COPLANNER: Assembly Planning Data for Flexible Assembly Systems

A thesis from the University of Southern California presents an approach for planning in flexible assembly systems. The work addresses knowledge representation, precedence identification, and cost-minimizing sequence generation, resulting in the COPLANNER system. The generated assembly plans are represented by Hierarchical Partial-Order Graphs (HPOGs) to show temporal and spatial parallelism.

Use Cases

• Optimizing assembly sequences for minimal cost based on the described planning approach.
• Analyzing temporal and spatial parallelism in assembly operations using Hierarchical Partial-Order Graph (HPOG) representations.
• Applying attributed liaison graphs for unified representation of parts and their geometric/physical relations in assembly tasks.
• Testing cooperative problem-solving (CPS) paradigms in manufacturing system planning.

Strengths

• The approach is validated through experiments showing generation of plans with maximal parallelism and minimum assembly cost.
• The system, COPLANNER, demonstrates efficiency by utilizing disassembly operations and subassemblies.
• The work integrates concepts from AI, Robotics, Geometric Modeling, and Industrial Engineering.

Limitations

• The actual dataset content, such as specific graphs or sequences, is not described; data quality requires manual inspection after download.
• Row count, file formats, and column-level documentation are absent.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Southern California

Collection Method

Research thesis presenting a planning approach and system (COPLANNER).