Overview:
- Subject 09: Optimizing Production Scheduling Using Artificial Intelligence.
- Department: Quality - Production - Engineering. Profile: Industrial / Manufacturing / Data student with interest in AI.
- Number of Interns: 01. Duration: 06 Months.
Tasks & Responsibilities:
- Model real-world constraints such as capacity, priorities, deadlines, and machine breakdowns to reflect current production environment.
- Develop an optimization algorithm based on AI (or genetic algorithms) to generate production schedules that respect constraints.
- Compare the AI-generated schedule with the current manual schedule and quantify differences in delays, utilization, and throughput.
Required Skills & Profile:
- Knowledge or coursework in production planning & scheduling, operations management, or industrial engineering.
- Experience or strong interest in AI, ML, or optimization algorithms (genetic algorithms, heuristics, or other relevant methods).
- Ability to translate manufacturing constraints into formal models and to validate models with real production data.
Expected Deliverables & Outcomes:
- A working prototype optimizer (AI or genetic algorithm) capable of producing feasible production schedules under modeled constraints.
- Comparative analysis (metrics and visualizations) showing reduced production delays and improved utilization of machines and operators versus the manual schedule.
- Documentation describing model assumptions, algorithm design, validation approach, and recommendations for deployment.
How to Apply:
- To apply, send your CV and a short motivation to G-TN-StagePFE@autoelectric.com.
- Use the email subject: "Application - Subject 09: Optimizing Production Scheduling Using Artificial Intelligence (PFE)" and indicate your relevant coursework or projects in AI/optimization.