Nanyang Polytechnic (NYP) and SAS Institute have jointly developed an enterprise-to-shopfloor platform designed to helps Singapore’s SMEs in the manufacturing sector to optimise their operations and increase production efficiency.
Harnessing artificial intelligence (AI) and cloud technology, the fully customisable Manufacturing Execution System (MES) has predictive analytics capability that enables near-accurate supply and demand forecasting.
Using past data and analytics, the system helps forecast raw materials required during specific time periods, allowing a smooth product delivery process through just-in-time purchase and delivery and optimised warehousing.
Indeed, in current production trials, the new platform has shown a significant increase in operational effectiveness through predictive analytics and forecasting, and enabling a 100% sampling of parts.
Furthermore, the MES is equipped with real-time machine vision that inspects production parts for defects as part of quality control management. Through digital automation, product quality assurance is also enhanced.
“Through this collaboration with SAS, we aim to co-create meaningful solutions to propel the next generation of manufacturing technologies, while concurrently mentoring our learners to be better prepared for the future workplace,” said Vinn Prabhu, deputy director, School of Engineering at NYP.
The new platform will offer Industry 4.0 solutions that incorporate open-source low-cost devices to connect two networks. With every additional volume of data acquired by the devices, the modelling and training of the AI models will concurrently improve.
To date, the prototype MES is being tested at Sanwa Plastic Industry to manage and schedule jobs for machining components and plastic injection moulds.
Previously, a mould usually requires 100 or more machined metal components, with each component undergoing a stringent quality control check before use. Through the MES prototype, Sanwa Plastic Industry is reporting a 15% increase in machine utilisation, which was brought about by more efficient scheduling of jobs on the shopfloor.
“Through this project, we have seen how analytics has successfully helped to improve the machine utilisation rates for an SME manufacturer, significantly boosting their productivity. We are also proud to have developed the AI machine vision to improve quality control in manufacturing,” said Lim Hsin Yin, managing director for Singapore, SAS Institute.
She added that through its partnership with NYP, SAS Institute will continue to offer innovative AI and cloud solutions that empower manufacturers with data-driven insights for their decision-making.
Already, the two companies have signed an MOU to continue their collaboration on other initiatives that would help SMEs in Singapore through their digital transformation journey.
