Research, innovation and enterprise are cornerstones of Singapore’s national strategy to develop a knowledge-based innovation-driven economy and society. Public investment in research and innovation has grown over the last 25 years. Under the last five-year Research, Innovation and Enterprise (RIE) 2015 Plan, the Singapore government committed $16 billion over 2011 to 2015 to establish Singapore as a global research and development (R&D) hub. The government will be sustaining its commitment to research, innovation and enterprise, and will invest $19 billion for the RIE2020 Plan over 2016 to 2020.
Under the Advanced Manufacturing and Engineering domain, eight key industry verticals have been identified for RIE2020, based on the potential for Singapore to achieve global leadership, the presence of new opportunities for growth, and the ability to generate good jobs for Singaporeans. These are:
•Machinery & Systems
•Marine & Offshore
•Precision Modules & Components
•Biologics & Pharmaceutical Manufacturing
•Medical Technology Manufacturing
Four cross-cutting technology areas have also been identified as essential enablers, which will undergird and support the verticals. These are:
•Robotics and Automation
To maximise value creation, integrated strategies will be developed across the entire innovation value chain, drawing on the capabilities of stakeholders in the ecosystem, including government agencies, public research performers, universities, and industry. For example, inputs from industry will be sought in the conceptualisation of programmes supported by the Industry Alignment Fund (Pre-Positioning) scheme.
For SIMTech, we develop on two project initiatives as part of Industrie 4.0 movement, namely:
Cyber-physical production system (CPPS) can be defined as a system of collaborating computational elements and subsystems that interact with the physical world throughout all layers of the production system to enable contextual sensing and intelligent response.
A*STAR initiated a Future of Manufacturing (FoM) Initiative to support Singapore’s Advanced Manufacturing Trust. This was done in close consultation with the Ministry of Trade and Industry (MTI), the Economic Development Board (EDB) Singapore and SPRING (now ESG) Singapore, under the government’s Research, Innovation & Enterprise 2020 (RIE2020) plan. Through the effort, this programme has been identified as key enablers in advancing manufacturing in Singapore: Digital Twin Unified Platform and Machine Learning for Active Artificial Intelligence.
The CPPS Programme aims to develop a scalable CPPS platform and contextual and intelligent decision support technologies to close the gaps. Upon development, the technologies will undergo prototyping for validation through test bedding at the Model Factory@SIMTech (Singapore Institute of Manufacturing Technology) and Model Factory@ARTC (Advanced Remanufacturing and Technology Centre), and identified industry partners’ site.
The Programme is designed around the systems approach; enabling individual focus areas augmented by an integrative framework. The integrative aspect is provided through the development of common libraries for cyber models, optimisation and simulation capabilities in Work Package 1. These will then support domain specific solutions at Work Package 2 Enterprise layer and Work Package 3 Shopfloor layer based on plug-and-play modules. This approach will enable virtual experimentation within the platform with feedback loops for learning, with contextual and intelligent decisions applied to the physical world.
Explore some of our research collaborators here.
The past few years have witnessed the tremendous growing demand for data analytics, artificial intelligence (AI), and internet-of-things (IoT) in various industries including healthcare, finance, retail, food, and manufacturing.
Industrial IoT (IIoT) Programme under the IAF-PP is to support Singapore’s advanced manufacturing and engineering (AME) industry sector with advanced IIoT technologies. In SIMTech, we develop cutting-edge technologies including industrial AI and analytics incorporating the IIoT sensors and connectivity, to help manufacturing companies for successful industrial transformation, and more importantly, for their sustainable future with growth, collaboration with I2R in the IIoT Programme.
Our research and development focus on the real-world industry problems in the manufacturing shop-floor such as predictive maintenance, online product quality monitoring, and real-time resource management for job dispatching.