Projected supply planning matching assets with demand in microelectronics manufacturing

• US 6,049,742 A
• Filed: 09/26/1997
• Issued: 04/11/2000
• Est. Priority Date: 09/26/1997
• Status: Expired due to Term

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: O'Neil, John P., Tang, Xueqing, Wong, Yuchung, Orzell, Robert A., Milne, Robert J.
• Primary Examiner(s): Grant, William
• Assistant Examiner(s): Rao, Sheela S.
• Application Number:
  US08/938,764
• Time in Patent Office: 928 Days
• Field of Search: 700/95, 700/97, 700/90, 700/99, 700/100-213, 705/7, 705/8-28
• US Class Current: 700/99
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A computer-implemented decision-support tool serves as a solver to generate a projected supply planning (PSP) or estimated supply planning (ESP) match between existing assets and demands across multiple manufacturing facilities within the boundaries established by the manufacturing specifications and process flows and business policies to determine what supply can be provided over what time-frame by manufacturing and establishes a set of actions or guidelines for manufacturing to incorporate into their manufacturing execution system to ensure that the delivery commitments are met in a timely fashion. The PSP or ESP tool resides within a data provider tool that pulls the required production and distribution information. PSP matching is driven directly by user-supplied guidelines on how to flow or flush assets "forward" to some inventory or holding point. After the supply plan is created, the analyst compares this plan against an expected demand profile.

Claims

1. A computer-implemented decision-support method to generate a projected supply planning (PSP) or estimated supply planning (ESP) match between existing assets and demands within boundaries established by manufacturing specifications and process flows and business policies using manufacturing specification and calendar information accessed by material requirements planning (MRP) matching tools to ensure synchronization between these matching tools to determine what supply can be provided over what time-frame, the method comprising the steps of:

selecting user provided part numbers of interest and modifying a user provided production specification information to reflect this selection;

specifying substitution rules, wherein the substitution rules allow one part to be substituted for another part;

specifying a start date and shutdown dates;

optionally allowing a user to modify any due dates for projected receipts;

specifying a "from/to" split of allocation fractions to reflect business plans, and to allow the projection of assets across multiple bills of material levels;

selectively inputting new starts for an individual date and dates propagated across a span of dates;

executing a forward-flush solver to generate a projected or estimated supply plan;

aggregating the supply plan and required starts into user-defined time buckets;

creating and analyzing explanation reports of the solution generated by the forward flush solver; and

comparing the supply plan with the required demands to assess a "fitness" of the plan relative to meeting demand.

2. The computer-implemented decision-support method as recited in claim 1, wherein said method further comprising the steps of:

optionally permitting the user to modify the receipt date for each work in progress (WIP) unit;

evaluating a current receipt date for each WIP unit and modifying the receipt date as necessary; and

evaluating a current receipt date for each WIP unit with a current status of manufacturing and modifying the receipt date as necessary.

3. The computer-implemented decision-support method as recited in claim 1 further comprising the steps of:

optionally permitting the user to specify future starts;

specifying a start quantity for a part number for one day;

specifying a start quantity for a part number for a range of days; and

propagating the start quantity to each work day.

4. The computer-implemented decision-support method as recited in claim 1, wherein said method further comprising the steps of:

identifying all "from/to" part number relationships;

inputting default splitting fractions that generate a uniform distribution; and

permitting the user to optionally modify the from/to splitting of allocation fractions.

5. The computer-implemented decision-support method as recited in claim 1, wherein said method performs a PSP forward-flush solution and further comprises the steps of:

calculating a reverse-low-level-code (RLLC) for each part number;

establishing a relative priority of each part, or process to produce a part, within a specific RLLC group using the user-specified priority values;

establishing an order in which parts are processed in forward flush where the order is based on ascending RLLC and ascending order within the RLLC group;

calculating a stock quantity and date for each user-specified start by appropriately applying yield, conversion factor, capacity, cycle time, and shutdown day list;

establishing an initial asset list from inventory, projected receipts, and calculated stock quantity and date for user-specified starts for each part consisting of part identification, quantity, and stock date;

applying substitution rules for parts with RLLC of one by changing its part number or name to the substitute for part name;

allocating the projected supplies or assets for parts in RLLC group one to be component supplies to produce other parts, based on user-specified "from/to" split of allocation fractions and bin split information;

determining all possible starts over time for parts or the process to produce the part that belong to RLLC group two by comparing available component supplies or quantities against component requirement values;

updating current asset list, adjusting for the parts in RLLC group one that were consumed and the parts in RLLC group two that were created, and then applying substitution rules for parts with RLLC of two and greater and repeating the steps of allocating, determining, calculating and updating until all RLLCs have been exhausted; and

creating a manufacturing release or start, final asset resting place, intermediate asset position, and allocation file.

6. The computer-implemented decision-support method as recited in claim 1, wherein said method includes a step of aggregating final supply by user-specified time buckets.

7. The computer-implemented decision-support method as recited in claim 1, wherein said method includes a step of aggregating all required manufacturing releases or starts by user-specified time buckets.