About the Client

The client is based out of Singapore and developing an Artificial Intelligence (AI) based solution which can solve the problem of manual maintenance and inspection data of rigs and pipes of Oil and gas industries through automation.

It is a condition-based inspection process whereby inspection data is collected via a tablet inspection application, on offshore platforms, remote yards and workshops across the world and made available to asset owners through a web-based platform.

The program, therefore, requires a back-end application so that legacy data, manual data entry and editing can be achieved.

The client from the oil and gas sector leveraged artificial intelligence (AI) software development capabilities of Perfomatix to develop this system.

About the Project

The client needed a complete AI based software platform which could solve the following use cases:

  • Prioritizing the raw inspection data collected by the different sources.
  • Predictive analysis based on the available data.
  • To determine the exact point of fracture or degradation in the pile/rigs.
  • To predict the age and the level of degradation of rigs/ pile through the data analysis.
  • Handing and prioritizing the huge amount of data that is fed to the system after the proper inspection by the teams.

Challenges

The following are the features required for this System;

  • Prioritising the raw inspection data collected by the different sources.
  • Predictive analysis based on the available data.
  • To determine the exact point of fracture or degradation in the pile/rigs.
  • To predict the age and the level of degradation of rigs/ pile through the  data analysis.
  • Handing and prioritising the huge amount of data which is fed to the system after the proper inspection by the teams.

Implementation

Equipment on oil rigs may be in use or in storage.

All equipment are vulnerable to corrosion and fatigue due to the harsh conditions of salt water, pressure, and extreme weather.

Therefore, equipment protection is key for preventing holes and cracks or damage to the joint threads.

Regular inspections can help rig owners identify any weaknesses in their equipment system that could put workers at risk.

Inspections can also identify flaws in the equipment, catching small cracks or abrasions before they become serious issues.

To address the issue of maintaining and storing the inspection data effectively and also to make the process fully automated the system is built on the AI and machine learning technologies.  

The scope of the project is to optimize the current inspection process and build a platform that allows equipment owners to switch to Condition Based Maintenance.

The platform will be a fully automated system which collects the batch of raw inspection data from different sources and is processed by the algorithm implemented on the Dataramp architecture.

The Solution

A fully automated solution is developed for the client which includes the development of a web application for the Super Admin (OP) to manage rigs/ clients/service providers(Admin) and Sub-assembly for rigs.

They also have access to update the legacy data into the system.

The platform will also have web applications for the Service Providers(Admin), through which they could manage their clients, create a project and manage the employees.

Also, a web application for the Project Engineers through which the PEs can define equipment details and describe the QCPs for each managed team and generate reports.

This application will also have access for Supervisor, they will allocate the inspection to an inspector based on their competencies.

There are multiple personas in this application that are listed here based on their hierarchy of privileges.

  • Super Admin ( OP)
  • Admin( Service Provider)
  • Project Engineer
  • Supervisor
  • Inspector

An Android tablet for Inspector is also part of the platform and using the Android application the Inspector users can track and record pending inspections and can be used to complete the data collection for inspection.

The components of the system are:

  • Web Application for Super Admin
  • Web Application for Service Provider – Administrators
  • Web Application for Project Engineer
  • Web Application for Inspection Supervisor
  • Web Application for Client – Drillers / OEM
  • Android tablet application for Inspectors
  • API Layer for Mobile Access and Modular Architecture

Architecture Diagram

Screens

Technology Stack Used

Front End Angular 5, HTML5, CSS, BootStrap
Backend Java Spring MVC
Mobile Apps Android SDK, Java, XML, Android Studio
Database MongoDB
Hosting Amazon Web Services

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