This SGUS for Digital Transformation and
Innovation™ (DTI™) Programme is to train and guide eligible
Singaporean and Permant Residents to be Digital
Transformers, in leveraging digital technologies to
accelerate business model changes and achieve
meaningful digital transformation for the company.
Using the Digital Transformation and Innovation™ (DTI™) Methodology, participants will learn to analyse and
(re-)design a company’s strategies, business model,
value streams, and system architecture to ensure greater
alignment, unlock new business growth and achieve
sustainable competitive advantage.
This programme consists of 10 training modules. By completing this programme successfully, the participants will be awarded Certificates of Attendance (COAs) in Digital Transformation and Innovation, Digital Manufacturing and Industrial 4.0 Enabling Technologies and Statement of Attainments (SOAs) in OEE for Productivity Improvement & Manufacturing Data Mining Techniques. A lab-based practise training module and 2 project-based training modules are designed to provide the unique opportunities to the participants to learn and apply the cutting edge technologies and skills in data mining techniques, overall equipment effectiveness, production planning and scheduling for smart manufacturing and data analytics driven inventory planning and equipment condition monitoring techniques.
* Trainees who are concurrently receiving COVID-19 Support Grant (CSG) or Self-Employed Person Income Relief Scheme (SIRS) payouts will receive a lower training allowance as they are already receiving income relief.
Participants will be awarded with Statement of Attainments (SOA) certificates and/or Certificates of Attendance (COAs) for each individual module, if they meet the following criteria:
This DTI™ module provides the necessary fundamental knowledge for participants to understand key
concepts of digital transformation. Under the mentoring of experienced trainers, participants learn to
identify relevant stakeholders in their organisations to successfully conduct business digitalisation using DTI™
Methodology; systematically determine business strategies and objectives; understand activity landscape and system
architecture; identify transformation areas; generate initiatives and develop action plans for digital transformation.
This module aims to provide participants with up-to-date methodologies in data mining and a thorough
discussion of successful case studies. The in-depth learning and hands-on practise on data mining projects will train the participants’ capabilities in data collection, data pre-processing and finally, using data mining
techniques to analyse the data to find out hidden correlations among various parameters for performance
prediction and root cause analysis. Through extensive hands-on practice and data mining projects, the
participants will gain the ability to use data mining techniques to solve actual industrial problems upon
completion of the course.
OEE (Overall Equipment Effectiveness) is a key machine performance metric to identify hidden capacities and
improve manufacturing productivity. The module aims to equip participants with a comprehensive understanding and systematic training in applying OEE to achieve high machine productivity. The course contents are designed to be highly practical and intensive with training provided by expert trainers with industrial experience. Participants will learn the latest knowledge about OEE and its developments to current technologies. This course is highly
suitable for those currently employed or seeking to better prepare themselves for further career advancement in the manufacturing sector.
Many industrial organisations are facing the challenge of excess inventories, which is the root of all evil in
business. This module trains participants in inventory planning concept, knowledge and principles, and equip them with skills and tools for conducting inventory performance analysis and optimisation. With these skills, participants will be able to help their companies to achieve right-sized inventory, mitigate inventory risk and maximise inventory performance. Participants will also have the opportunity to engage with SIMTech inventory planning system during the hands-on sessions for reinforcement of the learnt knowledge.
Smart System Framework™ (SSF™) is a highly interactive Rapid Company Assessment (RCA) workshop, integrating over 400 business processes to support rapid company assessment for digital roadmapping and continuous business process improvement. SSF™’s methodologies and tools are derived from more than 4 years of research and development to document small and medium-sized enterprises (SMEs) business processes. Through this development, SSF™ was able to determine over more than 400 business process flows that can represent ‘standard’ industry business processes and best practices. This module aims to train participants how to implement SSF™ and lead their organisations towards the 4.0 Digital Transformation.
This module aims to equip participants with the essential skills and knowledge for production planning and scheduling, through in-depth discussions and practical sessions including hands-on modelling of real-world
industrial planning & scheduling practices into SIMTech’s Smart Manufacturing Operations Management (S-MOM) software. They will gain the knowledge to help their organisations to embark on their digitalisation journey with best practices on Advanced Planning and Scheduling (APS).
Machine breakdowns and unplanned downtime affects equipment availability and interrupts the delivery of services. Monitoring equipment’s condition and alerting its impending failure can help to minimise disruptions and costly repairs. This course provides participants with training in implementing an equipment condition and alert system using Industrial Internet-of-Things (IIoT) devices for remote monitoring of machine conditions. This course is specifically developed for local industry needs and taught by industry practitioners in the field. Case studies are discussed to highlight the applications in industry.
This module is designed to provide extensive hands-on practise training on basic skills for common processes on Digital Technologies, Transformation Method and data analysis encountered in industrial applications. The module consists of 30 sessions (120 hours in total), which will allow participants the opportunity to operate
digital process equipment and analytical instruments in A*STAR Model Factory @ SIMTech to enhance the
knowledge learned from the technical skills modules.
Under the guidance of the experienced trainers, the participants are expected to do hands-on experiments in the following categories:
The project-based modules provide opportunities for the participants to embark on an industry project either in-house at SIMTech or work with a participating company.
For more information about the SkillsFuture Credit, please visit its webpage here.