ACP Approach based Intelligent Quality Management System for Manufacturing Processes

with the rapid progress of information and electronic technology, traditional industrial processes are becoming more and more complex. It is very important for manufacturing enterprises to manage and control the product quality under the circumstance of big data. Based on artificial systems, computational experiments, and parallel execution approach, modeling methods by mechanism, data, heuristic rules, etc. are proposed to construct intelligent management and control system for complex manufacturing processes. The presented system is helpful to visualize production processes, to earlier detect potential problems, to quantitatively analyze various risks, to verify management strategies by computational experiments, to optimize decisions by parallel execution.