Best can do matching of assets with demand in microelectronics manufacturing

• US 5,971,585 A
• Filed: 09/09/1997
• Issued: 10/26/1999
• Est. Priority Date: 09/09/1997
• Status: Expired due to Term

• Current Assignee: GlobalFoundries, Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Reid, Robert L., Gokhale, Anand R., Li, Shuchen, Orzell, Robert A., Milne, Robert J., Tang, Xueqing, Dangat, Geetaram S., Yen, Chih-Kuan
• Primary Examiner(s): Grant, William
• Assistant Examiner(s): Eissmann, Peter W.
• Application Number:
  US08/926,131
• Time in Patent Office: 777 Days
• Field of Search: 364/468.01, 364/468.03, 364/468.05, 364/468.08, 364/468.06
• US Class Current: 700/102
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A computer implemented decision support tool serves as a solver to generate a best can do (BCD) match between existing assets and demands across multiple manufacturing facilities within boundaries established by manufacturing specifications and process flows and business policies to determine which demands can be met in what time frame by microelectronics (wafer to card) or related (for example disk drives) manufacturing and establishes a set of actions or guidelines for manufacturing to incorporate into their manufacturing execution system to insure the delivery commitments are met in a timely fashion. The BCD tool has six major components, a material resource planning explode or "backwards" component, an optional STARTS evaluator component, an optional due date for receipts evaluator, an optional capacity available versus needed component, an implode "forward" or feasible plan component, and a post processing algorithm.

Claims

1. A computer implemented decision support method which intelligently matches assets with demand to create a best can do (BCD) match to determine which demands can be met in what time frame and identifies production necessary to meet demand comprising the steps of:

inputting an input file of requested demands, including customer identification, type of part, quantity, date, and priority;

receiving the input file and executing a BCD explosion component across multiple bills of material levels to create a required STARTS file for parts having no further bill of material (BOM), a file of work-in-progress (WIP) or receipts with need dates, a file of required capacity to meet demands, and clues for a BCD implode component;

accessing the STARTS file, the WIP and receipts file and the required capacity file and executing the BCD implode component across multiple bills of material levels to create a match between assets and demands and hence a BCD solution; and

generating a supply chain analysis report to explain the BCD solution that allows a user to trace how demand is satisfied across multiple bills of material levels.

2. The computer implemented decision support method recited in claim 1 wherein the BCD explode component comprises the steps of:

backward exploding from independent demand through a bill of materials (BOM) one low level code at a time using material requirements planning (MRP) logic;

keeping demand for each demand class separate and passing classification information backwards from independent demand through each level of dependent demand;

executing a separate optimization for binned parts to minimize required starts;

spreading starts to avoid capacity over utilization; and

storing propagated demand class, need date, and required starts information for use by other component systems of the decision support method.

3. The computer implemented decision support method recited in claim 1 wherein prior to executing the BCD implode component, the method further comprises the steps of:

adjusting the required STARTS file to modify start dates and/or quantity of one or more items in the STARTS file;

adjusting the WIP file to modify projected date and/or quantity of one or more items in the WIP file; and

allowing a user to adjust the capacity available file to modify projected available quantities.

4. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the STARTS file and further comprising the steps of:

displaying recommended starts relative to available capacity; and

receiving an input from a user modifying the starts.

5. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the STARTS file and further comprising the steps of:

displaying recommended starts relative to a current business plan; and

receiving an input from a user modifying the starts.

6. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the WIP file and further comprising the steps of:

displaying current receipt date for each unit with the need date; and

receiving an input from a user modifying the receipt date.

7. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the WIP file and further comprising the steps of:

displaying current receipt date for each WIP unit with a current status of manufacturing; and

receiving an input from a user modifying the receipt date.

8. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the capacity available file and further comprising the steps of:

displaying current capacity available information for each of a plurality of time buckets and resources with a calculated capacity required; and

receiving an input from a user modifying the capacity available information.

9. The computer implemented decision support method recited in claim 3 wherein the method includes a user interactive component to permit the user to modify items in the capacity available file and further comprising the steps of:

displaying current capacity available information with a current status of manufacturing; and

receiving an input from a user modifying the capacity available information.

10. The computer implemented decision support method recited in claim 1 including a BCD supply chain analysis reporting component comprising the steps of:

determining all increases and decreases in assets from implode solution files;

creating a needs file from a customer shipment file;

assigning assets to meet needs;

determining component needs from the BOM information;

assigning assets to the component needs; and

sorting the assets and needs files to match logically connected records.

11. The computer implemented decision support method recited in claim 1 wherein the BCD implode component comprises the steps of:

selecting between an implode solver based on heuristic decision technology or an implode solver based on linear programming (LP) technology; and

executing the selected solver.

12. The computer implemented decision support method recited in claim 11 wherein said implode solver based on heuristic decision technology comprises the steps of:

sorting all starts by demand class, date, and part number;

resetting all starts having a start date prior to the user specified start date;

resetting starts to be capacity feasible by giving priority to starts on a first come, first served basis based on a pre-emptive priority of demand class and date;

imploding each part number in reverse low level code order where priority is given to locations which ship to other locations;

gathering all assets;

calculating all possible starts by examining the starts file and available components; and

allocating supply to customers for further implosion based on demands and priorities established by the explode component.

13. The computer implemented decision support method recited in claim 12 wherein the implode solver based on heuristic decision technology further comprises the steps of:

adjusting starts for capacity considerations; and

calculating a projected to-stock date appropriately accounting for shutdown days.

14. The computer implemented decision support method recited in claim 11 wherein said implode solver based on LP technology comprises the steps of:

resetting all starts having a start date in the past to a user specified start date;

resetting starts to be capacity feasible by giving priority to starts on a first come, first served basis based on a pre-emptive priority of demand and date;

adjusting cycle time information and calculating time bucket production split information for user specified time buckets so that the adjusted cycle time information and time bucket production split information may be fed into the implode solver based on LP technology;

creating a computational form of the equations in an LP model called an LP data matrix;

instantiating the LP data matrix with the current production specification information; and

passing the instantiated LP data matrix to an LP solver and executing the LP solver to generate a BCD solution.

15. The computer implemented decision support method recited in claim 14 wherein said implode solver based on LP technology further comprises the steps of:

determining if the user is using a fixed starts option or an open starts option; and

placing the starts as entries in the WIP and receipts file and adjusting capacity if the user has selected the fixed starts option.

16. The computer implemented decision support method recited in claim 15 wherein said implode solver based on LP technology further comprises the step of turning production splitting off if that option is requested by the user.

17. The computer implemented decision support method recited in claim 14 wherein said implode solver based on LP technology further comprises the step of adjusting an inventory holding cost objective function coefficient to eliminate unwanted time bucket side effect of overbuilding.

18. The computer implemented decision support method recited in claim 14 wherein said implode solver based on LP technology further comprises the step of adjusting a production cost objective function coefficient to eliminate unwanted time bucket side effect of late delivery.

19. The computer implemented decision support method recited in claim 14 wherein the equations in the LP model of said implode solver based on LP technology represent manufacturing specifications, business policies, and business guidelines and include material balance, capacity balance, capacity balance equations to insure fixed production ratios between multiple processes producing a same part is maintained, back order conservation, sourcing constraints which permits the user to control how much supply a location receives from each manufacturing plant or distribution center, a complex objective function which supports multiple demand classes, weighted trade-offs between demand classes, inventory holding cost coefficients to support trade-offs between on-time delivery and inventory, production cost coefficients to permit the user to specify the relative preference of production options, and the flexibility to specify objective function coefficients to offset the unwanted side effects of overbuilding and late delivery.