Network production planning method

• US 7,873,429 B2
• Filed: 12/09/2005
• Issued: 01/18/2011
• Est. Priority Date: 12/10/2004
• Status: Active Grant

• Current Assignee: L'Air Liquide SA
• Original Assignee: L'Air Liquide Societe Anonyme Pour L'Etude et L'Exploitation Des Procedes Georges Claude (L'Air Liquide SA)
• Inventors: Pachany, Boris, Garcia Del Cerro, Sonia, Boutemy, Florence, Van de Weghe, Tom
• Primary Examiner(s): VON BUHR, MARIA N
• Application Number:
  US11/298,787
• Publication Number:
  US 20060190113A1
• Time in Patent Office: 1,866 Days
• Field of Search: 700 95- 97, 700/99, 700/100, 700/106, 705 7- 10
• 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 computer implemented 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) obtaining a plurality of planning data values for a given period of time, said planning data values including at least;

i) a plurality of raw material cost structures for raw materials used in the production of the product, wherein each raw material cost structure specifies one or more parameters of a take-or-pay supply contract between a production plant and a raw material supplier;

including at least one of a raw material price, a raw material quantity specified in the take-or-pay contract, a maximum contracted consumption rate, an energy adjustment, a series of prices based on quantity of usage, a forecast price for a raw material, and a spot price;

ii) a value of one or more by-products for each of a plurality of production plants within said network of production plants, wherein each by-product results from processing the raw materials used in the production of the product, and wherein the value for a given by-products specifies a cost of processing that by-product;

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 plants;

vi) a cost of the product;

vii) an availability of the product; and

b) reading a plurality of current data values including at least;

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

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

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

d) calculating from said inputted planning data values and said current data values;

i) a total network variable cost, wherein the total network variable cost specifies;

i) a plant production quantity;

ii) a plant variable cost;

iii) a total network production quantity; and

iv) the total network variable cost;

e) controlling production within the network of production plants by outputting a plant production quantity for each of said production plants on the basis of the total network variable cost.

2. 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, wherein:

a) said plant cost program calculates;

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

ii) said total network variable cost;

b) said network production optimization program calculates;

said plant production quantity for each of said production plants; and

c) said network real-time operation program calculates a targeted plant production quantity for each production plant.

3. The method of claim 2, wherein said plant variable cost is calculated for a given production plant by:

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

b) calculating a preliminary plant variable cost from said mass balance across said given production plant, said quantity of the raw material required to produce said planned plant production quantity, and said quantity of plant by-product produced.

4. The method of claim 2, 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.

5. The method of claim 4, wherein said real-time production rate is continually read for each of said production plants.

6. The method of claim 5, wherein said real-time consumption is continually read for each of said customers.

7. The method of claim 6, wherein said product comprises a hydrogen product and a carbon monoxide product.

8. The method of claim 1, wherein said production plants produce a hydrogen product and a carbon monoxide product.

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

10. The method of claim 1, wherein the raw material cost structure further specifies a contract volume purchased on a contract price and a spot volume purchased on a spot price, and is represented by the formula:

C=p_contract×

V_contract+p_spot×

V_spot

wherein C is the raw material cost structure, p_contract is the contract price, V_contract is the contract volume, p_spot is the spot price, and V_spot is the spot volume.

11. The method of claim 1, wherein the by-products include at least one of waste water, solid waste, CO₂, liquid waste, and gaseous waste.

12. A computer implemented H₂/CO production load planning method for a plurality of production plants, comprising:

i) inputting as inputs to a system;

H₂ and CO current consumption from consumers connected to the plurality of production plants by a network of pipelines configured for delivery of the H₂ and CO, forecasts of demand for H₂ and CO from consumers, and H₂ purchase price, a plurality of raw material cost structures for the raw materials used in the production of the H₂ and CO, wherein each raw material cost structure specifies one or more parameters of a take-or-pay supply contract between a production plant and a raw material supplier, and a value of one or more by-products for each of a plurality of production plants within said plurality of production plants, wherein each by-product results from processing the raw materials used in the production of the product, and wherein the value for a given by-products specifies a cost of processing that by-product; and

ii) on the basis of the inputs, generating a production plan that allocates production for each of the plurality of production plants in a manner that minimizes variable costs associated with producing the H₂ and CO.

13. The method of claim 12, wherein generating comprises computing a weekly planning of production for each plant.

14. A computer implemented method of calculating production for a plurality of production plants within a network of production plants, comprising:

a) obtaining a plurality of planning data values, a plurality of current data values, and a plurality of past data values, wherein the plurality of planning data values includes at least;

i) a plurality of raw material cost structures for the raw materials used in the production of the product wherein each raw material cost structure specifies one or more parameters of a take-or-pay supply contract between a production plant and a raw material supplier;

including at least one of a raw material price, a raw material quantity specified in the take-or-pay contract, a maximum contracted consumption rate, an energy adjustment, a series of prices based on quantity of usage, a forecast price for a raw material, and a spot price;

ii) a value of one or more by-products for each of a plurality of production plants within the network of production plants wherein each by-product results from processing the raw materials used in the production of the product, and wherein the value for a given by-products specifies a cost of processing that by-product;

iii) a forecast consumption for each of the consumers;

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

v) a production capacity for each of the production plants;

vi) a cost of the product;

vii) an availability of the product; and

b) calculating a plant production quantity for each plant that minimizes variable costs at each production plant based upon the obtained data.

15. The method of claim 14, wherein the raw material cost structures further include a contract volume purchased on a contract price and a spot volume purchased on a spot price, and is represented by the formula:

C=p_contract×

V_contract+p_spot×

V_spot

wherein C is the raw material cost structure, p_contract is the contract price, V_contract is the contract volume, p_spot is the spot price, and V_spot is the spot volume.

16. The method of claim 14, wherein the past data values comprise a past consumption of raw material.

17. The method of claim 14, wherein the production plants produce a hydrogen product and a carbon monoxide product.

18. The method of claim 14, wherein the current data values are selected from the group comprising:

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

ii) a real-time consumption for each of the consumers; and

iii) combinations thereof.

19. The method of claim 14, wherein the by-products include at least one of waste water, solid waste, CO₂, liquid waste, and gaseous waste.

20. A computer implemented method of controlling production within a network of production plants to produce and distribute a product to a network of consumers, the method comprising:

i) obtaining a plurality of planning data values over a time step;

ii) reading a plurality of current data values;

iii) inputting the planning data values and the current data values into a production planning system;

iv) calculating a total network production quantity based upon the planning data values and the current data values input to the production planning system; and

v) calculating a plant production quantity for each production plant based upon the total network production quantity, wherein the plant production quantities are calculated to minimize variable costs associated with production of the product at each production plant.

21. The method of claim 20, wherein the planning data values are selected from the group comprising:

i) a raw material cost structure for the raw materials used in the production of the product;

ii) a value of a by-product for each of a plurality of production plants within the network of production plants;

iii) a forecast consumption for each of the consumers;

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

v) a production capacity for each of the production plants;

vi) a cost of the product;

vii) an availability of the product; and

viii) combinations thereof.

22. The method of claim 21, wherein the raw material cost structure comprises a contract volume purchased on a contract price and a spot volume purchased on a spot price, and is represented by the formula:

C=p_contract×

V_contract+p_spot×

V_spot

wherein C is the raw material cost structure, p_contract is the contract price, V_contract is the contract volume, p_spot is the spot price, and V_spot is the spot volume.

23. The method of claim 20, further comprising inputting a plurality of past data values into the production planning system.

24. The method of claim 23, wherein the past data values comprise a past consumption of raw material.

25. The method of claim 20, wherein the production plants produce a hydrogen product and a carbon monoxide product.

26. The method of claim 20, wherein the current data values are selected from the group comprising:

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

ii) a real-time consumption for each of the consumers; and

iii) combinations thereof.

27. The method of claim 20, wherein the by-products include at least one of waste water, solid waste, CO₂, liquid waste, and gaseous waste.