Model-based systems and methods for calculating raw material usage rates from dynamic inventory trend data

• US 20040103047A1
• Filed: 11/27/2002
• Published: 05/27/2004
• Est. Priority Date: 11/27/2002
• Status: Abandoned Application

• Current Assignee: Sabic Innovative Plastics IP BV (Government of Saudi Arabia)
• Original Assignee: Sabic Innovative Plastics IP BV (Government of Saudi Arabia)
• Inventors: Park, Nam Seog, Mackenzie, Patricia Denise
• Application Number:
  US10/306,123
• Publication Number:
  US 20040103047A1
• Time in Patent Office: Days
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

Model-based systems and methods for calculating raw material usage rates from dynamic inventory trend data are described so that materials inventory may be monitored so as to allow for efficient use of the materials. These systems and methods also allow supply chain performance and operations management to be optimized. Materials inventory trend data may first be segmented into segments containing inventory data from one refill of a silo/storage vessel to the next refill. Thereafter, the data in each segment may be serialized to fit on a unified time and inventory scale. Models, preferably cubic regression analysis models, may then be created, and inventory levels on any dates within the models can be estimated therefrom. From these inventory levels, material usage rates may be calculated. These systems and methods may be accessible to users via web-based interfaces.

Claims

1. A method for creating a model that can be utilized to calculate a material usage rate for a material from dynamic material inventory data, the method comprising:

segmenting material inventory trend data into segments, wherein the segments comprise material inventory levels from one refill to the next refill;

serializing each segment so that each segment fits a unified time and inventory scale;

building an individual cubic regression model for each serialized segment; and

building a collective cubic regression model by combining all the individual cubic regression models together.

2. The method of claim 1, wherein the material inventory trend data is dynamic.

3. The method of claim 1, wherein each individual cubic regression model comprises data, wherein the data comprises at least one of:

an individual model identification, a start date of the data in the individual cubic regression model, an end date of the data in the individual cubic regression model, a C coefficient of the individual cubic regression model, a C₁ coefficient of the individual cubic regression model, a C₂ coefficient of the individual cubic regression model, and a C₃ coefficient of the individual cubic regression model, wherein each individual cubic regression model utilizes the equation y=C₃x³+C₂x²+C₁x+C.

4. The method of claim 1, wherein the collective cubic regression model comprises one or more individual cubic regression models.

5. The method of claim 1, further comprising:

utilizing the collective cubic regression model to calculate the material usage rate for the material from the material inventory trend data.

6. The method of claim 5, wherein the calculated material usage rate is sent to at least one Vendor Managed Inventory (VMI) system.

7. The method of claim 6, wherein the at least one VMI system comprises a multi-tiered service.

8. The method of claim 6, wherein the at least one VMI system comprises at least one of:

monitoring process data for one or more production lines;

monitoring material inventory levels for one or more production lines;

monitoring material usage for one or more production lines;

monitoring energy usage for one or more production lines;

monitoring production rates for one or more production lines;

calculating a material usage rate for one or more production lines.

9. The method of claim 1, wherein the material comprises at least one of:

an engineering thermoplastic, a liquid, a compressed gas, a food product, grains, concrete aggregates, packaged goods, a material capable of being stored in a storage vessel, and a material capable of being stored in a silo.

10. The method of claim 9, wherein the engineering thermoplastic comprises at least one of:

a polyester, polyethylene terephthalate (PET), polybutylene terephthalate (PBT), polyethylene naphthalate (PEN), liquid crystal polyester (LCP), a polyolefin, polyethylene (PE), polypropylene (PP), polybutylene, a styrene-type resin, polyoxymethylene (POM), polyamide (PA), polycarbonate (PC), polymethylene methacrylate (PMMA), polyvinyl chloride (PVC), polyphenylene sulfide (PPS), polyphenylene ether (PPE), polyimide (PI), polyamide imide (PAI), polyetherimide (PEI), polysulfone (PSU), polyether sulphone (PES), polyketone (PK), polyether ketone (PEK), polyether ether ketone (PEEK), polyalylate (PAR), polyethernitrile (PEN), a phenol resin (novolac type), a phenoxy resin, a fluorocarbon resin, a thermoplastic elastomer of a polystyrene type, a thermoplastic elastomer of a polyolefin type, a thermoplastic elastomer of a polyurethane type, a thermoplastic elastomer of a polyesters type, a thermoplastic elastomer of a polyamide type, a thermoplastic elastomer of a polybutadiene type, a thermoplastic elastomer of a polyisoprene type, a thermoplastic elastomer of a fluorine type, a styrene-type resin, a polycarbonate resin, a polyphenylene ether resin, a polyamide resin, a polyester resin, a polyphenylene sulfide resin, a polyolebi resin, a liquid-crystalline resin, and a phenol-type resin.

11. A model-based method for calculating a material usage rate for a material, the method comprising:

selecting an earlier date and a later date;

retrieving a model that comprises both the earlier date and the later date;

utilizing the model to determine a first inventory level on the earlier date;

utilizing the model to determine a second inventory level on the later date;

calculating the material usage rate of the material between the earlier date and the later date.

12. The method of claim 11, wherein the material usage rate is calculated by utilizing a difference between the first inventory level on the earlier date and the second inventory level on the later date.

13. The method of claim 11, wherein the calculated material usage rate is sent to at least one Vendor Managed Inventory (VMI) system.

14. The method of claim 13, wherein the at least one VMI system comprises a multi-tiered service.

15. The method of claim 13, wherein the at least one VMI system comprises at least one of:

monitoring process data for one or more production lines;

monitoring material inventory levels for one or more production lines;

monitoring material usage for one or more production lines;

monitoring energy usage for one or more production lines;

monitoring production rates for one or more production lines;

calculating a material usage rate for one or more production lines.

16. The method of claim 11, wherein the material comprises at least one of:

an engineering thermoplastic, a liquid, a compressed gas, a food product, grains, concrete aggregates, packaged goods, a material capable of being stored in a storage vessel, and a material capable of being stored in a silo.

17. The method of claim 16, wherein the engineering thermoplastic comprises at least one of:

a polyester, polyethylene terephthalate (PET), polybutylene terephthalate (PBT), polyethylene naphthalate (PEN), liquid crystal polyester (LCP), a polyolefin, polyethylene (PE), polypropylene (PP), polybutylene, a styrene-type resin, polyoxymethylene (POM), polyamide (PA), polycarbonate (PC), polymethylene methacrylate (PMMA), polyvinyl chloride (PVC), polyphenylene sulfide (PPS), polyphenylene ether (PPE), polyimide (PI), polyamide imide (PAI), polyetherimide (PEI), polysulfone (PSU), polyether sulphone (PES), polyketone (PK), polyether ketone (PEK), polyether ether ketone (PEEK), polyalylate (PAR), polyethernitrile (PEN), a phenol resin (novolac type), a phenoxy resin, a fluorocarbon resin, a thermoplastic elastomer of a polystyrene type, a thermoplastic elastomer of a polyolefin type, a thermoplastic elastomer of a polyurethane type, a thermoplastic elastomer of a polyester type, a thermoplastic elastomer of a polyamide type, a thermoplastic elastomer of a polybutadiene type, a thermoplastic elastomer of a polyisoprene type, a thermoplastic elastomer of a fluorine type, a styrene-type resin, a polycarbonate resin, a polyphenylene ether resin, a polyamide resin, a polyester resin, a polyphenylene sulfide resin, a polyolebi resin, a liquid-crystalline resin, and a phenol-type resin.

18. The method of claim 11, wherein the model comprise a mathematical algorithm.

19. The method of claim 18, wherein the mathematical algorithm comprises cubic regression analysis.

20. A model-based system for calculating material usage rates for a material, the system comprising:

a means for selecting an earlier date and a later date;

a means for retrieving a model that comprises both the earlier date and the later date;

a means for utilizing the model to determine a first inventory level on the earlier date;

a means for utilizing the model to determine a second inventory level on the later date;

a means for calculating the material usage rate of the material between the earlier date and the later date.

21. The system of claim 20, wherein the material usage rate is calculated by utilizing a difference between the first inventory level on the earlier date and the second inventory level on the later date.

22. The system of claim 20, wherein the calculated material usage rate is sent to at least one Vendor Managed Inventory (VMI) system.

23. The system of claim 22, wherein the at least one VMI system comprises a multi-tiered service.

24. The system of claim 22, wherein the at least one VMI system comprises at least one of:

monitoring process data for one or more production lines;

monitoring material inventory levels for one or more production lines;

monitoring material usage for one or more production lines;

monitoring energy usage for one or more production lines;

monitoring production rates for one or more production lines;

calculating a material usage rate for one or more production lines.

25. The system of claim 20, wherein the material comprises at least one of:

an engineering thermoplastic, a liquid, a compressed gas, a food product, grains, concrete aggregates, packaged goods, a material capable of being stored in a storage vessel, and a material capable of being stored in a silo.

26. The system of claim 25, wherein the engineering thermoplastic comprises at least one of:

a polyester, polyethylene terephthalate (PET), polybutylene terephthalate (PBT), polyethylene naphthalate (PEN), liquid crystal polyester (LCP), a polyolefin, polyethylene (PE), polypropylene (PP), polybutylene, a styrene-type resin, polyoxymethylene (POM), polyamide (PA), polycarbonate (PC), polymethylene methacrylate (PMMA), polyvinyl chloride (PVC), polyphenylene sulfide (PPS), polyphenylene ether (PPE), polyimide (PI), polyamide imide (PAI), polyetherimide (PEI), polysulfone (PSU), polyether sulphone (PES), polyketone (PK), polyether ketone (PEK), polyether ether ketone (PEEK), polyalylate (PAR), polyethernitrile (PEN), a phenol resin (novolac type), a phenoxy resin, a fluorocarbon resin, a thermoplastic elastomer of a polystyrene type, a thermoplastic elastomer of a polyolefin type, a thermoplastic elastomer of a polyurethane type, a thermoplastic elastomer of a polyester type, a thermoplastic elastomer of a polyamide type, a thermoplastic elastomer of a polybutadiene type, a thermoplastic elastomer of a polyisoprene type, a thermoplastic elastomer of a fluorine type, a styrene-type resin, a polycarbonate resin, a polyphenylene ether resin, a polyamide resin, a polyester resin, a polyphenylene sulfide resin, a polyolebi resin, a liquid-crystalline resin, and a phenol-type resin.

27. The system of claim 20, wherein the model comprise a mathematical algorithm.

28. The system of claim 27, wherein the mathematical algorithm comprises cubic regression analysis.