Public Lecture 2024 - AI for Production Planning and Control

Welcome & Opening Remarks

• Event by Puma Industrial Engineering, President University
• Master's of Ceremony: Rame and Kalisa
• Opening prayers according to respective religions
• Introduction of today's speaker: Mr. Zaki Darmawan
• Reminder about attendance link for certification

National Anthem

• Performance of the Indonesian national anthem "Indonesia Raya"

Opening Speeches

Project Manager of Public Lecture 2024 - Alya Keesya

• Thanks to head of study program Mam Andil Taslim, Industrial Engineering lecture Mam Anastasia, and moderator Mam Nisa
• Acknowledgement to speaker Mr. Zaki Darmawan and participants
• Thanks to the organizing committee

Chairperson of Puma Industrial Engineering 2024

• Thanks to all attendees, lecturers, and guest speaker Mr. Zaki
• Significance of the public lecture for thesis preparation
• Encouragement to stay tuned for future events

Guest Lecturer: Mr. Zaki Darmawan

• Introduction to the topic: Machine learning, genetic AI, and modeling applications in production planning
• Use of generative AI (Gen AI) in Astra International since 2022

Key Aspects of Gen AI in Production Planning

• Generative AI & Chat GPT: Understanding concepts
• AI Evolution: Historical context from data mining to deep learning and generative AI

Practical Applications of Gen AI at Astra International

• Online Interaction: Public website chatbots, internal knowledgebases
• Content Generation: Reporting, document generation, digital marketing
• Complex Data Handling: Inventory management, market analysis

Case Study: Smart Stock Using Gen AI

• Objective: Improve the accuracy and efficiency of PPIC analysts
• Methodology: Analyze demand patterns, automate tasks, and optimize stock levels
• Challenges: Execution time, data accuracy (mitigating ‘hallucinations’), balancing computation time

Roadmap for Implementation

• MVP 1: Exploratory analysis with basic data sets
• MVP 2: Advanced data sets and recognition of varied questions
• MVP 3: Advanced exploratory analysis integrating more complex machine learning models

Lessons Learned

• Importance of iterative project definition and close collaboration with business users
• Detailed data collection and preparation is crucial for accuracy
• Selection of appropriate models and algorithms for computations
• Deployment strategies and maintenance planning
• Fine-tuning using prompt engineering and hyper-parameter optimization

Q&A Session

• How generative AI impacts job roles and future work environments
• Cybersecurity measures in handling sensitive data with Gen AI
• The role of Gen AI in shaping human decision-making and privacy concerns
• Practical examples of the kind of tasks Gen AI can assist or automate

Closing Remarks

• Acknowledgements to speaker Mr. Zaki Darmawan, lecturers, and participants
• Encouragement to fill out the attendance link for certification purposes
• Gratitude and farewell from the MCs, Rame and Kalisa