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公开(公告)号:US20240333739A1
公开(公告)日:2024-10-03
申请号:US18192812
申请日:2023-03-30
发明人: Bhavna Agrawal , Robert Jeffrey Baseman , Jeffrey Owen Kephart , Anuradha Bhamidipaty , Elham Khabiri , Yingjie Li , Srideepika Jayaraman
CPC分类号: H04L63/1425 , H04L41/16
摘要: Detecting and mitigating anomalous system behavior by providing a machine learning model comprising a knowledge graph depicting system entity relationships, and modeling behavioral correlations among system entities according to historical time-series data, receiving real-time time-series data for the system, detecting an anomalous system behavior in a system locale, according to the real-time time-series data, according to the machine learning model and multivariate sensor metrics, diagnosing the anomalous system behavior according to an upstream portion of the knowledge graph and a statistical behavior model for the system locale, and mitigating the anomalous behavior by deriving a recommended action according to the anomalous behavior and generating a work order to implement the recommended action.
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公开(公告)号:US11301794B2
公开(公告)日:2022-04-12
申请号:US16005373
申请日:2018-06-11
发明人: Yada Zhu , Xuan Liu , Brian Leo Quanz , Ajay Ashok Deshpande , Ali Koc , Lei Cao , Yingjie Li
摘要: A computer implemented method and system of calculating labor resources for a network of nodes in an omnichannel distribution system. Input parameters are received from a computing device of a user. Historical data related to a network of nodes is received, from a data repository. A synthetic scenario is determined based on the received input parameters and the historical data. For each node, key parameters are identified and set based on a multi-objective optimization, wherein the multi-objective optimization includes a synthetic inventory allocation to the node based on the synthetic scenario. A synthetic labor efficiency is determined for the node from the synthetic scenario. Labor resources are calculated based on the synthetic inventory allocation for the synthetic scenario. The labor resources of at least one node are displayed on a user interface of a user device.
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公开(公告)号:US11138552B2
公开(公告)日:2021-10-05
申请号:US15836814
申请日:2017-12-08
发明人: Lei Cao , Ajay Ashok Deshpande , Ali Koc , Yingjie Li , Xuan Liu , Brian Leo Quanz , Yada Zhu
IPC分类号: G06Q10/08
摘要: Techniques for facilitating estimation of node processing capacity values for order fulfillment are provided. In one example, a computer-implemented method can comprise: generating, by a system operatively coupled to a processor, a current processing capacity value for an entity; and determining, by the system, a future processing capacity value for the entity based on the current processing capacity value and by using a future capacity model that has been explicitly trained to infer respective processing capacity values for the entity. The computer-implemented method can also comprise fulfilling an order of an item, by the system, based on the future processing capacity value.
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公开(公告)号:US11074544B2
公开(公告)日:2021-07-27
申请号:US16445568
申请日:2019-06-19
发明人: Ajay A. Deshpande , Saurabh Gupta , Arun Hampapur , Alan J. King , Ali Koc , Yingjie Li , Xuan Liu , Christopher S. Milite , Brian L. Quanz , Chek Keong Tan , Dahai Xing , Xiaobo Zheng
IPC分类号: G06Q50/28 , G06Q10/06 , G06Q30/00 , G06Q10/08 , G06Q30/02 , G06N20/00 , G06F16/14 , G06F16/182 , G06F16/17 , G06F16/23 , G06N5/00 , G06F3/0482 , G06F3/0484 , G06Q30/06 , H04L12/26 , G06N5/04
摘要: Evaluating node fulfillment capacity in node order assignment by receiving a current order for node order assignment, retrieving data of each node, the retrieved data of each node including current capacity utilization, determining a probability of backlog on an expected ship date of each node, the probability of backlog being based on the retrieved current capacity utilization, determining a capacity utilization cost of each node based on the probability of backlog on the expected ship date, automatically calculating a fulfillment cost of each node of the current order based on the capacity utilization cost, identifying one or more nodes for the current order with the lowest fulfillment cost and automatically generating a node order assignment assigning the current order to one of the one or more nodes with the lowest fulfillment cost.
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公开(公告)号:US10679178B2
公开(公告)日:2020-06-09
申请号:US14955509
申请日:2015-12-01
发明人: JoAnn Piersa Brereton , Ajay Ashok Deshpande , Arun Hampapur , Miao He , Alan Jonathan King , Xuan Liu , Christopher Scott Milite , Jae-Eun Park , Joline Ann Villaranda Uichanco , Songhua Xing , Steve Igrejas , Hongliang Fei , Vadiraja Ramamurthy , Yingjie Li , Kimberly D. Hendrix , Xiao Bo Zheng
摘要: A simulator is configured to simulate the fulfillment of orders by nodes. Each node has an inventory of products and is capable of shipping the products to destinations in response to receipt of a corresponding order. The simulator divides the nodes into groups and assigns a different priority to each group based on input provided by a user to the simulator to generate an ordered sequence of priorities. The simulator maintains safety stock data corresponding to each node that indicates minimum quantities of the products required to be present at the corresponding node. The simulator selects a current priority of the sequence and next simulates a first group among the groups having the current priority fulfilling the orders for a given product among the products while a quantity of the given product at each of the nodes in the first group is below the minimum quantity in the corresponding safety stock data.
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公开(公告)号:US10650438B2
公开(公告)日:2020-05-12
申请号:US15406323
申请日:2017-01-13
发明人: Shyh-Kwei Chen , Ajay A. Deshpande , Saurabh Gupta , Arun Hampapur , Ali Koc , Yingjie Li , Dingding Lin , Xuan Liu , Christopher S. Milite , Brian L. Quanz , Chek Keong Tan , Dahai Xing , Xiaobo Zheng
摘要: A system, method and computer program product for continuously tracking business performance impact of order sourcing systems and algorithms that decide how ecommerce orders should be fulfilled by assigning the items of the order to nodes in a fulfillment network such as stores, distribution centers, and third party logistics—to provide automatic root cause analysis and solution recommendations to pre-defined business problems arising from KPI monitoring. A Business Intelligence (BI) dashboard architecture operates with: 1) a monitoring module that continuously monitors business KPIs and creates abnormality alerts; and 2) a root cause analysis module that is designed specifically for each business problem to give real time diagnosis and solution recommendation. The root cause analysis module receives the created alert, and triggers conducting a root cause analysis at an analytics engine. The BI dashboard and user interface enables visualization of the KPI performance and root cause analysis results.
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公开(公告)号:US10296932B2
公开(公告)日:2019-05-21
申请号:US15153088
申请日:2016-05-12
发明人: Ajay A. Deshpande , Arun Hampapur , Ali Koc , Yingjie Li , Xuan Liu , Brian L. Quanz , Dahai Xing
摘要: A method is provided for selecting eligible nodes and item assignments to those nodes for fulfillment based on satisfaction of a reward constraint and fulfillment cost. This method includes several steps, including determining by a computer processor of the fulfillment engine whether each of the plurality of assignments to the plurality of nodes satisfies a reward constraint based on a first customer loyalty reward level of the plurality of customer loyalty reward levels, identifying by a computer processor of the fulfillment engine one or more satisfactory assignments to nodes by identifying which of the one or more assignments is both associated with an order fulfillment cost that is less than the maximum fulfillment cost and satisfies the reward constraint and automatically generating by a computer processor of the fulfillment engine a node order assignment assigning the current order to the one or more satisfactory nodes.
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公开(公告)号:US20180082355A1
公开(公告)日:2018-03-22
申请号:US15827458
申请日:2017-11-30
发明人: Shyh-Kwei Chen , Ajay A. Deshpande , Saurabh Gupta , Arun Hampapur , Ali Koc , Yingjie Li , Dingding Lin , Xuan Liu , Christopher S. Milite , Brian L. Quanz , Chek Keong Tan , Dahai Xing , Xiaobo Zheng
CPC分类号: G06Q30/0635 , G06Q10/06393
摘要: A method for continuously tracking business performance impact of order sourcing systems and algorithms that decide how ecommerce orders should be fulfilled by assigning the items of the order to nodes in a fulfillment network such as stores, distribution centers, and third party logistics—to provide automatic root cause analysis and solution recommendations to pre-defined business problems arising from KPI monitoring. A Business Intelligence (BI) dashboard architecture operates with: 1) a monitoring module that continuously monitors business KPIs and creates abnormality alerts; and 2) a root cause analysis module that is designed specifically for each business problem to give real time diagnosis and solution recommendation. The root cause analysis module receives the created alert, and triggers conducting a root cause analysis at an analytics engine. The BI dashboard and user interface enables visualization of the KPI performance and root cause analysis results.
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公开(公告)号:US20170206592A1
公开(公告)日:2017-07-20
申请号:US15406323
申请日:2017-01-13
发明人: Shyh-Kwei Chen , Ajay A. Deshpande , Saurabh Gupta , Arun Hampapur , Ali Koc , Yingjie Li , Dingding Lin , Xuan Liu , Christopher S. Milite , Brian L. Quanz , Chek Keong Tan , Dahai Xing , Xiaobo Zheng
CPC分类号: G06Q30/0635 , G06Q10/06393
摘要: A system, method and computer program product for continuously tracking business performance impact of order sourcing systems and algorithms that decide how ecommerce orders should be fulfilled by assigning the items of the order to nodes in a fulfillment network such as stores, distribution centers, and third party logistics—to provide automatic root cause analysis and solution recommendations to pre-defined business problems arising from KPI monitoring. A Business Intelligence (BI) dashboard architecture operates with: 1) a monitoring module that continuously monitors business KPIs and creates abnormality alerts; and 2) a root cause analysis module that is designed specifically for each business problem to give real time diagnosis and solution recommendation. The root cause analysis module receives the created alert, and triggers conducting a root cause analysis at an analytics engine. The BI dashboard and user interface enables visualization of the KPI performance and root cause analysis results.
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10.
公开(公告)号:US20170206591A1
公开(公告)日:2017-07-20
申请号:US15154119
申请日:2016-05-13
发明人: Ajay A. Deshpande , Saurabh Gupta , Arun Hampapur , Alan J. King , Ali Koc , Yingjie Li , Xuan Liu , Christopher S. Milite , Brian L. Quanz , Chek Keong Tan , Dahai Xing , Xiaobo Zheng
CPC分类号: G06Q10/08345 , G06F3/0482 , G06F3/04847 , G06F16/148 , G06F16/1734 , G06F16/183 , G06F16/1844 , G06F16/2365 , G06N5/003 , G06N5/04 , G06N5/045 , G06N20/00 , G06Q10/06315 , G06Q10/0633 , G06Q10/06375 , G06Q10/083 , G06Q10/0833 , G06Q10/0838 , G06Q10/087 , G06Q10/0875 , G06Q30/0201 , G06Q30/0206 , G06Q30/0283 , G06Q30/0284 , G06Q30/0635 , H04L43/0876 , H04L43/0882 , H04L43/16
摘要: A method and system for considering customized capacity utilization cost in node order fulfillment. The method includes receiving by a customized capacity utilization cost module an electronic record of a current order. The method includes retrieving data of a plurality of nodes and calculating an actual capacity utilization. The method includes automatically converting the actual capacity utilization of each node of the plurality of nodes and a predetermined maximum amount of cost to balance capacity utilization across the plurality of nodes into a customized capacity utilization cost, and transmitting the customized capacity utilization cost to an order fulfillment engine. The method includes receiving by the order fulfillment engine the current order, the processing cost data, and the customized capacity utilization cost. The method includes automatically calculating a fulfillment cost and identifying a node-order assignment with the lowest fulfillment cost.
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