Effective management of maintenance in industries is a major concern to reduce the cost and ensure reliable operation of high-value equipment/machines. With modern complex complicated equipment and time pressure from production, an informative decision with timely support from relevant data is critical for an optimal plan and cost-effective maintenance.
However, data are normally diverse and scattered around anywhere in the office or the shopfloor, and need to be collated with time-stamp first. To get insights from data for improving efficiency and quality of maintenance, profound data analysis knowledge, techniques and skills are needed.
This course aims to provide the participants with the knowledge, techniques and skills of data analysis for predictive maintenance and optimal maintenance planning. Data from operation management systems, machine sensors, maintenance activities will be analyzed. Latest technology such as machine learning-based predictive engine, maintenance planning system is introduced and allow participants to discuss industrial cases and gain hands-on experience.
At the end of the course, participants can:
The programme covers the following key topics:
Introduction of Data Analysis for Predictive Maintenance and Optimal Plan
Data Processing and Modelling Techniques
PdM-enabled Maintenance Management System
Downtime Forecast and Optimal Maintenance Plan
Participants will be awarded with a Certificate of Attendance (COA) by SIMTech if they meet the following criteria:
Please note that fees and funding amount are subject to change.
¹ Under the Enhanced Training Support for Small & Medium Enterprises (SMEs) scheme (ETSS), subject to eligibility criteria.
² Under the SkillsFuture Mid-Career Enhanced Subsidy (MCES) for employer-sponsored and self-sponsored Singapore Citizens aged 40 years old and above.
Singaporeans aged 25 years old and above are eligible for SkillsFuture Credit which can be used to offset course fees (for self-sponsored registrations only). For more information on the SkillsFuture funding schemes you are eligible for, please visit www.ssg.gov.sg