Category Archives: 2026 Training (Jun – Dec)

Process Mapping

DATE: 15 July 2026

TIME: 9.00am – 5.15pm

ONLINE via Zoom

DURATION: 1 full-day course

COURSE OBJECTIVES
After participating in the training, you will be able to:

• Understand the differences between process, major steps and activities.
• Map macro process model and detailed process map.
• Understand the principles of value-adding to customers.
• Systematically identify mistake risks in the business process.
• Improve cost, delivery and quality.

COURSE OUTLINE
1. Introduction to process and process mapping
2. Process mapping tools such as SIPOC and Cross Functional Process Map
3. Process analysis tools such as value adding analysis and risk analysis
4. Features of an ideal process
5. Strategies to improve current ‘as is’ process
6. Process management method and tools

Medical Device Change Control

DATE: 1 & 2 July 2026

TIME: 9.00am – 5.15pm

VENUE: Iconic Marjorie Hotel, Penang

DURATION: 2 full-day course

COURSE OBJECTIVES
This course provides quality systems professionals, manufacturing engineers, and process development engineers with the knowledge and skills to implement change control for medical devices.

COURSE OUTLINE
1. Introduction to design control
2. Application of risk management to design control
3. Design control system

• Design and development planning
• Design and development input
• Design and development output
• Design and development review
• Design and development verification
• Design and Development validation
  
• Design and development transfer
• Design and development changes
• Design history file

4. Validation system (Design/Installation/Operational and Performance Qualification)
5. Statistical tools and techniques
6. Design control – Quality system inspection technique

Failure Mode and Effects Analysis (FMEA) in Medical Device Manufacturing

DATE: 23 & 24 June 2026

TIME: 9.00am – 5.15pm

VENUE: Iconic Marjorie Hotel, Penang

DURATION: 2 full-day course

INTRODUCTION
This training course is designed specifically to equip professionals with the knowledge and skills needed to navigate the complex landscape of risk and compliance through an innovative and revamp approach on application of Failure Mode and Effects Analysis (FMEA) with a unified criteria framework. Join us as we delve into practical methodologies that foster a holistic understanding of integrated risk assessment, ensuring effective compliance measures in a dynamic medical device industry.

COURSE OBJECTIVES
After participating in the training, you will be able to:

• Learn the practical methodologies for applying reformed Failure Mode and Effects Analysis (FMEA) techniques in diverse business scenarios.
• Gain a deep understanding of the integrated risk landscape and its implications for compliance.
• Learn how to develop a rating table that addresses all pillars of risk.
• Use advance FMEA to determine Critical Product Attributes and Critical Process Attributes for subsequent validation and control activities.
• Develop the ability to identify, assess, and prioritize risks within a unified criteria framework.

COURSE OUTLINE
1. What is FMEA?
2. FMEA history
3. FMEA benefits
4. FMEA challenges
5. When FMEA is needed?
6. Types of FMEA
7. DFMEA vs PFMEA
8. Murphy’s Law
9. Product cycle
10. Terms and definitions
11. Steps in FMEA process
12. Input for DFMEA & PFMEA
13. Process flowchart / map
14. Conventional FMEA weakness
15. Advance FMEA (AFMEA)
16. Understanding & filling of FMEA template
17. FMEA rating & acceptance criteria: Conventional vs. True
18. Pillar of risk – Integrated risk compliance to ISO 13485:2016, ISO 14971:2019, FDA QSR & EU MDR
19. Investigation tools
20. 7 Things on FMEAs
21. Top 10 mistakes made when apply FMEA
22. Relationship between FMEA vs. validation vs. control plan
23. AFMEA for Critical Product Attributes (CPAs) and Critical Process Attributes (CRAs)
24. List of other risk assessment tools & techniques

Effective Root Cause Analysis

DATE: 22 June 2026

TIME: 9.00am – 5.15pm

VENUE: Iconic Marjorie Hotel, Penang

DURATION: 1 full-day course

INTRODUCTION
Root Cause Analysis (RCA) is one of the most common actions required at every organisation, not only to solve day-to-day operational problems but also to play an important role in other improvement activities such as lean sigma, risk management, etc. Root cause analysis involves searching backwards from an undesirable effect (or problem) to its cause(s) and addressing those causes to effectively prevent recurrence.

This training provides the learner with a basic understanding of the principles and techniques of effective root cause analysis and providing concepts needed to effectively perform investigation.

COURSE OBJECTIVES
After participating in the training, you will be able to:

• Understand the principles and techniques of effective root cause analysis.
• Recognise common barriers to root cause analysis and apply techniques to overcome those barriers.
  

COURSE OUTLINE
1. Challenges in root cause analysis
2. Benefits of effective root cause analysis
3. Symptoms vs cause of the problem
4. Contributing factor vs root cause
5. Types of root cause
6. Root cause analysis problem solving model
7. Root cause analysis tools
8. Actions to prevent future problem – corrective action preventive action
9. Human error
10. Root cause analysis in a regulated environment
11. Tips for performing effective root cause analysis

Design of Experiments

DATE: 30 June 2026

TIME: 9.00am – 5.15pm

VENUE: Iconic Marjorie Hotel, Penang

DURATION: 1 full-day course

COURSE OBJECTIVES
After participating in the training, you will be able to:

• Differentiate traditional experimentation and Design of Experiments (DOE) methods.
• Understand and apply crucial DOE concepts.
• Plan a full factorial or a fractional factorial experiment.
• Analyze DOE results.
• Handle confounding effects.
• Develop process models for process predictions and simulations.
• Use Minitab software for DOE analysis.
  

COURSE OUTLINE
1. Types of experimentations
2. Minitab navigation
3. Factorial design and analysis for experimentation
4. Develop process models for process performance prediction and simulations
5. Statistical process control