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Automated Decisions

By inferring and producing simple predictive if-then logic rules that can be easily integrated with existing infrastructure and software applications, Rulex enables the automation of many of the decisions currently being made by business and operations workers.

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Rulex examines examples of correct past decisions, discovers the logic behind those decisions, and uses that logic to evaluate new data to make optimum predictive decisions.  Rulex’s conditional logic rules can be easily integrated with existing business and control applications systems to enable automating thousands of predictive decisions formerly made by expert workers using BI reports and dashboards.

Example: Predictive Water Utility Pump Control

Rulex finds rules that experienced experts may already know but that junior people do not, allowing less experienced personnel to make more expert decisions.

And Rulex finds rules that even highly experienced personnel don’t know, allowing experts to be more productive and accurate, and to expose hidden risks and inefficiencies, and enable their remediation.

Condition 1 Condition 2 Condition 3 Output
Pressure (Pumping Station 8) > 49.7213 Flow (Pumping Station 19) > 419.058   Number of Pumps (Station 1) After 15 minutes = 0
Pressure (Pumping Station 7) <= 39.8308     Number of Pumps (Station 1) After 15 minutes = 1
Pressure (Pumping Station 6) > 41.6887 32.5025 < Pressure (Pumping Station 4) <= 40.7735 00:44:30.000 < time <= 05:20:30.000 Number of Pumps (Station 1) After 15 minutes = 1
Flow (Pumping Station 16) <= 260.562 Pressure (Pumping Station 7) <= 42.6721 Pressure (Pressure Point F) > 40.7815 Number of Pumps (Station 1) After 15 minutes = 1
20:06:30.000 < time <= 23:04:30.000     Number of Pumps (Station 1) After 15 minutes = 2
Pressure (Pumping Station 7) > 48.7331     Number of Pumps (Station 1) After 15 minutes = 3
423.126 < Flow (Pumping Station 3) <= 481.538 Pressure (Pumping Station 20) > 32.6889 05:29:30.000 < time <= 18:43:30.000 Number of Pumps (Station 1) After 15 minutes = 3
Flow (Pumping Station 7) > 373.63 Flow (Pumping Station 15) > 236.988 Pressure (Pumping Station 15) > 48.7424 Number of Pumps (Station 1) After 15 minutes = 4

Rulex replaces reactive human decisions with predictive automated ones.

In this example from a large European water utility, Rulex discovers the predictive rules for operating a network of pumping stations for optimum pressure delivery and electricity utilization.

Before Rulex, operations personnel used dashboards to monitor the network and, when certain events occurred, respond by executing control instructions based on their knowledge and experience.

After Rulex, these reactive decisions have been replaced by automated predictive logic in the SCADA system controlling the pumping network.  Rulex knows that certain conditions predict a future problem, and when they occur, Rulex issues the appropriate instructions to prevent the problem.