Intelligent Collaborative Optimization for Rubber Tyre Film Production Based on Multi-path Differentiated Clipping Proximal Policy Optimization

TL;DR

This paper introduces a novel deep reinforcement learning algorithm, MPD-PPO, designed to optimize complex, multi-objective rubber tyre film production processes, improving accuracy and efficiency in dynamic manufacturing environments.

Contribution

The paper presents a new multi-path differentiated clipping PPO algorithm tailored for high-dimensional, multi-objective industrial optimization tasks in tyre manufacturing.

Findings

Significant improvements in tuning accuracy and operational efficiency.

Effective handling of high-dimensional, multi-objective, and dynamic production challenges.

Enhanced stability and performance in real-time industrial deployment.

Abstract

The advent of smart manufacturing is addressing the limitations of traditional centralized scheduling and inflexible production line configurations in the rubber tyre industry, especially in terms of coping with dynamic production demands. Contemporary tyre manufacturing systems form complex networks of tightly coupled subsystems pronounced nonlinear interactions and emergent dynamics. This complexity renders the effective coordination of multiple subsystems, posing an essential yet formidable task. For high-dimensional, multi-objective optimization problems in this domain, we introduce a deep reinforcement learning algorithm: Multi-path Differentiated Clipping Proximal Policy Optimization (MPD-PPO). This algorithm employs a multi-branch policy architecture with differentiated gradient clipping constraints to ensure stable and efficient high-dimensional policy updates. Validated through experiments on width and thickness control in rubber tyre film production, MPD-PPO demonstrates substantial improvements in both tuning accuracy and operational efficiency. The framework successfully tackles key challenges, including high dimensionality, multi-objective trade-offs, and dynamic adaptation, thus delivering enhanced performance and production stability for real-time industrial deployment in tyre manufacturing.