An Artificial Intelligence Platform for Asset Management Contributes to Better Decision-making Tools for Operations, Maintenance, and Utility Management

被引：0

作者：

Sen, D. ^{[1
,6
]}

Fashokun, A. ^{[2
]}

Angelotti, R. ^{[3
]}

Brooks, M. ^{[3
]}

Bhaumik, H. ^{[4
]}

Card, C. ^{[5
]}

Lodhi, A. ^{[1
]}

Godrej, A. ^{[1
]}

Chung, C. ^{[7
]}

机构：

[1] Virginia Tech, Occoquan Lab, 9408 Prince William St, Manassas, VA 20110 USA

[2] Washington Suburban Sanit Commiss, Laurel, MD USA

[3] Upper Occoquan Serv Author, Centreville, VA USA

[4] Arcadis, Fairfax, VA USA

[5] EBA, Laurel, MD USA

[6] Santa Clara Valley Water Dist, San Jose, CA 95118 USA

[7] Kayuga Solut, Irvine, CA USA

来源：

WATER ENVIRONMENT RESEARCH | 2018年 / 90卷 / 04期

关键词：

asset management; artificial intelligence; process models; wastewater; reuse;

D O I：

10.2175/106143017X15131012152762

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

An Artificial Intelligence system was developed and implemented for water, wastewater, and reuse plants to improve management of sensors, short and long-term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it can simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.

引用

页码：355 / 375

页数：21

共 34 条

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