Foundations and Innovations in Sintering Automation Control: Multidimensional Capacity Optimization and Visual Positioning

Abstract

Powder metallurgy (PM) manufacturing is known for its cost-effectiveness and ability to produce intricate components, but the sintering process faces challenges due to non-standardized component positioning. This research establishes a framework for sintering automation, focusing on optimizing product positioning within limited space to enhance sintering results. It addresses the Multidimensional Knapsack Problem (MKP) during pre-sintering positioning (see Fig. 1), considering factors like carriers, material properties, process requirements, quality standards, and equipment limitations. The study formulates a visual positioning strategy for pre-sintering, aiding strategic product placement decisions. These patterns and coordinates support machine vision-assisted robotic arms, advancing Intelligent Manufacturing. The findings offer practical solutions for sustainable development and automation in PM manufacturing, effectively addressing real-world production challenges.