Mahesh Chandra Pati

US Patent:

7197469, Mar 27, 2007

Filed:

Jun 26, 2001

Appl. No.:

09/891850

Inventors:

Sanjay R. Hegde - Essex Junction VT, US
Robert John Milne - Jericho VT, US
Robert A. Orzell - Essex Junction VT, US
Mahesh Chandra Pati - South Glastonbury CT, US
Shivakumar P. Patil - South Burlington VT, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 9/46

US Classification:

705 8

Abstract:

A method and system for resource rationing which employs decision rules for the optimal allocation of supply and capacity over time that satisfy two key requirements (a) being consistent with accepted operational objectives (e. g. low inventory, short lead times, prioritized allocation of supply and capacity) and (b) allowing for the timely computation of a feasible production schedule. The method and system is generally characterized in that it is able to divide each of the priority ranked scheduled releases (Material Requirements Planning (MRP)) into “N” separate and smaller sized scheduled releases where the priority of each of the “N” releases may be equal to the priority of the original release. The “N” separate and smaller sized scheduled releases are sorted according to priority and then used to determine an optimal supply schedule for allocating resources including component supply and assembly capacity.

US Patent:

20030065415, Apr 3, 2003

Filed:

Aug 22, 2001

Appl. No.:

09/934662

Inventors:

Sanjay Hegde - Essex Junction VT, US
Robert Milne - Jericho VT, US
Robert Orzell - Essex Junction VT, US
Mahesh Pati - South Glastonbury CT, US
Shivakumar Patil - South Burlington VT, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F019/00

US Classification:

700/100000, 700/107000

Abstract:

A method and system for efficient allocation of limited manufacturing resources over time to meet customer demand. At the enterprise planning level this typically requires determination of a feasible production schedule for an extended supply chain. The method and system utilizes a new and unique type of systematic decomposition based on both product and process considerations. This approach simultaneously reduces the model size (and therefore computation time) and increases modeling flexibility from strictly linear programming based decision making to include more general nonlinear programming characteristics.