Novel network production planning method

• US 20060190113A1
• Filed: 12/09/2005
• Published: 08/24/2006
• Est. Priority Date: 12/10/2004
• Status: Active Grant

• Current Assignee: L'Air Liquide SA
• Original Assignee: L'Air Liquide SA
• Inventors: Weghe, Tom Van de, Cerro, Sonia Garcia Del, Pachany, Boris, Boutemy, Florence
• Granted Patent: US 7,873,429 B2
• Time in Patent Office: Days
• US Class Current: 700/97
• CPC Class Codes: F25J 2280/50 Advanced process control, e.g. adaptive or multivariable control
• CPC Class Codes: F25J 2290/50 Arrangement of multiple equipments fulfilling the same process step in parallel
• CPC Class Codes: F25J 3/0223 H2/CO mixtures, i.e. synthesis gas; Water gas or shifted synthesis gas production of carbon monoxide containing gas in general C01B32/40, C10J, C10K; production of hydrogen containing gas C01B3/00
• CPC Class Codes: F25J 3/0252 separation of hydrogen production of hydrogen containing gas in general C01B3/00, e.g. separation of hydrogen or hydrogen containing gases form gaseous mixtures at low temperatures C01B3/506
• CPC Class Codes: F25J 3/0261 separation of carbon monoxide production of carbon monoxide containing gas in general C01B32/40, C10J, C10K
• CPC Class Codes: F25J 3/04848 Control strategy, e.g. advanced process control or dynamic modeling
• CPC Class Codes: F25J 3/04951 Arrangements of multiple air fractionation units or multiple equipments fulfilling the same process step, e.g. multiple trains in a network F25J3/04636 takes precedence
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

Methods of production planning, including a novel method of optimized production planning for a plurality of production plants producing a product for delivery to a plurality of customers using a common distribution network, wherein the product consumption by customers can vary, and the variable cost of producing the product can vary between production plants, over time, and production quantity. The method maximizes profitability by characterizing raw material costs over varying production rates and minimizing variable cost across the network for any given production demand. The method considers the variable cost of producing product in varying production quantities, the variable cost structure of raw material supplies, and how these variable costs vary between production plants. The method also considers the variable cost impact of purchasing product from outside sources. The method produces monthly, weekly, daily, or hourly production plans and can automatically set target production quantities for each production plant to provide the lowest variable cost plan for a given production demand.

Claims

1. A method of controlling production within a network of production plants to produce and distribute a product to a network of customers, said method comprising:

a) linking a plurality of production plants and a distribution network to a production planning system, wherein said production plants produce a product, and said distribution network delivers said product to a plurality of customers;

b) obtaining a plurality of planning data values over a time step, said planning data values comprising;

i) a raw material cost structure;

ii) a value of a by-product for each of said production plants;

iii) a forecast consumption for each of said customers;

iv) a forecast production availability for each of said production plants or a forced production plan;

v) a production capacity for each of said production units;

vi) a process operating parameter for each of said production units;

vii) a network operating parameter;

viii) a cost of purchased product; and

ix) an availability of purchased product;

c) reading a plurality of current data values comprising;

i) a real-time production rate for each of said production plants;

ii) a real-time consumption for each of said customers; and

iii) a real-time network operating parameter;

d) reading a plurality of past data values comprising;

i) a past consumption for raw material; and

ii) a past parameter for raw material;

e) inputting said planning data values and said current data values into said production planning system;

f) calculating;

i) a total network production quantity; and

ii) a total network variable cost; and

g) outputting said plant production quantity for each of said production plants.

2. The method of claim 1, wherein said plurality of target network production values further comprises a purchased production quantity.

3. The method of claim 1, wherein said total network production quantity further comprises a unit production quantity and a unit cost.

4. The method of claim 1, wherein said production planning system comprises a plant cost program, a network production optimization program, and a network real-time operation program.

5. The method of claim 4, wherein:

a) said plant cost program calculates;

i) said plant variable cost for each of said production plants; and

ii) said total network variable cost;

b) said network production optimization program calculates;

i) said plant production quantity for each of said production plants;

ii) said purchased production quantity; and

iii) said total network production quantity.

6. The method of claim 1, wherein said plant variable cost is calculated for a production plant by:

a) calculating a preliminary plant production quantity for said production plant;

b) inputting said planned plant production quantity into a process-based model to calculate a mass balance across said production plant, wherein a quantity of a raw material required to produce said plant production quantity and a quantity of plant by-product produced is determined;

c) applying said raw material cost structure to said quantity of raw material required to calculate a cost of a raw material; and

d) calculating a preliminary plant variable cost.

7. The method of claim 6, wherein said total network variable cost is minimized by:

a) inputting said preliminary plant production quantity and said preliminary plant variable cost into a network production optimization program; and

b) calculating said total network production quantity.

8. The method of claim 1, wherein said distribution network comprises a pipeline and a compressor, said network operating parameter is an operating state of said compressor, and said production plants produce a hydrogen product and a carbon monoxide product.

9. The method of claim 1, wherein a production setpoint for at least one of said production plants is set considering said plant production quantity for said production plant.

10. The method of claim 9, wherein said plant production quantity for at least one of said production plants is electronically transmitted to an automated control system of said production plant.

11. The method of claim 10, wherein said production setpoint of said automated control system for at least one of said production plants is automatically set to a value to substantially achieve said plant production quantity for said at least one production plant.

12. The method of claim 10, further comprising:

a) continually reading at least one of said current data values;

b) continually calculating said plant production quantity for at least one of said production plants; and

c) updating said plant production quantity of said at least one production plant.

13. The method of claim 12, wherein said method continually reads said real-time network operating parameter.

14. The method of claim 13, wherein said method continually reads said real-time production rate for each of said production plants.

15. The method of claim 14, wherein said method continually reads said real-time consumption for each of said customers.

16. The method of claim 15, wherein said product comprises a hydrogen product and a carbon monoxide product.

17. The method of claim 1, wherein said time step is a day, a week, a month, or a year.

18. The method of claim 1, wherein said method further calculates and outputs a 3-hour production target for each of said production plants.

19. The method of claim 1, wherein said planning data further comprises a price penalty associated with purchasing particular products.

20. The method of claim 1, wherein said planning data comprises a plurality of raw material cost structures, and wherein said plurality of raw material cost structures simulate the structure and clauses of raw material purchase contracts.

21. The method of claim 1, wherein said total network variable cost is minimized.

22. A method of controlling production within a network of production plants to produce and distribute a product to a network of customers, said method comprising:

a) linking a plurality of production plants and a distribution network to a production planning system, wherein said production plants produce a product, said distribution network delivers said product to a plurality of customers, and said distribution network comprises a compressor;

b) obtaining a plurality of planning data values over a time step, said planning data values comprising;

i) a raw material cost structure;

ii) a value of a by-product for each of said production plants;

iii) a forecast consumption for each of said customers;

iv) a forecast production availability for each of said production plants or a forced production plan;

v) a production capacity for each of said production units and said compressor;

vi) a process operating parameter for each of said production units and said compressor;

vii) a network operating parameter;

viii) a cost of purchased product; and

ix) an availability of purchased product;

c) reading a plurality of current data values comprising;

i) a real-time production rate for each of said production plants;

ii) a real-time consumption for each of said customers; and

iii) a real-time network operating parameter;

d) reading a plurality of past data values comprising;

i) a past consumption for raw material; and

ii) a past parameter for raw material;

e) inputting said planning data values and said current data values into said production planning system;

f) calculating;

i) a total network production quantity; and

ii) a total network variable cost; and

g) outputting said plant production quantity for each of said production plants.

23. The method of claim 22, wherein said plurality of target network production values further comprises a purchased production quantity.

24. The method of claim 22, wherein said total network production quantity further comprises a unit production quantity and a unit cost.

25. The method of claim 22, wherein said production planning system comprises a plant cost program, a network production optimization program, and a network real-time operation program.

26. The method of claim 25, wherein:

a) said plant cost program calculates;

i) said plant variable cost for each of said production plants; and

ii) said total network variable cost;

b) said network production optimization program calculates;

i) said plant production quantity for each of said production plants;

ii) said purchased production quantity; and

iii) said total network production quantity.

27. The method of claim 22, wherein said network operating parameter is an operating state of said compressor, and said production plants produce a hydrogen product and a carbon monoxide product.

28. The method of claim 27, wherein said product comprises a hydrogen product and a carbon monoxide product.

29. The method of claim 22, wherein said time step is a day, a week, a month, or a year.

30. The method of claim 22, wherein said method further calculates and outputs a 3-hour production target for each of said production plants.

31. The method of claim 22, wherein said planning data further comprises a price penalty associated with purchasing particular products.

32. The method of claim 22, wherein said planning data comprises a plurality of raw material cost structures, and wherein said plurality of raw material cost structures simulate the structure and clauses of raw material purchase contracts.

33. The method of claim 22, wherein the total network variable cost is minimized.