaged downtime per incident grouped accordingDetection system problem category
Table 1: Comparison of averaged downtimes per incidentdepending on on-site availability of spare parts.
Figure 7a: Downtimes of Ortec detection systems Figure 7b: Incidents causing downtime of Ortec detection systems
Figure 7d: Incidents causing downtime of Canberra detection systemsFigure 7c: Downtimes of Canberra detection systems
Cooling System 5.0%
Electronics -‐ FET 5.0%
Electronics -‐ MCA 20.0%
Electronics -‐ Preamplifier
20.0%
Temperature sensor 10.0%
Vacuum problem (cryostat, sieves…)
5.0%
DT caused by Third Party 15.0%
Delayed Detector setup <me
5.0%
Infrastructure failure causing detector DT
15.0%
Distribu<on of Incidents with down<me of Canberra detector components Cooling System
Electronics -‐ FET
Electronics -‐ MCA
Electronics -‐ Preamplifier
Temperature sensor
Vacuum problem (cryostat, sieves…) DT caused by Third Party
Delayed Detector setup 0me
Infrastructure failure causing detector DT
Cooling System 0.3%
Electronics -‐ FET 0.4%
Electronics -‐ MCA 1.6%
Electronics -‐ Preamplifier
27.3%
Temperature sensor 0.5%
Vacuum problem (cryostat, sieves…) 3.4%
DT caused by Third Party
43.5% Delayed Detector
setup <me 13.3%
Infrastructure failure causing detector DT
9.6%
Distribu<on of down<me of Canberra detector components
Cooling System 26.3%
detailed info missing...
2
Electronics -‐ FET 3.2%
Electronics -‐ MCA 45.3%
Electronics -‐ Preamplifier
3.2%
Vacuum problem (cryostat, sieves…)
4.2%
DT caused by Third Party 1.1%
Delayed Detector setup <me
3.2%
Infrastructure failure causing detector DT
11.6%
Distribu<on of incidents with down<me of Ortec detector components
Cooling System
detailed info missing/not documented
Electronics -‐ FET
Electronics -‐ MCA
Electronics -‐ Preamplifier
Vacuum problem (cryostat, sieves…)
DT caused by Third Party
Delayed Detector setup 0me
Infrastructure failure causing detector DT
Cooling System 9.5%
detailed info missing/not documented
10.1%
Electronics -‐ FET 5.7%
Electronics -‐ MCA 8.8%
Electronics -‐ Preamplifier
5.5%
Vacuum problem (cryostat, sieves…)
17.9%
DT caused by Third Party
7.7%
Delayed Detector setup <me 12.1%
Infrastructure failure causing detector DT
22.8%
Distribu<on of down<me of Ortec detector components
Vacuum problem (cryostat, sieves…) 13.0%
Cooling System 6.4% Electronics -‐ FET
3.9% Electronics -‐ MCA
6.4%
Electronics -‐ Preamplifier 12.8%
Temperature sensor 0.2%
DT caused by Third Party 24.2%
Delayed Detector setup <me 12.5%
detailed info missing/not documented
6.7%
Infrastructure failure causing detector DT
18.4%
Distribu<on of down<me related to problems with the HPGe-‐detec<on system Affected system components in the period 2013/01/01 -‐ 2014/10/31 Total down<me related to detec<on systems: 3146 days (115 incidents)
Vacuum problem (cryostat, sieves…)
Cooling System
Ge-‐technology (leakage current)
Electronics -‐ Cooler controller
Electronics -‐ FET
Electronics -‐ High Voltage
Electronics -‐ HV filter
Electronics -‐ MCA
Electronics -‐ Preamplifier
Temperature sensor
Mechanical issue (contact…)
DT caused by Third Party
Delayed Detector setup 0me
Other
Human error (window broken, mistreatment…)
detailed info missing/not documented
Infrastructure failure causing detector DT
