Application Of Big Data and Predictive Analytics in Process Safety Using Bayesian Network
LEVEL : BEGINNER HRDF : CLAIMABLE
Five (5) CEP points approved by Department of Occupational Safety & Health (DOSH)
TRAINERS : Dr Mardhati Zainal Abidin, ASSOC. PROF. Dr Risza Rusli & Dr Syaza Izyanni Ahmad
WHEN
14 - 15 DECEMBER 2021
WHERE
MS TEAMS
TIME
9.00AM - 1.00PM
RM 700 FOR PROFESSIONALS
10% Discount for Early Bird (until 14 November 2021) / Group / Students
CONTENT SUMMARY
INTRODUCTION
Most catastrophic incidents caused businesses and organizations with major losses and may end up shutting down operations. In the advent of the Fourth Industrial Revolution, the advancement of technology through the digitalisation of process safety and integration of data analytics would be a great help in managing process safety. As a result of effective system and management, the organizations would become resilient towards any incident that might affect performance.
This course is designed to expose the participants with the concept of big data and predictive analytics for process safety using Bayesian Network (theory + case study). This course includes hands-on approach on developing four different models, to analyze the outputs using machine learning models which can later be directly applied by the participants to the job.
| NO. | TITLE/ACTIVITY | DURATION (MINS) | TIME / PIC |
| 1 | Introduction ü Participants to introduce themselves ü Develop course expectation | 10 | 0900 –0910
AP Dr Risza Rusli |
| 2 | Session 1: Introduction to big data & Data Analytics for Process Safety ü Introduction to Big Data & Data Analytics ü Supervised Machine Learning ü Application of Big Data in Process Safety | 50 | 0910- 1000
AP Dr Risza Rusli |
| 3 | Session 2: Introduction to Bayesian Network ü Introduction to Bayesian Network ü Types of Bayesian Model | 60 | 1000 –1100
Mardhati Zainal Abidin |
|
| BREAK | 20 | 1100 - 1120 |
| 4 | Session 3: Predictive Analytic Using Bayesian Network ü Basic on Building Bayesian Network ü Hands-on: Development of Steady-State Model for Process Safety | 80 | 1120 –1240
Dr Syaza Izyanni Ahmad |
|
| Course Evaluation | 20 | 1240-1300 |
|
| Total Time | 240 | 0900-1300 |
Day 2
| NO. | TITLE/ACTIVITY | DURATION (MINS) | TIME |
|
| RECAP OF DAY 1 | 15 | 0900 –0915 |
| 1 | Session 4: Predictive Analytic Using Bayesian Network ü Hands-on: Development of Dynamic Model for Process Safety | 50 | 0915 –1005
Dr Syaza Izyanni Ahmad |
| 2 | Session 5: Predictive Analytic Using Bayesian Network ü Hands-on: Development of Equation-Based Model for Process Safety | 60 | 1005 –1105
Mardhati Zainal Abidin |
|
| BREAK | 15 | 1105 - 1120 |
| 3 | Session 6: Predictive Analytic Using Bayesian Network ü Hands-on: Development of Hybrid Model for Process Safety | 60 | 1120 –1220
Mardhati Zainal Abidin |
| 4 | Overall Course Summary | 20 | 1220 –1240
Mardhati Zainal Abidin |
|
| Course Evaluation | 20 | 1240- 1300 |
|
| Total Time | 240 | 0900 - 1300 |
OBJECTIVES
Upon completion of this course, participants will be able to:
- To understand the concept of big data and predictive analytics and their significant importance in process safety.
- To implement big data and predictive analytics in improving decision making and safety management process.
WHO SHOULD ATTEND?
- Occupational & Process Safety Professionals
- Young Engineers
- Fresh Graduates
- Researchers
- Anybody Who are Interested to Know About Big Data in Process Safety
1. Dr Mardhati Zainal Abidin (UTP)
Dr Mardhati Zainal Abidin is a lecturer in Chemical Engineering Department, UTP and currently the member of Centre for Advanced Process Safety (CAPS).She is a Member of Board of Engineer Malaysia (BEM). Her first involvement in the research and consultancy on risk analysis was back in 2009 when she pursued her Master degree specializing in process safety. Since then, she has actively involved in the research and development of measurement tools for inherently safer design, consequence analysis, prediction of nanomaterials risk for the application of chemical processing.
2. Associate Professor Dr Risza Rusli (UTP)
Assoc Prof Dr Risza Rusli is an Associate Professor in Chemical Engineering Department, UTP and currently is the Head of Centre for Advanced Process Safety (CAPS). She is an Associate Member of IChemE in Process Safety. Her first involvement in the research and consultancy on risk analysis was back in 2001 with the AEA Technology, UK. Since then, she has actively involved in the research and development of measurement tools for inherently safer design, consequence analysis for carbon capture technology by applying Computational Fluid Dynamic technique and risk-based tools considering human factor elements for the application of chemical processing, oil and gas industries. Since 2007, she has involved in providing professional courses related to Process Safety and conducted consequence study and QRA consultancies for oil and gas companies in Malaysia.
3. Dr Syaza Izyanni Ahmad (UTP)
Dr Syaza Izyanni Ahmad is a lecturer and researcher in the Chemical Engineering Department, UTP and the Centre for Advanced Process Safety (CAPS). She started her involvement in research with her Master degree project on the development of a numerical and graphical inherent safety assessment technique for early stage of process design. She then continues this project for her PhD project focusing on the development of inherent safety assessment technique for preliminary engineering design stage. Since then, she is active in safety, health, and environmental related works involving green technologies such as the waste-to-energy technologies.
REGISTRATION FEES
ProfessionalS
myr700
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
Early bird/ group/ student
myr630
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
OUR LOCATION
Centre for Advanced & Professional Education (CAPE)
Level 16, Menara 2,
Menara Kembar Bank Rakyat,
50470, Jalan Travers,
Kuala Lumpur.
CALL US
+605 - 368 7558 /
+605 - 368 8485
DROP US AN EMAIL
cape@utp.edu.my