This SGUS for Operation Management and Innovation is to train key personnel, engineers, managers and senior staff of companies, to be technology innovators to achieve manufacturing excellence. This is accomplished by promoting the use of operations management techniques and technologies that support a company's strategy and productivity improvement. The programme will be delivered in an innovated Learn-Practise-Implement training model, consisting of classroom training and mentorship for onsite identification of operations improvement areas, and generation of suitable initiatives and development of implementation action plan for productivity improvements.
This programme consists of 10 training modules, offering a set of accredited manufacturing operation management methodologies and technologies including Operations Management Innovation Methodology (OmniMethodology™), LEAN, Data Analysis, Data Analytics Driven Inventory Management, Resource Scheduling, and Production Planning & Scheduling for Smart Manufacturing, which are proven effective through highly successful applications in various sectors of the manufacturing industry. The programme is enhanced with a lab-based practise training module and 2 project-based training modules to provide unique opportunities to the participants to learn and apply the knowledge and skills for utilisation in the workplace for productivity improvement.
* 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 unit provides the necessary fundamental knowledge and concepts needed to understand operations management by introducing key concepts in operations improvement and productivity through:
On completion of this unit, participants will be ready to embark on an on-site company training mentored by SIMTech’s trainers using the OmniMethodology™. This is the first step towards becoming a technology innovator of a company.
Data mining techniques are increasingly important for data-intensive manufacturing operations as the industry faces a number of challenges such as equipment and material condition variations, trial-and-error in process parameter setting, product quality inconsistencies, low capability of root cause discovery, process performance prediction and process parameters/recipe auto tuning. By applying data mining techniques, a company can improve its product quality and manufacturing productivity.This WSQ course aims to provide a good understanding of the fundamentals of data analytics and data mining techniques for different manufacturing applications. Participants will learn techniques for advanced clustering methods for product quality management, correlation modelling, and data pattern methods for root cause analyses and neural networks for process performance prediction.
Productivity improvement is the only sustainable way to increase the value-add of an organisation and is the key driver of business growth.
Under the Singapore Workforce Skills Qualifications (WSQ) system, this programme aims to achieve productivity breakthroughs for an organisation by educating trainees in LEAN principles and equipping them with LEAN techniques that can be implemented in the workplace.
This comprehensive programme consists of classroom sessions covering the systematic approach to identifying wastes (non-value-added activities), conducting root-cause analyses, and practical lean techniques; with on-site mentoring sessions to help facilitate the implementation of lean techniques.
Upon completing the course, trainees become LEAN champions and lean leaders who will commence on their own LEAN journeys, train colleagues, and foster a LEAN culture within their organisations for continuous productivity improvements and long-term benefits.
The digitalisation journey to Industry 4.0 is fundamentally transforming the traditionally siloed supply
chains into integrated digital supply networks, in which supply and demand signals are originated at any
point and travel immediately throughout the supply networks making data analytics a powerful tool in
This programme is to train participants in inventory planning knowledge and principles, and equip them
with skills and tools that are required in inventory performance analysis and planning.
Harvesting the Low Hanging Fruit
Reaching right-sized inventory by applying the knowledge and skills learned through the course is a low
hanging fruit that company can achieve in the early stage of the digitalisation journey. Meanwhile, the
course will pave the way for continuous inventory performance improvement in the journey to Industry 4.0.
To start companies on their digitalisation journey and equip them with the knowledge on advanced planning and scheduling (APS), this course aims to equip participants with the essential understanding of Production Planning and Scheduling, by providing practical sessions such as hands-on modelling of the participants’ existing planning & scheduling practices into SIMTech’s Smart Manufacturing Operations Management (S-MOM) software.
Participants get to gain knowledge and skills to:
This course is specifically designed to provide hands-on training in the area of resource scheduling for participants in the service industries. Resources to be scheduled may include Manpower (engineer/technician, lecturer/trainer, service staff, etc) and/or Equipment (crane/elevator, classroom, centre, etc). The training focuses on hands-on modelling of the participants’ existing resource scheduling practices into SIMTech’s Manpower Scheduling System (MSS) software.
Participants get to gain fundamental knowledge and skills to:
Upon the completion of the course, learners will be able to:
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.