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Zhennong W Wang

from Bellevue, WA
Age ~63
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Also known as:
Zhennong J Wang, G Wang
Phone and address:
14206 SE 63Rd St, Bellevue, WA 98006
(425) 351-1575
Related to:
Yibai Hu, 78Man Siu WanJian H Wang, 58Chang Wang, 47Tong Wang, 62Ping Wang ChihpingJack A WangDong Wang, 57Chihping Ping Wangchih, 62Kuokhong Wong, 47
Connected to:
Adele R Wang, 107Aiyuan Wang, 52Akiet Wang, 74Alene P Wang, 52Amanda K Wang, 46Amei Wang, 61Amity H Wang, 70Amy Wang, 59Anastasia S Wang, 84Ange Wang, 34

Zhennong Wang Phones & Addresses

  • 14206 SE 63Rd St, Bellevue, WA 98006 (425) 351-1575
  • 16016 184Th St, Renton, WA 98058
  • 1517 W 9Th St #24, Laurence, KS 66044 (785) 842-9230
  • 1301 W 24Th St #D19, Laurence, KS 66046 (842) 842-9230
  • 1732 24Th St, Laurence, KS 66046 (785) 843-8491
  • 1732 W 24Th St #37, Laurence, KS 66046 (785) 842-9230
  • Lawrence, KS
  • Kiona, WA

Publications

Us Patents

Aircraft Cabin Noise Exposure Analysis

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US Patent:
20110043382, Feb 24, 2011
Filed:
Aug 18, 2009
Appl. No.:
12/543402
Inventors:
Zhennong Wang - Renton WA, US
International Classification:
G08B 21/00
US Classification:
340945
Abstract:
Systems and methods for aircraft cabin noise analysis are disclosed. In one embodiment, a method includes receiving a first request for an aircraft cabin noise analysis, wherein the request comprises a plurality of flight parameters associated with a first flight mission, retrieving, from a computer readable memory, a plurality of noise parameters associated with the plurality of flight parameters for the first flight mission, determining a total noise exposure parameter associated with the first flight mission, generating an output comprising the total noise exposure on a user interface, and generating a warning on a user interface when the total noise exposure exceeds a threshold. In some embodiments, the monitored system may be implemented in a computing system or as logic instructions recorded on a computer readable medium.

Predictive Part Maintenance

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US Patent:
20220281618, Sep 8, 2022
Filed:
May 23, 2022
Appl. No.:
17/751647
Inventors:
- Chicago IL, US
Zhennong WANG - Bellevue WA, US
International Classification:
B64F 5/60
G06F 30/20
G07C 5/00
G07C 5/08
Abstract:
The present disclosure provides for predictive part maintenance by generating a reliability curve for an aircraft based on historic removals; setting a removal threshold on the reliability curve; tracking an installation of a given instance of the aircraft part into a given aircraft; tracking a number of cycles of the given instance of the aircraft part based on operations of the given aircraft in which the given instance of the aircraft part is installed; and in response to the number of cycles of the given instance of the aircraft part satisfying the removal threshold, transmitting a service alert to an operator of the given aircraft.

Fleet Assignment Based On An Aircraft Availability Metric

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US Patent:
20230040135, Feb 9, 2023
Filed:
Aug 4, 2021
Appl. No.:
17/444436
Inventors:
- Chicago IL, US
Zhennong Wang - Bellevue WA, US
International Classification:
G06Q 10/06
G06Q 10/08
G06Q 10/00
B64F 5/60
Abstract:
A method of managing in-service operation of a fleet of aircraft is provided that includes generating a schedule of flights through an air transportation network that includes airports, and that includes direct flight routes or flight connections between the airports. The method includes performing a fleet assignment of the fleet of aircraft to the schedule of flights based on availability metric values for respective aircraft of the fleet of aircraft, and dispatching the fleet of aircraft serve the schedule of flights to according to the fleet assignment. In this regard, performing the fleet assignment includes, for an aircraft of the fleet of aircraft, accessing reliability metric values for parts of the aircraft. Availability scores for the aircraft are determined based on the reliability metric values from respective ones of the data sources, and the availability scores are combined to determine an availability metric value for the aircraft.

Predictive Part Maintenance

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US Patent:
20200354086, Nov 12, 2020
Filed:
May 8, 2019
Appl. No.:
16/406827
Inventors:
- Chicago IL, US
Zhennong WANG - Bellevue WA, US
International Classification:
B64F 5/60
G07C 5/08
G07C 5/00
G06F 17/50
Abstract:
The present disclosure provides for predictive part maintenance by generating a reliability curve for an aircraft based on historic removals; setting a removal threshold on the reliability curve; tracking an installation of a given instance of the aircraft part into a given aircraft; tracking a number of cycles of the given instance of the aircraft part based on operations of the given aircraft in which the given instance of the aircraft part is installed; and in response to the number of cycles of the given instance of the aircraft part satisfying the removal threshold, transmitting a service alert to an operator of the given aircraft.

Vehicle Part Reliability Determination System And Method

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US Patent:
20180342116, Nov 29, 2018
Filed:
May 25, 2017
Appl. No.:
15/604713
Inventors:
- Chicago IL, US
Zhennong Wang - Bellevue WA, US
Assignee:
THE BOEING COMPANY - Chicago IL
International Classification:
G07C 5/08
Abstract:
A part reliability determination system and method are used to determine a reliability of at least one part of a vehicle. The reliability determination system and method include a part life prediction control unit that determines a remaining life of the part(s) based on current life data of the part(s) in relation to a part life distribution related to the part(s).

Systems And Methods For Detecting Aircraft Maintenance Events And Maintenance Intervals

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US Patent:
20150051786, Feb 19, 2015
Filed:
Aug 15, 2013
Appl. No.:
13/967729
Inventors:
- seal Beach CA, US
Zhennong Wang - Bellevue WA, US
Assignee:
The Boeing Company - Seal Beach CA
International Classification:
B64F 5/00
US Classification:
701 294
Abstract:
A computing device for use in detecting maintenance events and maintenance intervals is provided. The computing device is configured to receive aircraft usage data for at least one carrier, identify at least one potential maintenance event in the usage data, identify at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to a second aircraft of the at least one carrier during each potential maintenance event, determine an indicator used by each carrier for scheduling maintenance events, determine a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.
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Zhennong W Wang from Bellevue, WA, age ~63 Get Report