Research Directions for Improving Autonomous Manufacturing Quality of Humanoid Robots: A Systems Engineering Approach

Purpose: This study proposes a systems engineering framework and mathematical optimization strategies to maximize the operational availability and quality of humanoid robots within autonomous manufacturing systems.Methods: Based on the ISO/IEC/IEEE 15288 standard, five operational constraint aspects—technical, operational, economic, safety, and legal/ethical—are analyzed. Furthermore, a new metric termed AoSAFE is defined to quantitatively reflect productivity adjustments mandated by safety compliance.Results: To address the identified constraints, five mathematical models are recommended for further research topics: maintenance scheduling, inventory optimization for long lead-time parts, task allocation using the Knapsack problem, dynamic path planning, and multi-robot sequencing.Conclusion: The study identifies that these operational variables are interdependent, indicating that an integrated optimization approach, rather than individual optimization, is essential for ensuring manufacturing quality. Consequently, the development of a unified mathematical framework for these coupled dynamics is presented as a critical future research direction for effective robot deployment.