Description
Developing turnaround strategies to minimize the life cycle costs in a refinery A case study on SINOPECs Refinery of the catalytic cracking units.
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
Tel: +44(0) 161 918 6790 www.proaimltd.com |Registered in England and Wales with Company Number 7969647
1
Developing turnaround strategies to minimize the life cycle
costs in a refinery: A case study on SINOPEC’s Refinery of
the catalytic cracking units
Developing turnaround strategies to minimize the life cycle costs in a refinery: A case study on
SINOPEC’s Refinery of the catalytic cracking units ................................................................................. 2
Introduction ............................................................................................................................................ 2
Fundamental Analysis ............................................................................................................................. 5
Analysis and Application of RAM ............................................................................................................ 6
Process simulation .............................................................................................................................. 6
Development and Evaluation of Key Performance Indicators (KPI) for Turnaround extension ..... 8
Equipment ranking for risk/ loss evaluation ................................................................................... 9
Process Evaluation .............................................................................................................................. 9
Spare Parts Optimization .................................................................................................................. 11
Conclusion ............................................................................................................................................. 12
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
Tel: +44(0) 161 918 6790 www.proaimltd.com |Registered in England and Wales with Company Number 7969647
2
Developing turnaround strategies to minimize the life cycle costs in a
refinery: A case study on SINOPEC’s Refinery of the catalytic cracking
units
Optimizing the turnaround strategies has a significant impact on the life cycle cost of assets. However,
developing such strategies are often complex for an integrated system such as a refinery where there are a large
number of assets with different designed life and operational and failure characteristics integrated to form the
complex whole. In addition, altering the existing strategies might give rise to new criticalities in the system that
increases the risk of implementing such strategies. This case study exemplifies the use of ProAIM’s holistic
approach based on reliability engineering principles coupled with simulation methods to develop turnaround
strategies in one of the biggest refineries in China. Reviewing the existing system identified gaps in maintenance
management and opportunities to improve profitability by means of altering the turnaround strategies. As a result,
firstly, a number of Key Performance Indicators (KPIs) were developed to assist the monitoring of the system to
improve maintenance management. However, to develop turnaround strategies it was imperative to predict the
risks and losses associated with an alternative turnaround interval or any other perturbation. ProAIM’s reliability
software RAM-Int was used for RAM simulation and to predict the performance of the system with an extended
turnaround. The analysis recommended extending the existing turnaround interval by one year to maximize the
profitability with minimal risks. To further complement the turnaround, other strategies were developed including
spare parts strategy and cost-effective retrofit options involving redundancies. Results from the whole analysis
suggested that the refinery operators could save more than £1.6 million per year for the entire refinery complex.
Software Used – RAM-int by ProAIM Ltd
Introduction
Sinopec’s case study company is an integrated oil refining and petrochemical company with crude oil processing
capacity of 5 million TPA. The case study company has more than 30 sets of refining and petrochemical
production units, which produce more than 50 kinds of products including gasoline, kerosene, diesel, chemical
light oil, lubricating base oil, etc.
ProAIM provide specialist and bespoke consultancy, software and training solutions in the area of reliability and
maintenance engineering to enable asset integration and management for our clients in asset centric industries,
particularly in process industries including upstream oil and gas and petrochemical sectors.
ProAIM has been assigned by Sinopec to conduct RAM studies on the catalytic cracking unit at the Case study
Refinery consisting of around 300 static and dynamic equipments. ProAIM has previously conducted RAM
studies for similar industries in the UK and RAM studies for chemical companies and refining companies in
Japan amongst others and has unrivalled expertise in the area of RAM technology. This is accomplished with
the help of ProAIM’s unique software RAM-int.
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
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Figure 1 – Schematic diagram of 1.4 million ton/year crude oil catalytic cracking process unit at the Refinery (Source:
Milton Beychok, Wikipedia; since the actual flow diagram cannot be published due to confidentiality issues)
Figure 1 illustrates the crude oil catalytic cracking process unit at the refinery. The process is similar to any other
catalytic cracking where high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils to
more valuable gasoline, olefenic gases, and other products. The process consists of units such as motors,
compressors, boilers, energy recovery units, turbines and fans amongst others as described in the Figure 1.
The main objectives of the reliability analysis are as follows,
? Build a failure data bank for the refinery
? Evaluate the system RAM performance and identify the maintenance management gap
? Verify the advantages of long-term operation (4 year) as opposed to the current operation of 3 years in
terms of turnarounds.
? Identify the potential risk/loss with new TA interval
? Recommend actions to eliminate the risk/losses
? Find out the bottleneck units affecting system RAM performance
? Make recommendation to those critical units
? Optimize the spares parts stock strategies in the system
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In order to accomplish the above objectives the following approach illustrated in Figure 2 is employed. The
project started with collection of data from the refinery. These could be failure and repair data, maintenance
records, Process Flow diagrams(PFDs) etc. additionally discussion with process engineers, reliability engineers
and maintenance engineers are carried out so as to obtain more information about plant operations. The first
five blocks (steps) constituting the Fundamental analysis in Figure 2 provides the basic data for the RAM analysis
that included RBD model establishment, Historical data collection and Data Regression. These are explained in
the next section. The rest of the blocks (steps) in Figure 2 constitute the Analysis and Application of RAM. These
steps help in the simulation and evaluation of the process and enables engineers to make decisions and
strategies for improving the performance of the Cracking Unit.
Collect PFD, Failure Data from
the refinery , Discussion with
Engineers etc.
Prepare the Reliability Block
Diagram – Impact of each item
on system reliability
Agree how historical data will
be used - interpretation
Data regression and failure
mode analysis
Develop the full RAM model
(RBD)
Simulate the full RAM model
for the production logic
Check results against what
actually happens on the plant
– reality check
Identification of factors that
negatively affect the plant
operation such as bottlenecks
Assessing existing
Turnaround scheme and
evaluating new scheme
Retrofit Recommendation,
Spare Parts Optimization
Risk/ Loss evaluation &
propose actions for mitigation
Final Presentation and Report
Development of KPIs
Identify Maintenance
Management Gap
Scenario based/ Sensitivity
Studies
Figure 2 – Steps involved in the RAM analysis of Refinery Project
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Fundamental Analysis
Fundamental Analysis provides basic data for the RAM study. These include RBD model establishment,
Historical data collection and Data Regression. Reliability Block Diagrams (RBDs) describe the logic relationship
between failures of equipment and the equipment units. It also describes the logic relationship between
equipment and system failure. RBD is set-up from based on process flow sheet diagram (PFD) in the process
industries. In order to develop the RBD discussion are held between RAM engineers and process engineers in
the refinery. The RBD also includes common failures and conditional events.
Common
Failures
Reaction and
Regeneration
CO Boiler
Energy
Recovery
Air
Compressor
Fractionator
Absorption &
Stabilization
Gasoline
Deodorization
Desulphurization
Figure 3 - High level RBD of Refinery - Parallel lines indicates Conditional Events
Figure 3 illustrates the high level RBD of the Refinery’s Catalytic cracking unit.
Other steps involved in the fundamental analysis include historical data collection and analysis and data
regression. For the historical data collection, ProAIM provided the data format to the client which helped them in
collecting maintenance data from static and rotating equipment. The data contained shut-down date,
maintenance start and end dates, maintenance type, downtime, failure mode, failure cause and maintenance
action details amongst others. The historical data was collected from 78 static units and 50 rotating units in this
study.
Following the data collection, the data are then regressed using ProAIM’s RAM-int software. The failure and
repair data of equipment were fitted with probability distribution. For instance for failures Weibull and normal
distributions were employed, however for repairs normal and lognormal distributions were employed. For units
without failure and repair data empirical values estimated from process engineers were used. In addition public
databanks were also used.
The data obtained are then used in the RBD model created in for simulating and evaluating the performance of
the system at different levels, availability throughput. Analysis can be carried out at system level, subsystem level
unit level equipment level or failure mode/cause level. In addition to the maintenance and repair data economic
data regarding plant shutdown and failure were provided by the client. These were calculated based on the cost
of raw material, water and electrical utilities. Some information provided by the client are provide (some
information may be redacted).
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1. Planned downtime: 30 days.
2. Profit loss of planned shutdown: XXXXX? /day, RMB
3. Profit loss of unplanned shut down: XXXXM? /day, RMB
4. Profit loss of reduced throughput: percentage reduced* XXXXM? /day, RMB.
5. Profit loss of degraded products: XXXX ? /t, RMB.
6. Increased electricity consumption due to the standby unit of main blower: XXXXk ? /day, RMB.
7. Profit loss of the shut-down of the desulfurization unit: XXXXXk/d, RMB.
Above information is vital in analysing the performance of the system in optimizing strategies.
Analysis and Application of RAM
This stage of the project follows the fundamental analysis. By this stage the RBD of the system is established,
historical data collection has been undertaken and failure and repair distribution of each unit have been obtained.
The next step then is to simulate the process.
Process simulation
This step simulates the RAM performance of the catalytic cracking unit. The simulation model is based on the
RBD that was created at the fundamental analysis stage, Failure and Repair parameters obtained from the data
regressions stage and, financial information provided by the client. The inputs and some of the outputs that can
be obtained from the simulation model are given in Figure 4. Process simulation is the basis for further system
evaluation and optimization.
Catalytic Cracking
unit
Simulation Model
RBD of Cracking Unit
Failure and Repair
Parameters
Financial Information
From client
Annual Cost, Profit,
Production loss
Usage of Capacity,
Throughput profile
Bottleneck Units
Top Critical Units
Reliability, availability and
annual average downtime
Figure 4 – Input and Output of the simulation model
In the high level RBD, nine units in the catalytic cracking unit are considered. These include common failures,
reaction and regeneration system, CO boiler system, Energy recovery system, Air compressor system,
Fractionator system, Absorption and Stabilization system, deodorization system and desulphurization system.
The high level RBD of the units are depicted in Figure 5. Each unit represents a sub-RBD, all nine sub-RBDs are
on equipment level (as illustrated in Figure 6), A new block (unit) is added in the RBD called ‘common failures’ to
represent failures due to instrument-air, steam, electricity and water utilities. Any failure of these might result in
the system failure. However for this refinery no failures were recorded due to instrument air, steam and water
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
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utilities except for electricity failures. A critical electricity failure happens once every two years and the vital
equipment units in the process need to be shut down for 2 hours without production.
There are a few conditional events in the RBD; this is a unique feature of RAM-int. For instance, if the failure of
the compressor lasts less than 24 hours, the system throughput will decrease from 160 ton/ hour to 90 ton/ hour
and all of the gas products (dry gas, natural gas) will be flared. This condition can be modelled using the
conditional event in RAM-int. Another example of conditional event in the RBD is the gasoline deodorization and
desulphurization unit. 15 % of the gasoline products will be processed in this unit. If this unit fails, the gasoline will
be transported to the off-spec tank. When the desulphurization unit fails, the product will be transported to the
Sulphuric process for purification. The RBD also shows the use of import and export features in RAM-int.
Figure 5 - High Level simulation model of the Refinery Catalytic Cracking unit created in Ram-Int.
Figure 6 – Sub-RBD of the Reaction and Regeneration system.
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From the high level RBD, individual RBDs for each of the 9 units are developed. These are integrated to obtain
the final RBD of the system. Once the RBD of the system is established it is simulated and evaluated to obtain
the performance of the system. Figure 6 shows the RBD for the Reaction and regeneration System.
Development and Evaluation of Key Performance Indicators (KPI) for Turnaround
extension
A number of KPIs have been developed for the refinery. The results for different KPIs have been evaluated for
different scenarios. Calculating the KPI provided insights into the performance of the system with varying
turnaround duration. For instance the case study refinery conducted turnaround at an interval of three years.
When the operating period increases from 3 to 4 years, even though the failure rate increases at a small amount,
it can create risks for the process, operation and maintenance employees. This needed to be evaluated with
simulation against the KPIs at system levels as illustrated in Table 1. The KPIs are chosen in such a way to
compare the performance of the system with 3 and 4 year interval for turnaround. For instance, achievable
availability between turnarounds measures the availability of the system between turnarounds without including
the turnaround duration. As can be seen from the table the achieved availability decreases only slightly (0.03%).
The usage of capacity (based on the actual throughput of the system) is decreased by a small amount by the
extension of the Turnaround. However, KPIs such as total profit loss shows that the profit loss is decreased by
the increase in the turnaround extension; pointing out positive responses to the extension in Maintenance.
Similarly, other advantages in extending the Turnaround are apparent from the Table and it helps in making a
decision at system level.
Table 1 – Key performance Indicators at the system level
Turnaround Duration
KPI 3-year
period
4-year
period Achievable availability between turnarounds 0.9996 0.9993
Usage of capacity 98.85% 98.82%
Reliability at the end of operation period (considering common failure) 0.7396 0.6595
Reliability at the end of operation period (excluding common failure) 0.9983 0.9839
No of system shut-downs within an operation period 0.6149 0.8194
Unplanned downtime (h/y 3.7901 5.6511
Planned downtime?h/y? 240 180
Profit loss of unplanned downtime (10k ? /a, RMB) 2845 2937
Profit loss of planned downtime (10k ? /a, RMB) 6778 5084
Total downtime (h/a) 243.79 185.65
Total profit loss (10k ? /a, RMB) 9624 8021
Reduction of the total downtime standard 23.8%
Reduction of the total profit loss standard 16.7%
Similarly, simulation is carried out for each sub systems. These results also helped in the comparing the
performance of the system on changing the turnaround period from 3 year to 4 year. For instance, the simulation
results for reaction and regeneration system is illustrated in Table 2. It can be seen from Table 2 that availability
and reliability of reaction and regeneration system is varied significantly. However, similar simulations on power
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recovery units, air compressors, CO boilers, fractionator units, absorption and stabilization and desulphurization
units did not show much variation the values.
Table 2 - Simulation for reaction and regeneration system
3-year period 4-year period
Availability of unit in the period 0.9996 0.9994
Reliability of unit at the end-of-period 0.9983 0.9550
No of shut-downs in the period 0.5431 0.7389
unplanned downtime?h/a? 10.86 22.68
Equipment ranking for risk/ loss evaluation
Based on the process simulation the equipment are ranked based on a number of criteria such as the impact on
availability, financial loss, reason causing reduced load etc. to evaluate the risks and losses. For instance, top
critical unit according to the inherent availability for the entire lifecycle are slide valves, whereas for three or four
years of simulation it is axial compressors. Similarly, lists of critical items have been identified for various time
periods in the life cycle of the assets. This helps in identifying the new risks in the system as a result of changing
turnaround interval. To reduce the identified new risks, cost effective maintenance strategies are recommended,
and the potential risks/losses are lowered down by tailored maintenance solution. Similarly in regards to financial
losses, for the entire life cycle slide valves are again the top contributes.
Process Evaluation
In this section scenario based analyses are carried out. Detailed analysis based on the simulation results are
carried out. These involve identifying the best maintenance strategy, identifying the best retrofit option and
operational strategy among others to improve the reliability, availability, maintainability and productivity of the
system.
During the first phase of evaluation, it was identified that economic losses could be reduced by changing the
operation period from three years to four years; thus, the annual profits could be increased with about 16 million
RMB, i.e. 64 million RMB for four years in total. (Excluding the savings from the maintenance cost).
A few of the suggestions following the process evaluation include,
1. Extension of turnaround from 3 year to 4 year.
2. Enhance monitoring ion residual heat boilers during daily operation
3. Based on cost analysis detailed inspection of equipment during overhaul
4. Retrofit option for residual heat boilers, slide valves, steam turbines, pumps etc. with payback period
5. Suggestions during overhaul for static equipment
A number of retrofit options were recommend, for instance for the residual heat boiler. The residual heat boiler
accounted for 12.7% of the system loss. Failure of one boiler causes 30% decrease in the load while failure of
two boilers leads to the shutdown of the system. In this scenario, Table 3 suggests the recommended retrofit
options. In Table 3, three scenarios are evaluated for the new standby boilers. Since the MTBF of the new
standby system is not known, a value lower than the current MTBF value is provided in the simulation to assess
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the different scenarios. It can be seen from Table 3 that profit growth is higher (and hence low pay back period)
when the standby system retrofitted has the lowest MTBF (1 year).
Table 3 - Retrofit option for boilers. Current scenario and two cases of the new standby boiler with lower MTBF are
illustrated along with the payback period.
Scenario
Current 1 2
MTBF of residual heat boiler?year? 2.8 1.5 1
Unplanned economy loss (10k/a) No standby 2937 3268 3624
With standby 2557 2564 2572
System productivity (Practical
production/ designing production)
No standby 98.85% 98.16% 98.01%
With standby 98.97% 98.45% 98.45%
Profit growth (10k/a, RMB? 380 705 1052
Payback period (Retrofit fee: 10 million, RMB? 3.5 year 1.5 year 1 year
Another critical item identified was the slide valves, regarding their maintenance a sensitivity analysis was
carried out as shown in Table 4. From Table 4 it can be seen that a 100% repair of the slide valves can improve
the system productivity and cause no profit reduction. Therefore, in order to reduce the risks/ losses, it was
recommended that during turnaround period, the slide valves maintenance scheme should be changed from only
maintaining 4 out 6 to maintaining 6 out of 6.
Table 4 - Effect of Repair percentage of slide valves on the system performance
Analysis 1 Analysis 2 Analysis 3
Repair percentage Repair100% Repair95% Repair90%
Failure probability of slide valves 0.0015 0.0082 0.0359
Economy loss from slide valves (10k/a) 41 249 1090
Unplanned economy loss (10k/a) 2937 3145 3987
System productivity (Practical
production/designing production) 98.82% 98.74% 98.40%
Profit reduction (10k/a) -- 208 1050
Similar analysis was carried out for all the critical items identified in the refinery. A detailed description of the
analysis carried out for all the equipment is beyond the scope of this report.
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A few Suggestions for overhaul on Static equipment based on process evaluation
? Residual heat boiler - in terms of new boilers, ensure the quality of purchase, installation and inspection.
The failure, leakage that has a low MTBF needs to be inspected and a CBM system shall be
implemented during overhaul. .
? Slide valves - ensure the maintenance quality, return to the factory for maintenance as much as possible
for an as god as new maintenance. Carry out maintenance for all the 6 slide valves rather than the
current scheme of 4 out of 6.
? 1st stage regenerator – RCA are preferred for the incidents occurred.
? Load/unloading ports of 1st stage regenerator – In the event of another occurrence, preventive
maintenance or replacement need to be considered during each overhaul.
? Cyclones in the regenerator - replace according to its design life, to ensure the installation qualities of
accessory components such as wing valve.
? Stripper-ensure the installation qualities of nozzle or other accessory components to the highest.
? Butterfly valve and gate valve - ensure maintenance quality.
? Lines-replacement of expansion joints and other frequently failed parts should be conducted according
on the designing life-span.
? 3 stage cyclone- focus shall be on frequent failure parts
Spare Parts Optimization
Spares parts can be critical for one component or multi equipment. RAM-int is used to obtain the solution to
which spare parts to purchase when, and how many. The solution is optimized by considering the spare parts
purchasing options, delivery options, storage options, the corresponding costs and the failures of the spares parts
on one component or multiple components. This provides the optimal spare parts management to minimize the
process life cycle cost.
For the refinery it was noted that the same items installed in different unit has different failure profile. Hence while
developing spare strategy for such items it was imperative to consider this aspect into it. For the analysis, data
collected include Failure and repair parameters, Penalty costs, purchase costs, depreciation costs and delivery
time. Using the information collected simulation is carried out. Sample results obtained from the simulation are
given in Table 5. The suggested cost reduction is given in the table as a result of adopting the new policy.
Table 5 - Results from Spare parts optimization analysis. By keeping the suggested maximum storage cost reduction can
be achieved.
Spare Type Number of
installations
on working
machines
Current Maximum
storage
Suggested
maximum
storage
Cost
reduction
Seal YG6YWN8 1(1) 1 2 77.0%
Seal YG6SIC 1(1) 1 2 54.9%
Seal DBM90 1(1) In common use 2 94.1%
Seal DTM85B-2 2(1) 2 4 94.4%
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Seal DTM95 1(1) 1 2 92.3%
Seal VBBA40 1(1) In common use 2 87.7%
Seal VJB90-1 2(1) 2 4 82.5%
Bearing 3313 1(1) In common use 2 88.4%
Bearing6217 2(2) In common use 2 23.3%
Bearing6218 1(1) In common use 2 94.9%
Bearing7307BECBM 2(1) In common use 2 --%
Bearing7312 2(1) In common use 4 36.8%
Bearing7314 4(2) In common use 2 --%
Bearing7317 2(1) In common use 4 57.8%
BearingNU307 1(1) In common use 1 --%
BearingNU312 1(1) In common use 2 68.6%
BearingNU313 2(1) In common use 4 49.8%
Conclusion
This report demonstrates how turnaround interval extension is carried out in a refinery. It was shown that
extending the turnaround from 3 years to 4 years could bring savings to the refinery. The risks in extending the
turnaround have been identified in terms of financial loss, availability variation and reduction in load. To further
complement the extended turnaround, other strategies were developed including spare parts strategy and cost-
effective retrofit options consisting of redundancies. Retrofit options using redundancies for boilers, slide valves,
compressors etc. were proposed. Results from the whole analysis suggested that the refinery operators could
save more than £1.6 million per year for the entire refinery complex.
doc_645050437.pdf
Developing turnaround strategies to minimize the life cycle costs in a refinery A case study on SINOPECs Refinery of the catalytic cracking units.
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
Tel: +44(0) 161 918 6790 www.proaimltd.com |Registered in England and Wales with Company Number 7969647
1
Developing turnaround strategies to minimize the life cycle
costs in a refinery: A case study on SINOPEC’s Refinery of
the catalytic cracking units
Developing turnaround strategies to minimize the life cycle costs in a refinery: A case study on
SINOPEC’s Refinery of the catalytic cracking units ................................................................................. 2
Introduction ............................................................................................................................................ 2
Fundamental Analysis ............................................................................................................................. 5
Analysis and Application of RAM ............................................................................................................ 6
Process simulation .............................................................................................................................. 6
Development and Evaluation of Key Performance Indicators (KPI) for Turnaround extension ..... 8
Equipment ranking for risk/ loss evaluation ................................................................................... 9
Process Evaluation .............................................................................................................................. 9
Spare Parts Optimization .................................................................................................................. 11
Conclusion ............................................................................................................................................. 12
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
Tel: +44(0) 161 918 6790 www.proaimltd.com |Registered in England and Wales with Company Number 7969647
2
Developing turnaround strategies to minimize the life cycle costs in a
refinery: A case study on SINOPEC’s Refinery of the catalytic cracking
units
Optimizing the turnaround strategies has a significant impact on the life cycle cost of assets. However,
developing such strategies are often complex for an integrated system such as a refinery where there are a large
number of assets with different designed life and operational and failure characteristics integrated to form the
complex whole. In addition, altering the existing strategies might give rise to new criticalities in the system that
increases the risk of implementing such strategies. This case study exemplifies the use of ProAIM’s holistic
approach based on reliability engineering principles coupled with simulation methods to develop turnaround
strategies in one of the biggest refineries in China. Reviewing the existing system identified gaps in maintenance
management and opportunities to improve profitability by means of altering the turnaround strategies. As a result,
firstly, a number of Key Performance Indicators (KPIs) were developed to assist the monitoring of the system to
improve maintenance management. However, to develop turnaround strategies it was imperative to predict the
risks and losses associated with an alternative turnaround interval or any other perturbation. ProAIM’s reliability
software RAM-Int was used for RAM simulation and to predict the performance of the system with an extended
turnaround. The analysis recommended extending the existing turnaround interval by one year to maximize the
profitability with minimal risks. To further complement the turnaround, other strategies were developed including
spare parts strategy and cost-effective retrofit options involving redundancies. Results from the whole analysis
suggested that the refinery operators could save more than £1.6 million per year for the entire refinery complex.
Software Used – RAM-int by ProAIM Ltd
Introduction
Sinopec’s case study company is an integrated oil refining and petrochemical company with crude oil processing
capacity of 5 million TPA. The case study company has more than 30 sets of refining and petrochemical
production units, which produce more than 50 kinds of products including gasoline, kerosene, diesel, chemical
light oil, lubricating base oil, etc.
ProAIM provide specialist and bespoke consultancy, software and training solutions in the area of reliability and
maintenance engineering to enable asset integration and management for our clients in asset centric industries,
particularly in process industries including upstream oil and gas and petrochemical sectors.
ProAIM has been assigned by Sinopec to conduct RAM studies on the catalytic cracking unit at the Case study
Refinery consisting of around 300 static and dynamic equipments. ProAIM has previously conducted RAM
studies for similar industries in the UK and RAM studies for chemical companies and refining companies in
Japan amongst others and has unrivalled expertise in the area of RAM technology. This is accomplished with
the help of ProAIM’s unique software RAM-int.
Process Asset Integration and Management Limited (ProAIM), One Central Park, Northampton Road, Manchester, M40 5BP, UK.
Tel: +44(0) 161 918 6790 www.proaimltd.com |Registered in England and Wales with Company Number 7969647
3
Figure 1 – Schematic diagram of 1.4 million ton/year crude oil catalytic cracking process unit at the Refinery (Source:
Milton Beychok, Wikipedia; since the actual flow diagram cannot be published due to confidentiality issues)
Figure 1 illustrates the crude oil catalytic cracking process unit at the refinery. The process is similar to any other
catalytic cracking where high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils to
more valuable gasoline, olefenic gases, and other products. The process consists of units such as motors,
compressors, boilers, energy recovery units, turbines and fans amongst others as described in the Figure 1.
The main objectives of the reliability analysis are as follows,
? Build a failure data bank for the refinery
? Evaluate the system RAM performance and identify the maintenance management gap
? Verify the advantages of long-term operation (4 year) as opposed to the current operation of 3 years in
terms of turnarounds.
? Identify the potential risk/loss with new TA interval
? Recommend actions to eliminate the risk/losses
? Find out the bottleneck units affecting system RAM performance
? Make recommendation to those critical units
? Optimize the spares parts stock strategies in the system
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In order to accomplish the above objectives the following approach illustrated in Figure 2 is employed. The
project started with collection of data from the refinery. These could be failure and repair data, maintenance
records, Process Flow diagrams(PFDs) etc. additionally discussion with process engineers, reliability engineers
and maintenance engineers are carried out so as to obtain more information about plant operations. The first
five blocks (steps) constituting the Fundamental analysis in Figure 2 provides the basic data for the RAM analysis
that included RBD model establishment, Historical data collection and Data Regression. These are explained in
the next section. The rest of the blocks (steps) in Figure 2 constitute the Analysis and Application of RAM. These
steps help in the simulation and evaluation of the process and enables engineers to make decisions and
strategies for improving the performance of the Cracking Unit.
Collect PFD, Failure Data from
the refinery , Discussion with
Engineers etc.
Prepare the Reliability Block
Diagram – Impact of each item
on system reliability
Agree how historical data will
be used - interpretation
Data regression and failure
mode analysis
Develop the full RAM model
(RBD)
Simulate the full RAM model
for the production logic
Check results against what
actually happens on the plant
– reality check
Identification of factors that
negatively affect the plant
operation such as bottlenecks
Assessing existing
Turnaround scheme and
evaluating new scheme
Retrofit Recommendation,
Spare Parts Optimization
Risk/ Loss evaluation &
propose actions for mitigation
Final Presentation and Report
Development of KPIs
Identify Maintenance
Management Gap
Scenario based/ Sensitivity
Studies
Figure 2 – Steps involved in the RAM analysis of Refinery Project
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Fundamental Analysis
Fundamental Analysis provides basic data for the RAM study. These include RBD model establishment,
Historical data collection and Data Regression. Reliability Block Diagrams (RBDs) describe the logic relationship
between failures of equipment and the equipment units. It also describes the logic relationship between
equipment and system failure. RBD is set-up from based on process flow sheet diagram (PFD) in the process
industries. In order to develop the RBD discussion are held between RAM engineers and process engineers in
the refinery. The RBD also includes common failures and conditional events.
Common
Failures
Reaction and
Regeneration
CO Boiler
Energy
Recovery
Air
Compressor
Fractionator
Absorption &
Stabilization
Gasoline
Deodorization
Desulphurization
Figure 3 - High level RBD of Refinery - Parallel lines indicates Conditional Events
Figure 3 illustrates the high level RBD of the Refinery’s Catalytic cracking unit.
Other steps involved in the fundamental analysis include historical data collection and analysis and data
regression. For the historical data collection, ProAIM provided the data format to the client which helped them in
collecting maintenance data from static and rotating equipment. The data contained shut-down date,
maintenance start and end dates, maintenance type, downtime, failure mode, failure cause and maintenance
action details amongst others. The historical data was collected from 78 static units and 50 rotating units in this
study.
Following the data collection, the data are then regressed using ProAIM’s RAM-int software. The failure and
repair data of equipment were fitted with probability distribution. For instance for failures Weibull and normal
distributions were employed, however for repairs normal and lognormal distributions were employed. For units
without failure and repair data empirical values estimated from process engineers were used. In addition public
databanks were also used.
The data obtained are then used in the RBD model created in for simulating and evaluating the performance of
the system at different levels, availability throughput. Analysis can be carried out at system level, subsystem level
unit level equipment level or failure mode/cause level. In addition to the maintenance and repair data economic
data regarding plant shutdown and failure were provided by the client. These were calculated based on the cost
of raw material, water and electrical utilities. Some information provided by the client are provide (some
information may be redacted).
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1. Planned downtime: 30 days.
2. Profit loss of planned shutdown: XXXXX? /day, RMB
3. Profit loss of unplanned shut down: XXXXM? /day, RMB
4. Profit loss of reduced throughput: percentage reduced* XXXXM? /day, RMB.
5. Profit loss of degraded products: XXXX ? /t, RMB.
6. Increased electricity consumption due to the standby unit of main blower: XXXXk ? /day, RMB.
7. Profit loss of the shut-down of the desulfurization unit: XXXXXk/d, RMB.
Above information is vital in analysing the performance of the system in optimizing strategies.
Analysis and Application of RAM
This stage of the project follows the fundamental analysis. By this stage the RBD of the system is established,
historical data collection has been undertaken and failure and repair distribution of each unit have been obtained.
The next step then is to simulate the process.
Process simulation
This step simulates the RAM performance of the catalytic cracking unit. The simulation model is based on the
RBD that was created at the fundamental analysis stage, Failure and Repair parameters obtained from the data
regressions stage and, financial information provided by the client. The inputs and some of the outputs that can
be obtained from the simulation model are given in Figure 4. Process simulation is the basis for further system
evaluation and optimization.
Catalytic Cracking
unit
Simulation Model
RBD of Cracking Unit
Failure and Repair
Parameters
Financial Information
From client
Annual Cost, Profit,
Production loss
Usage of Capacity,
Throughput profile
Bottleneck Units
Top Critical Units
Reliability, availability and
annual average downtime
Figure 4 – Input and Output of the simulation model
In the high level RBD, nine units in the catalytic cracking unit are considered. These include common failures,
reaction and regeneration system, CO boiler system, Energy recovery system, Air compressor system,
Fractionator system, Absorption and Stabilization system, deodorization system and desulphurization system.
The high level RBD of the units are depicted in Figure 5. Each unit represents a sub-RBD, all nine sub-RBDs are
on equipment level (as illustrated in Figure 6), A new block (unit) is added in the RBD called ‘common failures’ to
represent failures due to instrument-air, steam, electricity and water utilities. Any failure of these might result in
the system failure. However for this refinery no failures were recorded due to instrument air, steam and water
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utilities except for electricity failures. A critical electricity failure happens once every two years and the vital
equipment units in the process need to be shut down for 2 hours without production.
There are a few conditional events in the RBD; this is a unique feature of RAM-int. For instance, if the failure of
the compressor lasts less than 24 hours, the system throughput will decrease from 160 ton/ hour to 90 ton/ hour
and all of the gas products (dry gas, natural gas) will be flared. This condition can be modelled using the
conditional event in RAM-int. Another example of conditional event in the RBD is the gasoline deodorization and
desulphurization unit. 15 % of the gasoline products will be processed in this unit. If this unit fails, the gasoline will
be transported to the off-spec tank. When the desulphurization unit fails, the product will be transported to the
Sulphuric process for purification. The RBD also shows the use of import and export features in RAM-int.
Figure 5 - High Level simulation model of the Refinery Catalytic Cracking unit created in Ram-Int.
Figure 6 – Sub-RBD of the Reaction and Regeneration system.
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From the high level RBD, individual RBDs for each of the 9 units are developed. These are integrated to obtain
the final RBD of the system. Once the RBD of the system is established it is simulated and evaluated to obtain
the performance of the system. Figure 6 shows the RBD for the Reaction and regeneration System.
Development and Evaluation of Key Performance Indicators (KPI) for Turnaround
extension
A number of KPIs have been developed for the refinery. The results for different KPIs have been evaluated for
different scenarios. Calculating the KPI provided insights into the performance of the system with varying
turnaround duration. For instance the case study refinery conducted turnaround at an interval of three years.
When the operating period increases from 3 to 4 years, even though the failure rate increases at a small amount,
it can create risks for the process, operation and maintenance employees. This needed to be evaluated with
simulation against the KPIs at system levels as illustrated in Table 1. The KPIs are chosen in such a way to
compare the performance of the system with 3 and 4 year interval for turnaround. For instance, achievable
availability between turnarounds measures the availability of the system between turnarounds without including
the turnaround duration. As can be seen from the table the achieved availability decreases only slightly (0.03%).
The usage of capacity (based on the actual throughput of the system) is decreased by a small amount by the
extension of the Turnaround. However, KPIs such as total profit loss shows that the profit loss is decreased by
the increase in the turnaround extension; pointing out positive responses to the extension in Maintenance.
Similarly, other advantages in extending the Turnaround are apparent from the Table and it helps in making a
decision at system level.
Table 1 – Key performance Indicators at the system level
Turnaround Duration
KPI 3-year
period
4-year
period Achievable availability between turnarounds 0.9996 0.9993
Usage of capacity 98.85% 98.82%
Reliability at the end of operation period (considering common failure) 0.7396 0.6595
Reliability at the end of operation period (excluding common failure) 0.9983 0.9839
No of system shut-downs within an operation period 0.6149 0.8194
Unplanned downtime (h/y 3.7901 5.6511
Planned downtime?h/y? 240 180
Profit loss of unplanned downtime (10k ? /a, RMB) 2845 2937
Profit loss of planned downtime (10k ? /a, RMB) 6778 5084
Total downtime (h/a) 243.79 185.65
Total profit loss (10k ? /a, RMB) 9624 8021
Reduction of the total downtime standard 23.8%
Reduction of the total profit loss standard 16.7%
Similarly, simulation is carried out for each sub systems. These results also helped in the comparing the
performance of the system on changing the turnaround period from 3 year to 4 year. For instance, the simulation
results for reaction and regeneration system is illustrated in Table 2. It can be seen from Table 2 that availability
and reliability of reaction and regeneration system is varied significantly. However, similar simulations on power
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recovery units, air compressors, CO boilers, fractionator units, absorption and stabilization and desulphurization
units did not show much variation the values.
Table 2 - Simulation for reaction and regeneration system
3-year period 4-year period
Availability of unit in the period 0.9996 0.9994
Reliability of unit at the end-of-period 0.9983 0.9550
No of shut-downs in the period 0.5431 0.7389
unplanned downtime?h/a? 10.86 22.68
Equipment ranking for risk/ loss evaluation
Based on the process simulation the equipment are ranked based on a number of criteria such as the impact on
availability, financial loss, reason causing reduced load etc. to evaluate the risks and losses. For instance, top
critical unit according to the inherent availability for the entire lifecycle are slide valves, whereas for three or four
years of simulation it is axial compressors. Similarly, lists of critical items have been identified for various time
periods in the life cycle of the assets. This helps in identifying the new risks in the system as a result of changing
turnaround interval. To reduce the identified new risks, cost effective maintenance strategies are recommended,
and the potential risks/losses are lowered down by tailored maintenance solution. Similarly in regards to financial
losses, for the entire life cycle slide valves are again the top contributes.
Process Evaluation
In this section scenario based analyses are carried out. Detailed analysis based on the simulation results are
carried out. These involve identifying the best maintenance strategy, identifying the best retrofit option and
operational strategy among others to improve the reliability, availability, maintainability and productivity of the
system.
During the first phase of evaluation, it was identified that economic losses could be reduced by changing the
operation period from three years to four years; thus, the annual profits could be increased with about 16 million
RMB, i.e. 64 million RMB for four years in total. (Excluding the savings from the maintenance cost).
A few of the suggestions following the process evaluation include,
1. Extension of turnaround from 3 year to 4 year.
2. Enhance monitoring ion residual heat boilers during daily operation
3. Based on cost analysis detailed inspection of equipment during overhaul
4. Retrofit option for residual heat boilers, slide valves, steam turbines, pumps etc. with payback period
5. Suggestions during overhaul for static equipment
A number of retrofit options were recommend, for instance for the residual heat boiler. The residual heat boiler
accounted for 12.7% of the system loss. Failure of one boiler causes 30% decrease in the load while failure of
two boilers leads to the shutdown of the system. In this scenario, Table 3 suggests the recommended retrofit
options. In Table 3, three scenarios are evaluated for the new standby boilers. Since the MTBF of the new
standby system is not known, a value lower than the current MTBF value is provided in the simulation to assess
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the different scenarios. It can be seen from Table 3 that profit growth is higher (and hence low pay back period)
when the standby system retrofitted has the lowest MTBF (1 year).
Table 3 - Retrofit option for boilers. Current scenario and two cases of the new standby boiler with lower MTBF are
illustrated along with the payback period.
Scenario
Current 1 2
MTBF of residual heat boiler?year? 2.8 1.5 1
Unplanned economy loss (10k/a) No standby 2937 3268 3624
With standby 2557 2564 2572
System productivity (Practical
production/ designing production)
No standby 98.85% 98.16% 98.01%
With standby 98.97% 98.45% 98.45%
Profit growth (10k/a, RMB? 380 705 1052
Payback period (Retrofit fee: 10 million, RMB? 3.5 year 1.5 year 1 year
Another critical item identified was the slide valves, regarding their maintenance a sensitivity analysis was
carried out as shown in Table 4. From Table 4 it can be seen that a 100% repair of the slide valves can improve
the system productivity and cause no profit reduction. Therefore, in order to reduce the risks/ losses, it was
recommended that during turnaround period, the slide valves maintenance scheme should be changed from only
maintaining 4 out 6 to maintaining 6 out of 6.
Table 4 - Effect of Repair percentage of slide valves on the system performance
Analysis 1 Analysis 2 Analysis 3
Repair percentage Repair100% Repair95% Repair90%
Failure probability of slide valves 0.0015 0.0082 0.0359
Economy loss from slide valves (10k/a) 41 249 1090
Unplanned economy loss (10k/a) 2937 3145 3987
System productivity (Practical
production/designing production) 98.82% 98.74% 98.40%
Profit reduction (10k/a) -- 208 1050
Similar analysis was carried out for all the critical items identified in the refinery. A detailed description of the
analysis carried out for all the equipment is beyond the scope of this report.
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A few Suggestions for overhaul on Static equipment based on process evaluation
? Residual heat boiler - in terms of new boilers, ensure the quality of purchase, installation and inspection.
The failure, leakage that has a low MTBF needs to be inspected and a CBM system shall be
implemented during overhaul. .
? Slide valves - ensure the maintenance quality, return to the factory for maintenance as much as possible
for an as god as new maintenance. Carry out maintenance for all the 6 slide valves rather than the
current scheme of 4 out of 6.
? 1st stage regenerator – RCA are preferred for the incidents occurred.
? Load/unloading ports of 1st stage regenerator – In the event of another occurrence, preventive
maintenance or replacement need to be considered during each overhaul.
? Cyclones in the regenerator - replace according to its design life, to ensure the installation qualities of
accessory components such as wing valve.
? Stripper-ensure the installation qualities of nozzle or other accessory components to the highest.
? Butterfly valve and gate valve - ensure maintenance quality.
? Lines-replacement of expansion joints and other frequently failed parts should be conducted according
on the designing life-span.
? 3 stage cyclone- focus shall be on frequent failure parts
Spare Parts Optimization
Spares parts can be critical for one component or multi equipment. RAM-int is used to obtain the solution to
which spare parts to purchase when, and how many. The solution is optimized by considering the spare parts
purchasing options, delivery options, storage options, the corresponding costs and the failures of the spares parts
on one component or multiple components. This provides the optimal spare parts management to minimize the
process life cycle cost.
For the refinery it was noted that the same items installed in different unit has different failure profile. Hence while
developing spare strategy for such items it was imperative to consider this aspect into it. For the analysis, data
collected include Failure and repair parameters, Penalty costs, purchase costs, depreciation costs and delivery
time. Using the information collected simulation is carried out. Sample results obtained from the simulation are
given in Table 5. The suggested cost reduction is given in the table as a result of adopting the new policy.
Table 5 - Results from Spare parts optimization analysis. By keeping the suggested maximum storage cost reduction can
be achieved.
Spare Type Number of
installations
on working
machines
Current Maximum
storage
Suggested
maximum
storage
Cost
reduction
Seal YG6YWN8 1(1) 1 2 77.0%
Seal YG6SIC 1(1) 1 2 54.9%
Seal DBM90 1(1) In common use 2 94.1%
Seal DTM85B-2 2(1) 2 4 94.4%
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Seal DTM95 1(1) 1 2 92.3%
Seal VBBA40 1(1) In common use 2 87.7%
Seal VJB90-1 2(1) 2 4 82.5%
Bearing 3313 1(1) In common use 2 88.4%
Bearing6217 2(2) In common use 2 23.3%
Bearing6218 1(1) In common use 2 94.9%
Bearing7307BECBM 2(1) In common use 2 --%
Bearing7312 2(1) In common use 4 36.8%
Bearing7314 4(2) In common use 2 --%
Bearing7317 2(1) In common use 4 57.8%
BearingNU307 1(1) In common use 1 --%
BearingNU312 1(1) In common use 2 68.6%
BearingNU313 2(1) In common use 4 49.8%
Conclusion
This report demonstrates how turnaround interval extension is carried out in a refinery. It was shown that
extending the turnaround from 3 years to 4 years could bring savings to the refinery. The risks in extending the
turnaround have been identified in terms of financial loss, availability variation and reduction in load. To further
complement the extended turnaround, other strategies were developed including spare parts strategy and cost-
effective retrofit options consisting of redundancies. Retrofit options using redundancies for boilers, slide valves,
compressors etc. were proposed. Results from the whole analysis suggested that the refinery operators could
save more than £1.6 million per year for the entire refinery complex.
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