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公开(公告)号:US20180075399A1
公开(公告)日:2018-03-15
申请号:US15262832
申请日:2016-09-12
Applicant: Ecolab USA Inc.
Inventor: Ashish Agarwal , Kenneth R. Hecimovich , Raymond H. Perdue , David A. Ambrose , Chen Yao , Michael K. Antenore
CPC classification number: G06Q10/083 , C02F1/42 , C02F2209/05 , C02F2209/40 , C02F2209/44 , C02F2303/14 , G01F1/00 , G01F1/007 , G01F23/0076 , G06Q10/1097
Abstract: Systems for analyzing and monitoring deionization tank system performance in a fluid flow system and generating delivery schedules for servicing deionization tanks can include a conductivity sensor and a fluid flow meter. Data regarding the amount and conductivity of fluid flowing through the deionization tank system can be used to predict a remaining capacity of the deionization tank system. A central server can determine the remaining capacity of deionization tank systems at a plurality of service locations. The central server can generate a delivery schedule for servicing deionization tank systems at each of the plurality of service locations based on the determined remaining capacities. Other parameters can be used to optimize efficiency of the delivery schedule while meeting the needs of each of the service locations.
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公开(公告)号:US11017344B2
公开(公告)日:2021-05-25
申请号:US15262832
申请日:2016-09-12
Applicant: Ecolab USA Inc.
Inventor: Ashish Agarwal , Kenneth R. Hecimovich , Raymond H. Perdue , David A. Ambrose , Chen Yao , Michael K. Antenore
Abstract: Systems for analyzing and monitoring deionization tank system performance in a fluid flow system and generating delivery schedules for servicing deionization tanks can include a conductivity sensor and a fluid flow meter. Data regarding the amount and conductivity of fluid flowing through the deionization tank system can be used to predict a remaining capacity of the deionization tank system. A central server can determine the remaining capacity of deionization tank systems at a plurality of service locations. The central server can generate a delivery schedule for servicing deionization tank systems at each of the plurality of service locations based on the determined remaining capacities. Other parameters can be used to optimize efficiency of the delivery schedule while meeting the needs of each of the service locations.
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