Creating a system for predicative maintenance in shipping

Chord X partnered with Neurons Lab to deliver predictive maintenance and insights in order to optimize the performance and energy consumption of fleets.

Partner Overview

Chord X was founded in 2019 and is based in Singapore. It is a maritime data analytics company that focuses on the energy management of large maritime assets.  Chord X partnered with Neurons Lab to implement predictive maintenance and insights in order to optimize the performance and energy consumption of fleets.

Challenge

Working with a limited number of deployed sensors and collected data.

Chord X is on a journey to transform how shipping companies work with asset data onboard their vessels. Moving away from reactive responses to incidents or issues, Chord X uses machine learning techniques based on vast data sets from vessels to provide actionable insights, and move from reactive to predictive maintenance, and avoid breakdowns before they happen.

As well as this, Chord X wanted to use independent variables identified through these techniques and apply them to emissions control levers, allowing ship owners, operators, and charterers to identify practices that will manage emissions down, in line with the industry goals.

However, due to the limited number of deployed sensors and collected data, ChordX was constrained in developing a predictive maintenance solution. They partnered with Neurons Lab to tackle this.

Solution

A fusion of ML-based and physics based models.

Neurons Lab collaborated with Chord X to combine  previous experience in diesel engine optimization in the automotive industry  and competencies in physics and machine learning, developing an AI solution that was a fusion of ML-based and physics based models.

Neurons Lab set up alternative models and algorithms to identify anomalies across different vessel types, and identified an ensemble of solutions to surface insights that allow early alerts and notifications to prevent failure modes. During the process, new models and algorithms were created that helped to reveal inefficiencies in the engine combustion process and generated new valuable insights into the possible root causes. These improvements also can be applied to reduce fuel consumption and emissions.

Results

With the new solution, ChordX was able to replace outdated rule-based and statistical models with new physics-based machine learning models. This led to a significant optimization of vessel performance and a reduction in fuel consumption and CO2 emissions.At the project’s conclusion, the customer initiated the process of patenting their new solution.

About Neurons Lab

Neurons Lab is an AI service provider that partners with fast-growing companies to co-create disruptive AI solutions, empowering them to gain a competitive edge in their industries.

Our goal is to help businesses to unlock the full potential of AI technologies with support from our diverse and highly skilled team, made up of applied scientists and PhDs, industry experts, data scientists, AI developers, cloud specialists, user design experts and business strategists with international expertise from across a variety of industries.