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Related Experiment Video

Updated: Sep 29, 2025

Operation of the Collaborative Composite Manufacturing CCM System

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Multi-Criterial Algorithm for the Efficient and Ergonomic Manual Assembly Process.

Maja Turk¹, Marko Šimic¹, Miha Pipan¹

¹Faculty of Mechanical Engineering, University of Ljubljana, Aškerčeva Cesta 6, 1000 Ljubljana, Slovenia.

International Journal of Environmental Research and Public Health

|March 25, 2022

Summary

This summary is machine-generated.

This study introduces a multi-criterial algorithm (MCA) for optimizing manual assembly workstations. The MCA enhances worker efficiency and ergonomics by personalizing workstation configuration, leading to increased productivity and quality in Industry 4.0 environments.

Keywords:

Industry 4.0 assistance system digitalization ergonomic workplace multi-criterial algorithm productivity smart technologies and tools

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Area of Science:

Industrial Engineering
Human Factors Engineering
Manufacturing Systems

Background:

Industry 4.0 emphasizes smart solutions for supply chain optimization, including manual assembly.
Current manual assembly processes aim to improve work cycle time, productivity, quality, and cost-efficiency.
Digital transformation is key to achieving Industry 4.0 goals in manufacturing.

Purpose of the Study:

To propose a digital transformation of manual assembly processes using a multi-criterial algorithm (MCA).
To develop a human-centered smart manual assembly workstation configuration system.
To ensure efficient and ergonomic performance tailored to individual workers.

Main Methods:

Implementation of a multi-criterial algorithm (MCA) for workstation adjustment and configuration.
Consideration of worker anthropometry, gender, assembly complexity, and product characteristics within the MCA.
Verification through laboratory time analysis and virtual Digital Human Modelling (DHM) with ergonomic assessments.

Main Results:

The MCA effectively configures smart manual assembly workstations for improved performance.
Laboratory and virtual environment analyses confirmed the efficiency and ergonomic benefits of the MCA.
Personalized workstation adjustments led to enhanced manual assembly processes.

Conclusions:

The digital redesign of manual assembly using the MCA creates efficient and ergonomically suitable workstations.
The proposed system increases productivity and efficiency in human-centered manual assembly.
This approach supports the broader integration of Industry 4.0 principles in manufacturing.