Method and apparatus for inventory control of a manufacturing or distribution process

• US 5,819,232 A
• Filed: 03/22/1996
• Issued: 10/06/1998
• Est. Priority Date: 03/22/1996
• Status: Expired due to Term

• Current Assignee: DADE Chemistry Systems Incorporated
• Original Assignee: E. I. du Pont de Nemours and Company (Corteva, Inc.)
• Inventors: Shipman, Lester Lynn
• Primary Examiner(s): McElheny, Jr., Donald E.
• Application Number:
  US08/620,523
• Time in Patent Office: 928 Days
• Field of Search: 705/7, 705/8, 705/22, 395/904, 364/468.02, 364/468.06, 364/468.05, 364/468.1, 364/468.07, 364/468.08, 364/468.09, 364/468.13, 364/478.04
• US Class Current: 705/7.24
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06314 Calendaring for a resource
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

A method and apparatus, using a computer model, to control a manufacturing or distribution process, which determines a demand forecast by using an optimized historical weighting factor, determines an upper and a lower bound of a planned inventory by explicitly accounting for the customer order lead time, and computes a production schedule at predetermined intervals to maintain an actual inventory between the upper and lower bounds of the planned inventory.

Claims

1. A computer implemented method of inventory control of a manufacturing or distribution process using a computer model of the manufacturing or distribution process, which comprises the steps of:

(a) determining a demand forecast by using an optimized historical weighting factor,

(b) determining an upper and a lower bound of a planned inventory by explicitly accounting for the customer order lead time, and

(c) computing a production schedule at predetermined intervals to maintain an actual inventory between the upper and lower bounds of the planned inventory.

2. The method of claim 1 further comprising explicitly accounting for a cost of production changeover and an inventory carrying cost.

3. The method of claim 1, where in step (c), a demand forecast is computed by:

(i) dividing the shipment data into predetermined intervals,

(ii) using a first predetermined number of intervals as a first history period and a second predetermined number of intervals as a second history period,

(iii) using the second history period to compute predicted demand for the intervals of the first history period,

(iv) computing the error between the predicted demand and the actual demand for the intervals of the first history period to determine, and

(v) determining an historical weighting factor F, said factor being between 0 and 1, by comparing the predicted demand with the actual demand for each interval of the first history period, the weighting factor being optimized by a recursive method of computation.

4. The method of claim 3 where the weighting factor F is determined such that the mean average deviation of the difference between the actual demand and the predicted demand is minimized.

5. The method of claim 3 where the upper bound of the planned inventory is computed as the sum of a cycle stock and a safety stock, where the cycle stock is computed using the predicted demand and the historical weighting factor F and the safety stock is computed using a method wherein a period of risk value is replaced by the difference of the period of risk and a customer order lead time.

6. The method of claim 3 where the lower bound of the planned inventory is equal to the safety stock, where the safety stock is computed using a method wherein the period of risk value is replaced by the difference of the period of risk and the customer order lead time.

7. The method of claims 5 and 6 where the customer order lead time is a single value.

8. The method of claims 5 and 6 where the customer order lead time is a Gaussian distribution function.

9. The method of claims 5 and 6 where the customer order lead time is a Poisson distribution function.

10. The method of claims 5 and 6 where the customer order lead time is a probability distribution function determined from historical data.

11. The method of claims 5 and 6 where the period of risk is a single value.

12. The method of claims 5 and 6 where the period of risk is a Gaussian distribution function.

13. The method of claims 5 and 6 where the period of risk is a Poisson distribution function.

14. The method of claims 5 and 6 where the period of risk is a probability distribution function determined from historical data.

15. The method of claims 5 and 6 where the upper and lower bounds of the planned inventory are selected so that sum of cost of production changeovers and inventory carrying cost is minimized.

18. A data structure generated by a method of any of claims 1-17.

19. A machine having a memory which contains a data structure for the control of a manufacturing and distribution process by performing the method of any of claims 1, 3, 5, 6, or 16.

20. A data processing system executing an application program for controlling a manufacturing and distribution process, containing a data structure, the data structure being formed by the method of any of claims 1, 3, or 16.

16. A method of inventory control of a manufacturing or distribution process comprising:

(a) computing a production schedule that reads current inventory from an inventory tracking system, reads the open orders from an order entry transaction system, reads invoiced shipments from the transaction system,

(b) at pre-determined intervals regenerating a demand forecast, wherein

(i) the demand forecast is computed by dividing the shipment data into predetermined intervals,

(ii) designating a first predetermined number of intervals as a first history period and designating a second predetermined number of intervals as a second history period,

(iii) using the second history period to compute predicted demand for the intervals of the first history period,

(iv) using the second history period to compute the error between the predicted demand for the intervals of the first history period and the actual demand for the intervals of the first history period to determine a historical weighting factor F, said factor being between 0 and 1, and

the weighting factor being determined by comparing the predicted demand with the actual demand for each interval of the first history period, the weighting factor being optimized by a recursive method of computation and determined such that the mean average deviation of the difference between the actual demand and the predicted demand is minimized, and

(c) at predetermined intervals recalculating the upper bound of the planned inventory, where the upper bound is computed as the sum of cycle stock and safety stock, wherein

(i) the cycle stock is computed using the predicted demand and the historical weighting factor F, and

(ii) the safety stock is computed using a method wherein the period of risk value is replaced by the difference of the period of risk and the customer order lead time, where

the period of risk may be a single value, a Gaussian distribution function, a Poisson distribution function, or a probability distribution function determined from historical data, where the customer order lead time may be a single value, a Gaussian distribution function, a Poisson distribution function, or a probability distribution function determined from historical data,

(d) at predetermined intervals recalculating the lower bound of the planned inventory, where the lower bound is equal to the safety stock, wherein

(i) the safety stock is computed using a method wherein the period of risk value is replaced by the difference of the period of risk and the customer order lead time,

where the period of risk may be a single value, a Gaussian distribution function, a Poisson distribution function, or a probability distribution function determined from historical data,

where the customer order lead time may be a single value, a Gaussian distribution function, a Poisson distribution function, or a probability distribution function determined from historical data.

17. The method of claim 16 where predicted inventory for a predetermined number of future intervals is computed from:

the sum of current inventory plus all production scheduled to be produced within the predetermined number of intervals, minus the sum of all open orders scheduled to be shipped within the predetermined number of intervals, minus the scaled forecast demand,

the scaled forecast demand being multiplied by the expectation value of the difference between the number of intervals and the customer order lead time.