Innovative Supply Chain Solutions
Optimising business operation with data-driven insights and analytics.
About Supply Chain Analysis
Our mission
At Supply Chain Analysis Ltd., our mission is to revolutionise the way businesses manage their supply chains. We utilise cutting-edge technology and data analytics to enhance efficiency and drive growth.
Our capabilities
- AI & Machine Learning for Decision Intelligence: Extracting valuable insights from big data and large text sources to
At Supply Chain Analysis Ltd., our mission is to revolutionise the way businesses manage their supply chains. We utilise cutting-edge technology and data analytics to enhance efficiency and drive growth.
Our capabilities
- AI & Machine Learning for Decision Intelligence: Extracting valuable insights from big data and large text sources to support informed decision-making.
- Supply Chain Carbon Footprint: Capturing and quantifying Scope 1-3 emissions across supply chains to drive sustainability.
- Life Cycle Assessment (LCA): Evaluating environmental impacts across products, services, and value chains for better resource management.
Funded Projects
Smart RRCycle
RRCycle is an intelligent trailer movement optimisation developed by Supply Chain Analysis Ltd with the aim of improving operation efficiency in Roll-on/Roll-off (RoRo) port operations. The objective is to use AI-driven prediction models with advanced optimisation alogirthms to optimise trailer sequencing and tug allocation, which maximises simultaneous loading and unloading of trailers.
The impact is that it enhances operational efficiency, reduces vessel turnaround times, lower operating costs and cut associated carbon emissions without requiring additional physical infrastructure.
Funded by Connected Places Catapult, Supply Chain Analysis Ltd. successfully trialled RRCycle within DFDS’s trailer operations at Portsmouth International Port. The trial demonstrated up to a 30% increase in operational efficiency and up to a 34% reduction in vessel turnaround times.
Shore Power for Wightlink Ferries
Funded by the Innovate UK Clean Maritime Demonstration Competition Round 6 (CMDC6), this project assesses the feasibility of replacing in-port diesel use on Wightlink’s FastCat ferry with renewable shore-side energy with the aim of enabling zero-emission operations while docked.
We modelled the in-port energy demand of the FastCat ferry and evaluated viable renewable shore-side power solutions at Portsmouth and Ryde. This included assessing port infrastructure readiness, regulatory and safety requirements in consultation with the Maritime and Coastguard Agency, and reviewing state-of-the-art energy technologies, such as diesel-battery hybrids, full battery electric systems, hydrogen fuel cells combined with batteries, and engines powered by green ammonia and methanol.
The study also developed CAPEX/OPEX models, assessed emissions impacts, and achieved the outcome of outlining a regulator-informed roadmap to eliminate in-port diesel use and enable future zero-emissions high-speed ferry operations
Our Partners
Case studies
AI-Powered Yard Management container ports
Machine Learning for Earthquake Damage Cost Prediction
Machine Learning for Earthquake Damage Cost Prediction
- Predicting gate or out-terminal assignments for containers upon vessel arrival.
- Optimising container stacking locations to minimise crane and truck movements.
- Reducing vessel and truck waiting times, enhancing port efficiency.
Machine Learning for Earthquake Damage Cost Prediction
Machine Learning for Earthquake Damage Cost Prediction
Machine Learning for Earthquake Damage Cost Prediction
Developing machine learning models to estimate repair costs for residential buildings impacted by earthquakes, utilising historical earthquake data and construction costs to enhance recovery planning engagement.
Energy Aware Ship Scheduling
Machine Learning for Earthquake Damage Cost Prediction
Social Media & Supply Chain Risk Analysis
- Minimise waiting and berthing times.
- Maximise ship space utilisation.
- Reduce energy and fuel consumption during berthing and transit.
Social Media & Supply Chain Risk Analysis
Predicting Disease Prevalence using NHS Digital Data
Social Media & Supply Chain Risk Analysis
- Utilising text mining to classify risks imposed on community healthcare supply chains (GPs, pharmacies, patients) during the COVID-19 pandemic.
- Evaluating the effectiveness of mitigation strategies implemented by healthcare providers.
Predicting Disease Prevalence using NHS Digital Data
Predicting Disease Prevalence using NHS Digital Data
Predicting Disease Prevalence using NHS Digital Data
Applying clustering methods and econometric modelling to forecast chronic disease prevalence for Integrated Care Systems in East England.
AI-Driven Chatbot for Data Queries & Dashboards
Predicting Disease Prevalence using NHS Digital Data
Predicting Disease Prevalence using NHS Digital Data
- Developing a chatbot enabling natural language queries for relational databases.
- Automating Power BI dashboard generation to simplify complex data access and reduce query time.
Carbon Emission Tracking and Reduction
Carbon Emission Tracking and Reduction
Carbon Emission Tracking and Reduction
- Developing a sustainability platform to track and quantify carbon emissions generated from all the activities and products associated with an event, and produce a dashboard to compare emissions by companies, sectors and events, using machine learning and scenario modelling to recommend interventions to reduce carbon emissions in future events.
- Tracking and calculating emissions in logistics and warehouse operations within the aviation material sector, making recommendations for reducing carbon emissions, to meet requirements from downstream customers.