761. Optimizing Smart Manufacturing: Scheduling of Smart Robots in Intralogistics
Invited abstract in session TC-58: AGVs, stream Vehicle Routing and Logistics.
Tuesday, 12:30-14:00Room: Liberty 1.13
Authors (first author is the speaker)
| 1. | Bilgenur Erdogan
|
| Industrial Engineering & Innovation Sciences, Eindhoven University of Technology | |
| 2. | Quang-Vinh Dang
|
| Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology | |
| 3. | Mehrdad Mohammadi
|
| Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology | |
| 4. | Ivo Adan
|
| School of Industrial Engineering, Eindhoven University of Technology |
Abstract
With Industry 4.0 advancements, manufacturing environments are becoming increasingly automated and intelligent, enhancing operational flexibility. However, integrating smart robots into these systems introduces scheduling challenges that require efficient coordination. Unlike previous studies, we address the joint scheduling of heterogeneous smart robots in a flow shop setting, where different types of robots are responsible for distinct transport and handling tasks. Our model involves assigning tasks to appropriate robots and sequencing them alongside workstation operations. The objective is to minimize makespan while managing complex task interdependencies. We propose a mixed-integer linear programming model and, to address scalability, develop a matheuristic that combines iterated local search with linear programming. Using real-world data, we demonstrate the effectiveness of our approach across varying fleet sizes, job volumes, and time constraints. The proposed method improves MILP results and significantly enhances computational efficiency, outperforming current practices.
Keywords
- Flexible Manufacturing Systems
- Scheduling
- Simulation
Status: accepted
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