Consultancy Projects

Intelligent Solutions

Our customized AI solution that meets industrial needs, from machines to end users.

01.

DOMAIN

DIGITALIZING OPERATION & MAINTAINENCE VIA
ARTIFICIAL INTELLIGENCE

  • Live feed data from sensors at oil fields
  • Customized predictive analytics models to predict failure
  • Live prediction for critical equipment, such as gas compressors and turbines
  • Pinpoints sensors that could potentially cause the failure
  • Allow engineers to properly plan corrective actions, minimizing operational downtime

02.

i-CoRPA

INTELLIGENT CORROSION RATE PREDICTIVE ANALYTICS

  • Predict active corrosion in complex piping system
  • Pinpoint where exactly to perform the inspection activity
  • Provides ahead of time solution to avoid hazards and disasters
  • Customized predictive algorithm developed together with corrosion experts
  • Integrated with existing descriptive analytic system

03.

PrAnCorr

CORROSION PREDICTIVE ANALYTICS 

  • Enhance the integrity management of these strategic pipeline asset to better manage the technical integrity, faster decision making and potential process optimization as well inspection and maintenance. 
  • Reduction of OPEX. Spending up to 20% (RM 167.8 mil) through reduction of IP cost, CI & OP optimization
  • Eliminate downtime due to corrosion

04.

PrAnSpan

PREDICTIVE ANALYTICS FOR PIPELINE FREE SPAN 

  • Free spanning in offshore pipelines due to uneven sea bed and local scouring due to flow turbulence and instability.
  • Cost to inspect and rectify free span is significant thus predicting its occurrence enable more effective decision making, reducing cost of inspection and risk
  • Predictive analytics for pipeline condition assessment and monitoring provide a better overview of operations, and more control in managing assets
  • A pipeline initiative under PotF (Pipeline of the Future) and a future module under i-PIMS

05.

AIM - IP

ASSET INTEGRITY MANAGEMENT

  • Transformation of Online Risk-Based Inspection data from predictive to prescriptive
  • Enhancing equipment integrity performance & minimizing HSE risk via machine learning
  • Comprehensive integration of data to prescribe equipment maintenance
  • Enables customization of inspection, maintenance and technical assurance scope according to equipment risk.

06.

REAL TIME PREDICTIVE MAINTENANCE ON IOT DEVICES

  • Developing and integrating a machine learning ( algorithm model that would allow for real time streaming of data from IoT (Internet of Things) devices for predictive maintenance.
  • Develop a streaming application that will handle streaming events and process real time data.
  • Develop a machine learning model for predictive maintenance.
  • Integrate the developed machine learning model that will allow real time streaming of data and prediction.
  • Real-time streaming of data and prediction

07.

INTELLIGENT DATA DRIVEN PREDICTIVE MAINTENANCE SYSTEM - IP

  • Prediction system solution for Oil & Gas industry that identifies potential failure causal and anticipate it beforehand by deploying advanced digital technology based on AI engine.

08.

INTELLIGENT FOG COMPUTING - BASED ECG MONITORING SYSTEM - IP

  • The main limitation of healthcare IoT is high latency as IoT in billions generating 507.5 zettabytes of data
  • Computing and transmission of this much data will increase the service latency to patients and doctors.
  • Healthcare time-sensitive applications for Electrocardiogram (ECG) data transmission requires less than 300 milliseconds (ms) of delay.
  • Conventional cloud servers cannot fulfill the minimum latency demands of healthcare IoT
  • To minimize the high latency and to send the patient ECG data in real-time, an intelligent device such as laptop or mobile acts as a fog computing (FC)-based gateway between healthcare IoT and cloud.
  • Works as a sub-cloud for IoT, minimize the high latency.