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Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling

Andreas Lind^1,2, V Elango^1,2, L Hanson²

¹Scania CV AB, Södertälje, Sweden.

IISE Transactions on Occupational Ergonomics and Human Factors

|June 12, 2024

Summary

This study introduces an automated factory layout planning method for Industry 5.0, integrating multi-objective optimization and digital human modeling to enhance worker well-being and system efficiency.

Keywords:

Multi-objective assembly factory layouts industry 5.0 optimization

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Area of Science:

Manufacturing Engineering
Operations Research
Human Factors Engineering

Background:

Traditional factory layout planning is slow and prone to human error.
Existing methods often rely heavily on subjective engineer expertise.
Industry 5.0 demands more integrated and efficient planning approaches.

Purpose of the Study:

To develop an advanced methodology for manufacturing factory layout planning.
To integrate multi-objective optimization with nature-inspired algorithms and digital human modeling.
To address limitations of traditional planning methods in Industry 5.0 contexts.

Main Methods:

Utilized multi-objective optimization focusing on worker well-being and system performance.
Incorporated nature-inspired algorithms for efficient search and optimization.
Employed a digital human modeling tool for realistic simulation and analysis.

Main Results:

Demonstrated a transparent, cross-disciplinary, and automated layout planning process.
Successfully applied the methodology to a pedal car assembly station layout case.
Achieved objective and efficient layout planning considering dual targets.

Conclusions:

The proposed methodology represents a significant advancement in manufacturing factory layout design.
It offers robust multi-objective decision support for factory planning.
Facilitates a transition towards more automated and data-driven layout design practices.