Adeel Z Najmi

7685015, Mar 23, 2010

Feb 15, 2008

12/031975

Adeel Najmi - Plano TX, US
Dharmaraj Veerappanaicker - Lexington MA, US
Aseem Kohli - Melrose MA, US

i2 Technologies US, Inc. - Dallas TX

G06Q 10/00

705 10, 705 28, 235385

Locations that include supply, manufacturing, demand locations, and channels are defined. A demand is computed for each part at each location. An availability lead-time is estimated for each part at each location and for each part at each channel. A total landed cost is calculated for each part at each location and each channel. A lead-time demand is computed for each part at each location using the availability lead-times for the part. A demand over lead-time is computed for each part at each location using the availability lead-times for the part. A completely filled demand is determined from the lead-time demands and the stock levels, and a partially filled demand is determined from the lead-time demands and the stock levels. A coverage function is generated for the parts at the locations and the channels from the completely filled demand and the partially filled demand.

7711597, May 4, 2010

Mar 30, 2009

12/414085

Adeel Najmi - Plano TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 17/30
G06F 19/00

705 10, 705 28, 235385

In one embodiment, optimizing inventory includes accessing service level band sets. Each service level band set is associated with a policy group, and includes service level bands. Each service level band of a service level band set has a service level priority with respect to any other service level bands of the same service level band set. An inventory band set is determined for each service level band set. Each inventory band set includes inventory bands, where each inventory band satisfies a corresponding service level band assuming an unconstrained network. Each inventory band of an inventory band set has an inventory priority with respect to any other inventory bands of the same inventory band set. A feasible supply chain plan that satisfies the inventory band sets is generated in order of the inventory priorities until a constrained network is depleted.

7712072, May 4, 2010

Mar 30, 2009

12/414113

Adeel Najmi - Plano TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 9/00
G06F 17/30

717100, 705 10, 705 28

In one embodiment, optimizing inventory includes accessing service level band sets. Each service level band set is associated with a policy group, and includes service level bands. Each service level band of a service level band set has a service level priority with respect to any other service level bands of the same service level band set. An inventory band set is determined for each service level band set. Each inventory band set includes inventory bands, where each inventory band satisfies a corresponding service level band assuming an unconstrained network. Each inventory band of an inventory band set has an inventory priority with respect to any other inventory bands of the same inventory band set. A feasible supply chain plan that satisfies the inventory band sets is generated in order of the inventory priorities until a constrained network is depleted.

7721959, May 25, 2010

Jul 19, 2004

10/894248

Adeel Najmi - Plano TX, US

i2 Technologies US, Inc. - Dallas TX

G06Q 30/00

235385, 707 1, 705 28

In one embodiment, optimizing inventory includes accessing service level band sets. Each service level band set is associated with a policy group, and includes service level bands. Each service level band of a service level band set has a service level priority with respect to any other service level bands of the same service level band set. An inventory band set is determined for each service level band set. Each inventory band set includes inventory bands, where each inventory band satisfies a corresponding service level band assuming an unconstrained network. Each inventory band of an inventory band set has an inventory priority with respect to any other inventory bands of the same inventory band set. A feasible supply chain plan that satisfies the inventory band sets is generated in order of the inventory priorities until a constrained network is depleted.

7761903, Jul 20, 2010

Mar 13, 2009

12/403834

Koray Dogan - Boston MA, US
Adeel Najmi - Plano TX, US
Ramesh Raman - San Carlos CA, US
Praveen Upadhyay - Flower Mound TX, US

i2 Technologies US, Inc. - Dallas TX

G06F 17/00

726 1, 705 7

Determining a policy parameter for an entity of a supply chain includes establishing attributes of the entities of the supply chain. Attribute segments are established for each attribute, where an attribute segment includes one or more values of the corresponding attribute. Rules are formulated using the attribute segments to define policy groups, and policy parameters are assigned to each policy group. A policy group corresponding to an entity is identified in accordance with the rules. The policy parameters assigned to the identified policy group are determined and selected for the entity.

7788119, Aug 31, 2010

May 7, 2004

10/841003

Adeel Najmi - Plano TX, US
Vasudev Rangadass - Arlington TX, US
Ramesh Raman - San Carlos CA, US

i2 Technologies US, Inc. - Dallas TX

G06F 9/44
G06F 17/50

705 7, 705 8

In one embodiment, optimizing inventory for a supply chain includes generating an inventory plan for the supply chains. Execution of a supply chain plan associated with the inventory plan is initiated at the supply chain. The supply chain is monitored to generate metric values. A watchpoint triggered by a metric value is detected, and a cause of the triggered watchpoint is identified using a causal tree. The inventory plan is adjusted in response to the detected triggered watchpoint and in accordance with the identified cause, and the supply chain plan is adjusted in accordance with the adjusted inventory plan. Execution of the adjusted supply chain plan is initiated, and new metric values are measured to determine performance. The performance is evaluated, and the causal tree is updated in response to the evaluation.

7827049, Nov 2, 2010

Apr 29, 2004

10/836002

Koray Dogan - Boston MA, US
Adeel Najmi - Plano TX, US
Ramesh Raman - San Carlos CA, US

i2 Technologies US, Inc. - Dallas TX

G06F 9/44

705 7, 705 10

In one embodiment, estimating demand for a supply chain includes accessing a probability distribution for expected order lead time of the supply chain. The supply chain has nodes including a starting node and an ending node and a path from the starting node to the ending node. The probability distribution for expected order lead time describes ending node demand for the ending node versus order lead time. The path is divided into order lead time segments, and the order lead time segments are associated with the probability distribution for expected order lead time by associating each order lead home segment with a corresponding order lead time range of the probability distribution for expected order lead time. A demand percentage is estimated for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain. Each demand percentage describes a percentage of a total ending node demand associated with the corresponding order lead time segment.

7853462, Dec 14, 2010

Apr 29, 2004

10/836135

Koray Dogan - Boston MA, US
Adeel Najmi - Plano TX, US
Ramesh Raman - San Carlos CA, US

i2 Technologies US, Inc. - Dallas TX

G06F 9/44
G06F 17/30

705 7, 705 10

Optimizing inventory targets for nodes of a supply chain to satisfy a target customer service level may include accessing a supply chain model that has an assumed value for each of a number of inputs. An optimized inventory target is calculated according to the supply chain model to satisfy the target customer service level, and a measured actual customer service level and a measured actual value for each input are accessed. If the measured actual customer service level fails to satisfy the target customer service level, deviations between the measured actual and assumed values for each input are determined. An input for which the deviation is significant is identified to be a root cause of the failure. For a subsequent time period, using the deviation for the identified input as feedback, the assumed value for the identified input is adjusted, and a reoptimized inventory target is calculated to satisfy the target customer service level.