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Related Experiment Video

Updated: Sep 6, 2025

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars

Published on: August 4, 2018

Modeling manufacturing resources based on manufacturability features.

Changlong Zhao¹, Chen Ma¹, Haifeng Zhang²

¹College of Mechanical and Vehicle Engineering, Changchun University, Changchun, 130022, China.

Scientific Reports

|June 24, 2022

Summary

This study introduces a hybrid algorithm for manufacturability evaluation, grouping manufacturing resources effectively. The approach improves decision-making and optimizes manufacturing processes for better company performance.

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Area of Science:

Manufacturing Engineering
Operations Research
Computer Science

Background:

Manufacturability evaluation is crucial for reducing product development time and costs.
Effective evaluation relies on understanding the processing capabilities of manufacturing resources.
A robust manufacturing resources model is fundamental for accurate manufacturability assessment.

Purpose of the Study:

To develop a hybrid algorithm integrating fuzzy c-means and genetic algorithms for grouping manufacturing resources.
To establish an information model for manufacturing resources using object-oriented methods.
To define a framework for evaluating manufacturing capability based on these resources.

Main Methods:

A hybrid approach combining fuzzy c-means clustering and genetic algorithms was employed.
Manufacturing resources were grouped using manufacturing and geometric features.
An object-oriented method was used to build the manufacturing resources information model.

Main Results:

The hybrid algorithm demonstrated reliability and validity in subgroup analysis.
The approach successfully improved the overall performance of the studied company.
Enhanced feasibility in decision-making was observed, leading to more informed management choices.

Conclusions:

The proposed hybrid algorithm effectively groups manufacturing resources for improved manufacturability evaluation.
The developed framework enhances decision-making processes in manufacturing.
This integrated approach offers significant benefits for optimizing manufacturing operations and reducing costs.