Data Analytics and Complex Systems (DACS)

With the phenomenal growth in data sensing, storage and computing capacities as well as reduced costs, it has become easier than ever to generate large quantities of data - in a wide variety of structures, formats and across multiple industrial applications. In Rolls-Royce, data is generated in large volume and variety across the products' life cycles. The effective analysis of this data could provide valuable insights about the quality and performance of the products. In the Data Analytics & Complex Systems programme within the Rolls-Royce@NTU Corporate Lab, we are investigating state-of-the-art techniques in Data Analytics to process data from across the Rolls-Royce design, development, manufacturing and in-service applications in order to develop strategic capability for introducing step-change improvements in the products and processes.

DACS will focus on developing new capabilities in data analytics and art​ificial intelligence to create actionable insights from big data and to aid decision making across our businesses and product lifecycle. The programme has developed and demonstrated data analytics and machine learning capabilities broadly across Rolls-Royce’s product lifecycle – design, make, inservices and repair-overhaul.

Some tangible benefits were derived from the application of the capabilities not just within the company but also for our external customers. We have also pushed the boundary in new concepts such as transferring knowledge from past design programmes to inform the design of a new product. Having said this, the exploitation of machine learning is still nascent, particularly on the use of advanced deep learning tools as well as explanatory models which can expound the rationale of the decisions in the analytics. More opportunities are availing themselves as the businesses become more informed and aware of the possibilities.

DACS Phase 1 Projects

C-RT1.1 Robust Large Vocabulary Continuous Speech Recognition (LVCSR) for Far Field Recordings   
C-RT1.2 Ontology-Based Text Mining from Speech Data 
C-RT2.1 Image Data Knowledge Elicitation              
C-RT2.2 Context-Aware Exploration of Image Data             
C-RT3.1 Virtual Engine Emulator by Using Data Fusion 
C-RT3.2 Intuitive Visualization of Large-Scale Data           
C-RT3.3 Automated Flow Feature Detection and Tracking on Unsteady CFD Simulation Data              
C-RT3.4 Inverse Modelling and Transfer for Virtual Engine Emulator    
C-RT3.5 Active and Incremental Learning for Virtual Engine Design      
C-RT3.6 Digital Events – Semantic Miner 
C-RT3.7 Digital Events - Data Manager 
C-RT4.1 Electro-Optical Camera Based Object Detection, Identification and Tracking at Sea 
C-RT4.2 Marine Navigational Decision Aid based upon Vessel Route Prediction from Historical Evidence 
C-RT5.1 Framework for Rapid Simulation of Complex Business Systems 
C-RT5.2 Development of a Business Process Simulation Description Language (BPSDL) 

DACS Phase 2 Projects

DACS1.1 Artificial Intelligence (AI) for Smart Design
DACS2.1 Automated Image Analytics for Smart Image Understanding
DACS3.1 Artificial Intelligence (AI) for Smart Discovery

Assoc Prof Quek Hiok Chai
DACS Programme Director
School of ​Computer Science & Engineering
Nanyang Technological University
​Click here​ to view profile
Dr Terence Hung
DACS Programme Director
Chief, Future Intelligence Technologies
Rolls-Royce Singapore Pte Ltd