Collaborative Research in Engineering, Science and Technology (CREST), the quasi-government body that has been tasked with catalysing the electrical and electronics (E&E) ecosystem for advanced research and engineering in Malaysia, has partnered SAS Institute, a leading international software company, to offer manufacturers an advanced analytics methodology to help them journey towards Industry 4.0.
What is Industry 4.0 and why should manufactures be concerned about it? Industry 4.0 refers to the current trend of automation and data exchange in manufacturing technologies. It integrates the Internet of Things (IoT), cloud computing, data integration and other technological advances into the heart of production and manufacturing systems.
Right now, businesses compete based on cost and efficiency. But when digitalisation takes hold in a real way, any business that falls behind may find that it lacks the ability to compete at all.
CREST and SAS will nurture the Electronic Smart Manufacturing cluster, where manufacturing data can be analysed with advanced perspectives and techniques. Local manufacturers will be able to access the data analytics environment of a manufacturing factory through this platform, which will help them transform their operations and move towards Smart Manufacturing and gain the necessary proficiency for Industry 4.0.
CREST and SAS will organise challenges such as the Data Analytics Challenge within the Great Lab Grand Design Challenge pioneered by CREST. The Great Lab Design Grand Design Challenge is an annual hackathon aimed at giving engineering and science students the experience of thinking about and using problem-solving processes to tackle real industry problems.
SAS will train university students in data analytics methods and tools for the future engineering workforce, in line with the emerging era of big data, IoT and Smart Manufacturing. It will also jointly develop and deliver professional training in data analytics to CREST member companies and universities to enhance competencies in this area among industry and academia.
“Driven by the massive volume of data being generated by IoT and the speed at which it arrives, we are going to see more data captured for in-stream analytics at the edges of the infrastructure. On the back of IoT, we are entering what SAS thinks is the age of the ‘Analytics of Everything’, says Andrew Tan, SAS Institute country manager for Malaysia.
“Whether they are manufacturers overcoming production interruptions or retailers capitalising on sudden shopper behaviour, organisations will increasingly apply in-stream analytics across everything. They will do this to seek faster insights for pre-emptive decision-making on the fly”.
The Analytics of Everything calls for collecting and listening to data from every relevant source – sensors, devices, social media, business systems and more – and using machine learning algorithms to detect patterns of importance while they are building, he adds. “When data from everywhere is evaluated for the immediacy of its potential value, traditional in-cloud analytics will increasingly give way to in-stream”.
CREST CEO Jaffri Ibrahim says these efforts are in line with the organisation’s primary purpose. “We are committed to helping Malaysia establish a world-class electronic manufacturing ecosystem to ensure that the country retains its high value-added R&D and manufacturing capabilities in our pursuit of developing our own unique Industry 4.0 flavour.
“Our partnership with SAS will help us digitise the country’s four decades of capability and expertise in manufacturing. It will also help accelerate new products to market and promote Malaysia as the preferred manufacturing destination”.
This collaborative effort demonstrates the momentum needed to transform the country’s E&E manufacturing landscape so that it is ready for Industry 4.0 and Smart Manufacturing, which are essential to the future of manufacturing in Malaysia.
LED / Optoelectronics
IoT & Embedded Systems
IC Design, Test & Validation
Advanced Material & Packaging
Drones & Autonomous Vehicles
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