Refinery Planning & Scheduling - Plan the Act. Act the Plan.
Refinery Planning & Scheduling - Plan the Act. Act the Plan.
Refinery Planning & Scheduling - Plan the Act. Act the Plan.
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<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> & <strong>Scheduling</strong><br />
- <strong>Plan</strong> <strong>the</strong> <strong>Act</strong>. <strong>Act</strong> <strong>the</strong> <strong>Plan</strong>.<br />
By Sowmya Santhanam<br />
WIPRO TECHNOLOGIES
EXECUTIVE SUMMARY<br />
Due to <strong>the</strong> record high and fluctuating crude prices, refineries are under extreme pressure to cut down<br />
operating costs. This has led to a great focus on <strong>the</strong> downstream supply chain management processes and<br />
tools, which when effectively used, result in significant benefits for <strong>the</strong> refinery. This paper talks about <strong>the</strong><br />
best practices that are followed while modelling <strong>the</strong> planning and scheduling tools. The planning tools are<br />
used with <strong>the</strong> single objective of maximising <strong>the</strong> margins from <strong>the</strong> refinery. The scheduling tools help in<br />
implementing <strong>the</strong> plan on a day to day level.<br />
Currently, complete automation of scheduling tools has still not been achieved. This paper also talks about<br />
<strong>the</strong> future improvements that refiners are looking forward to. This paper attempts to give some thoughts<br />
and ideas that could be followed in developing general heuristics which are a step forward in <strong>the</strong> direction of<br />
complete automation of scheduling tools.
TABLE OF CONTENTS<br />
Introduction to <strong>the</strong> <strong>Refinery</strong> Supply Chain...................................................................4<br />
<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> and <strong>Scheduling</strong> in <strong>the</strong> Supply Chain................................................4<br />
Current Practices and Tool Modeling Basics.................................................................4<br />
<strong><strong>Plan</strong>ning</strong> Tool Modeling Basics.............................................................................................4<br />
Need for a <strong>Scheduling</strong> Tool and <strong>Scheduling</strong> Tool Modeling Basics.......................................................5<br />
<strong>Scheduling</strong> in <strong>the</strong> Future.............................................................................................. 5<br />
Crude <strong>Scheduling</strong>............................................................................................................6<br />
Product <strong>Scheduling</strong>..........................................................................................................7<br />
Monitoring of Schedulers Performance........................................................................8<br />
Data Consistency across Models..................................................................................8<br />
Conclusion....................................................................................................................9<br />
Appendix...................................................................................................................... 9<br />
About <strong>the</strong> Author...........................................................................................................9
<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> and <strong>Scheduling</strong> - <strong>Plan</strong> <strong>the</strong> <strong>Act</strong>. <strong>Act</strong> <strong>the</strong> <strong>Plan</strong>.<br />
Introduction to <strong>the</strong> <strong>Refinery</strong> Supply Chain<br />
Supply chain optimization is an important margin driver for a refinery. The<br />
complexity, with which a refinery is built, provides <strong>the</strong> flexibility to optimize<br />
operations, <strong>the</strong>reby maximizing margins. Supply chain managers need to<br />
analyze a very complex set of choices before taking decisions. Best in class<br />
Supply Chain Management (SCM) tools and practices will be required to give<br />
forward visibility to supply chain operations.<br />
The principles necessary for an operationally effective and successful<br />
downstream supply chain, includes a requirement for integrated planning,<br />
information flowing in all directions, efficient execution, and visibility to<br />
performance across <strong>the</strong> organization.<br />
Hence, one cannot underestimate <strong>the</strong> importance of an integrated<br />
architecture in <strong>the</strong> complete supply chain.<br />
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Wikipedia Says...<br />
Supply Chain Optimization is <strong>the</strong><br />
application of processes and tools<br />
to ensure <strong>the</strong> optimal operation of a<br />
manufacturing and distribution<br />
supply chain. This includes <strong>the</strong><br />
optimal placement of inventory<br />
within <strong>the</strong> supply chain, minimizing<br />
operating costs. This often involves<br />
<strong>the</strong> application of ma<strong>the</strong>matical<br />
modelling techniques using<br />
computer software.<br />
<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> and <strong>Scheduling</strong> in <strong>the</strong> Supply Chain<br />
The objective and scope of each tool in <strong>the</strong> supply chain should be well defined.<br />
<strong><strong>Plan</strong>ning</strong> tools -> <strong>Plan</strong> <strong>the</strong> act! To maximize <strong>the</strong> margins from <strong>the</strong> refinery complex<br />
<strong>Scheduling</strong> -> <strong>Act</strong> <strong>the</strong> plan!<br />
The manufacturing plants follow <strong>the</strong> guidelines as defined by <strong>the</strong> planning and scheduling tools, for optimized refinery<br />
operations. A well-defined feedback mechanism should be part of <strong>the</strong> process, so as to analyze and identify any gaps in <strong>the</strong><br />
plan, schedule, and operations and continually improve and tune <strong>the</strong> process.<br />
Current Practices and Tool Modeling Basics<br />
<strong><strong>Plan</strong>ning</strong> Tool Modeling Basics<br />
The refinery planning tool is generally being used for different purposes like financial forecasting, feedstock valuation, crude<br />
run and refinery unit optimization, stock forecasting, etc with <strong>the</strong> single objective of maximizing Gross Refining Margins<br />
(GRM).<br />
The planning tool serves as an important medium for aligning <strong>the</strong> midstream planning with <strong>the</strong> downstream marketing. It<br />
captures <strong>the</strong> refinery as a whole; and <strong>the</strong> key is optimization of <strong>the</strong> various constraints with <strong>the</strong> single objective of margin<br />
maximization. Hence, it is very important that we do not land up with local optima problems with this tool. Non-linear<br />
solvers have an inherent problem of local optima, so all efforts should be made to keep all constraints in <strong>the</strong> tool as much<br />
linear as possible. The basic idea is to compromise on small inaccuracies caused because of linearization without losing any<br />
focus on <strong>the</strong> single main objective of <strong>the</strong> planning tool, i.e. maximizing GRM by optimization.<br />
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Need for a <strong>Scheduling</strong> Tool and <strong>Scheduling</strong> Tool Modeling Basics<br />
<strong><strong>Plan</strong>ning</strong> is typically done for a month, so we have a monthly average as <strong>the</strong> Linear Programming (LP) model output i.e.<br />
we have:<br />
An average crude blend to be fed to <strong>the</strong> crude distillers<br />
An average product mix, which is to be produced during <strong>the</strong> entire month<br />
In complex refineries, where different crudes are blended to produce a cocktail which is ultimately fed to <strong>the</strong> crude unit,<br />
<strong>the</strong> crude diet to <strong>the</strong> unit changes almost every day. It is generally difficult to implement this “average” schedule on a<br />
day-to-day basis, because of several issues like non-availability of crudes as planned during <strong>the</strong> LP model run, <strong>the</strong> tank-<br />
pump hardware constraints in <strong>the</strong> field, etc which are generally not configured in <strong>the</strong> LP in an effort to keep <strong>the</strong><br />
constraints linear.<br />
Hence, it is very important to have a scheduling tool, in which all <strong>the</strong> constraints are modeled in great detail, to check <strong>the</strong><br />
feasibility of plan implementation. The primary goal of a scheduling tool is to have a feasible schedule, meeting all<br />
targets identified from plan. Once, all targets are met, <strong>the</strong> schedule is already optimal i.e. <strong>the</strong> schedule drives towards<br />
maximizing <strong>the</strong> GRM of <strong>the</strong> refinery.<br />
The process units behave in a highly non-linear fashion and many a product specification blend in a non-linear way. The<br />
emphasis on <strong>the</strong> solution provided by <strong>the</strong> tool is on its practical implement ability, so <strong>the</strong> scheduling tool should provide<br />
very accurate results. Hence, we need to use Mixed Integer Nonlinear Programming (MINLP) solvers when solving<br />
problems of this type. Local optima problems, which are inherent problems with MINLP solvers, are no longer a concern,<br />
since optimization is not <strong>the</strong> primary objective. We are more bo<strong>the</strong>red with <strong>the</strong> accuracy of <strong>the</strong> results for its day-to-day<br />
implementation; hence <strong>the</strong>se complex solvers best suit refinery schedulers’ requirements.<br />
It is essential to have a high-fidelity scheduling tool for<br />
scheduling decisions that are accurate and enables <strong>the</strong><br />
scheduler to quickly respond to changing business scenarios<br />
like emergency shutdown of a unit or purchase decision of a<br />
distress sale crude cargo. The scheduling team has to quickly<br />
act on such situations advising <strong>the</strong> traders <strong>the</strong> best possible<br />
solution; else <strong>the</strong> refinery loses out on that opportunity. Not<br />
only is it important to have a good tool, it is essential to have a<br />
good team of people working on <strong>the</strong>se tools.<br />
<strong>Scheduling</strong> in <strong>the</strong> Future<br />
The current scheduling tools and processes have allowed <strong>the</strong> refinery planner and scheduler close <strong>the</strong> gap between LP<br />
plan and schedule to a fair extent. However, <strong>the</strong> preparation of <strong>the</strong> schedule is still largely person-dependent. Even with<br />
a fairly robust model and an experienced scheduler, it typically takes a couple of hours to prepare a months’ schedule for<br />
a complex refinery. The dream of <strong>the</strong> refiner is to move from a “person-dependent regime” to a “process dependent<br />
regime”. In o<strong>the</strong>r words, <strong>the</strong> idea is to have generic heuristics built into <strong>the</strong> tool so as to make it “intelligent” to handle all<br />
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Tools today help us to move from a “finding<br />
a solution” scenario to an “analysis of<br />
schedules” scenario i.e. with <strong>the</strong> availability<br />
of a good tool, schedulers will now spend<br />
more time on analyzing <strong>the</strong> various possible<br />
schedules and decide which one is <strong>the</strong> most<br />
effective in terms of maximizing GRM.<br />
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<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> and <strong>Scheduling</strong> - <strong>Plan</strong> <strong>the</strong> <strong>Act</strong>. <strong>Act</strong> <strong>the</strong> <strong>Plan</strong>.<br />
kinds of scenarios, so that <strong>the</strong> schedule will be <strong>the</strong> same irrespective of <strong>the</strong> person preparing <strong>the</strong> schedule. The<br />
challenge today for <strong>the</strong> tool developer is to have a “recursion” feature developed in <strong>the</strong> tool so that it has <strong>the</strong> capability<br />
to go back and forth in time to make <strong>the</strong> overall schedule feasible or find <strong>the</strong> “best schedule”.<br />
Crude <strong>Scheduling</strong><br />
The preparation of <strong>the</strong> crude blend itself has been automated in most tools to a large extent, however it is <strong>the</strong> receipt of<br />
crudes in various tanks that is present in <strong>the</strong> refinery is mostly manual. The receipt largely dictates <strong>the</strong> feasibility of<br />
crude blends from <strong>the</strong>reon. A “wrong” receipt could cause infeasibility even a couple of weeks forward in <strong>the</strong> schedule.<br />
The dilemma is to specify to <strong>the</strong> optimizer <strong>the</strong> time period it should go back and rework <strong>the</strong> schedule, just like a<br />
scheduler would, so as to make <strong>the</strong> blends over <strong>the</strong> entire horizon feasible.<br />
Typically, <strong>the</strong> following challenges are faced when developing a general heuristic:<br />
1<br />
2<br />
3<br />
4<br />
5<br />
6<br />
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Whe<strong>the</strong>r to make a blend or take receipt of <strong>the</strong> crude into tanks at any point in time?<br />
If <strong>the</strong>re are multiple crudes present in <strong>the</strong> ship/ scheduled to be received through <strong>the</strong><br />
pipeline, which crude to be received first?<br />
If <strong>the</strong>re is a problem with blend feasibility, <strong>the</strong>n can some property be relaxed in <strong>the</strong><br />
crude blend window to make blend feasible? If multiple properties can be relaxed <strong>the</strong>n<br />
<strong>the</strong> order of preference of relaxation?<br />
Incase of complete infeasibility, how many days’ schedule to be deleted and readjusted<br />
so that we make <strong>the</strong> complete schedule feasible?<br />
Even with recursion features <strong>the</strong> challenge is to have a generic algorithm which will<br />
decide how long should we go back in time and rework <strong>the</strong> blends inorder to make <strong>the</strong><br />
schedule feasible.<br />
Demurrage vs. blend quality<br />
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It is also seen that, in a refinery which processes multiple crudes in a blend, <strong>the</strong> trick is to store crudes as diverse in quality as<br />
possible in order to make blends feasible. This problem, by itself, is a ma<strong>the</strong>matical challenge, as it is analogous to finding<br />
<strong>the</strong> maximum distance between two points. However, it is possible to develop a practically implementable solution, if <strong>the</strong><br />
scheduler is able to diversify categories of crudes to different tanks based on his experience.<br />
Such clues along with clear answers to above situations will help a scheduler develop general heuristics for <strong>the</strong> tool, which<br />
will lead to feasible blends in most cases. These procedures will help <strong>the</strong> scheduler a lot in running sensitivity cases, with<br />
small changes in crude cargo types, cargo arrival dates etc. The user still has to manually take receipt into <strong>the</strong> tanks and do<br />
one complete schedule to identify <strong>the</strong> problem areas, so that he can give <strong>the</strong> right kind of inputs to run <strong>the</strong> tool in “auto”<br />
mode while carrying out sensitivity analyses. We are going one step fur<strong>the</strong>r in trying to avoid repetitive work for <strong>the</strong> crude<br />
scheduler<br />
Product <strong>Scheduling</strong><br />
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The output crude<br />
schedule<br />
Product Schedule<br />
The output crude schedule is one of <strong>the</strong> primary inputs of <strong>the</strong> product scheduling tool. Apart from this, <strong>the</strong> primary unit<br />
throughputs, <strong>the</strong> feedstock and product prices and production targets are inputs that are taken from <strong>the</strong> LP. The grade-wise<br />
dispatch schedule of products is taken from marketing. All <strong>the</strong>se inputs are automated, with <strong>the</strong> help of a common database<br />
which helps in data transfer between tools.<br />
Primary unit<br />
throughputs, feedstock,<br />
product prices,<br />
production targets<br />
Grade-wise disptatch<br />
schedule of products<br />
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Once all <strong>the</strong> required inputs are given, with just a click of a button, we should have <strong>the</strong> complete product schedule ready.<br />
The tool should provide a good analysis of <strong>the</strong> component production, component usage in each grade, component and<br />
product tanks usage, economic analysis, etc which helps <strong>the</strong> user analyze <strong>the</strong> solution. In case of infeasibilities, <strong>the</strong> tool<br />
should be capable of providing clues to infeasibility breakers so that <strong>the</strong> scheduler is not lost in <strong>the</strong> vast amount of data that<br />
is presented to him.<br />
These are typically decisions which vary with time. The challenge is to have a senior scheduler formulate a generic algorithm<br />
which would work in most of <strong>the</strong> situations. The goal is to have a full months’ schedule prepared by <strong>the</strong> tool without any user<br />
intervention in-between.<br />
All <strong>the</strong> above initiatives will help refinery planning and scheduling professionals to go one step ahead in automation of<br />
scheduling tools. While we are still far from making <strong>the</strong> process completely automated, it is a step in <strong>the</strong> right direction.<br />
Monitoring of Schedulers Performance<br />
To reap <strong>the</strong> full benefits of a tool implementation, <strong>the</strong> performance of <strong>the</strong> schedulers should also be monitored with<br />
quantifiable objectives. Some of <strong>the</strong> objectives for <strong>the</strong> product schedulers could be predicted grade-wise production<br />
numbers vs. actual, Quality Give Away in cents/bbl against a target, no of product/batch failures, etc. Similarly for <strong>the</strong> crude<br />
scheduler it could be <strong>the</strong> comparison of crude consumption as suggested by <strong>the</strong> LP model vs. actual consumed.<br />
These serve as important checks to continually make sure that <strong>the</strong> scheduler is completely in sync with <strong>the</strong> plan goals and<br />
objectives, and working as per <strong>the</strong> schedule suggested by <strong>the</strong> tool.<br />
Data Consistency across Models<br />
The data that is present in <strong>the</strong> planning and scheduling models should be accurate and tuned to represent <strong>the</strong> current<br />
conditions of <strong>the</strong> plant. There should be a person/team of people who are given <strong>the</strong> responsibility of having consistent data<br />
across all models used in planning and scheduling. There should be a good business process for <strong>the</strong> model update. Changes<br />
in yields/quality in a plant for a small duration of time are generally not updated in <strong>the</strong> planning model, as it has greater<br />
ramifications including influencing decisions on crude valuations and buying. Hence, only consistent shifts in yields and<br />
qualities of streams are updated in <strong>the</strong> planning model with due explanation. However, <strong>the</strong>se small changes could be<br />
updated in <strong>the</strong> process models present in <strong>the</strong> scheduling tool to capture <strong>the</strong> variations in production that it might cause in<br />
<strong>the</strong> immediate future.<br />
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<strong>Refinery</strong> <strong><strong>Plan</strong>ning</strong> and <strong>Scheduling</strong> - <strong>Plan</strong> <strong>the</strong> <strong>Act</strong>. <strong>Act</strong> <strong>the</strong> <strong>Plan</strong>.<br />
Conclusion<br />
In this paper, we discussed on <strong>the</strong> important things that are to be taken care of while modelling planning and scheduling<br />
tools. One should not lose focus on <strong>the</strong> primary objectives of running <strong>the</strong>se tools. The planning tool acts as a bible - it is <strong>the</strong><br />
single most important tool from which directions are to be taken. The scheduling tool should primarily enact <strong>the</strong> plan, but<br />
with all adjustments required because of <strong>the</strong> non-linear nature of refinery processes. With <strong>the</strong>se thoughts, schedulers<br />
move one step higher in scheduling automation. However, to make <strong>the</strong> tools more person independent, <strong>the</strong> senior<br />
schedulers <strong>the</strong>mselves have to identify general guidelines which work in <strong>the</strong>ir refinery in most situations. The effectiveness<br />
of a robust “recursion” feature is very essential for working towards this goal and more studies need to be done in this<br />
direction.<br />
Appendix<br />
About <strong>the</strong> Author<br />
Sowmya Santhanam, Lead Consultant, Refining Practice of Wipro Technologies, is a Chemical Engineer with a degree in<br />
Ma<strong>the</strong>matics from BITS, Pilani. She has earlier worked with <strong>the</strong> <strong><strong>Plan</strong>ning</strong> & <strong>Scheduling</strong> department of Reliance Industries<br />
Ltd for over 6 yrs on various scheduling desks, and has implemented supply chain tools for <strong>the</strong> 1.2 kbpsd refinery.<br />
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