Abstract:

Objective The textile industry, as a part of traditional and extensive manufacturing, features long and complex processes with specific requirements at each step. The widespread lack of informatization and automation results in low production efficiency and unstable quality control, demanding higher levels of process collaboration and control optimization. Additionally, being labor-intensive, it faces an increasing shortage of human resources. The industry's poor foundation in componentization and intelligence, alongside its weak flexibility and reconfiguration capabilities, faces pressures from resource scarcity, high energy consumption, and environmental costs, complicating the fulfillment of customization, diversity, small batches, and quality-focused transformation demands. The limitation of traditional digital manufacturing technologies on industry upgrades becomes apparent. The integration of the Industrial Internet, internet of things (IoT), big data, cloud computing, artificial intelligence (AI), and human-machine collaboration in new-generation digital manufacturing for textile printing and dyeing aims to meet demands for personalized customization, dynamic process reconstruction, and lean quality management. Textile production, spanning from negotiation to warehousing, encompasses various management areas like orders, design, and quality. Sharing data across these areas enables collaborative decision-making, supporting production and operational decisions through intelligent analysis and optimization, marking a key strategy in advancing collaborative manufacturing driven by digital information.

Method Addressing the digital transformation pain points in the textile printing and dyeing industry, such as decentralized cross-domain production data, weak interaction across management systems, and frequent manual involvement, the paper introduces a new-generation digital manufacturing system architecture for the textile and dyeing sector. It establishes a data hub for the business production process to collect and integrate data from various stages. By constructing decision-support components, the system enhances the customization capacity of the manufacturing system, meeting the optimization and control needs of different companies at various decision-making levels. Finally, it develops a comprehensive digital control system. Through creating a management cockpit, it achieves digital control over orders, equipment, energy, and environmental safety, fulfilling the industry's needs for integrated intelligent decision-making across systems, merging business and control systems, and a closed-loop control model from decision to execution.

Results Paper proposes a new-generation digital manufacturing system framework for textile printing and dyeing to meet the needs of networked and intelligent industrial upgrading such as data perception, information fusion, knowledge reasoning, business interaction, and human-computer collaboration in there. It combines the whole process of business production to establish data center to achieve cross-system integration of integrated intelligent decision-making, build a pool of decision support components for the whole production decision-making field, which is used to promote the integration of business systems and control systems, and set up management cockpit, order digital control system, equipment digital control system, energy digital control system and environmental protection and security digital control system based on the integration of the whole business production process data. Finally, the model of decision-execution closed-loop feedback is formed to realize the information control of the whole process of business and production. A textile dyeing and finishing company in Guangdong, based on the system framework, upgraded the digital manufacturing technology in its dyeing workshop. Compared to 2019, in 2021, the digital intelligent dyeing demonstration workshop saw its per capita output value increase from 1.140 4 million yuan per person to 2.791 1 million yuan per person, with production efficiency up by 145.0%. The product yield rate rose from 88.2% to 96.2%, marking a 9.1% quality improvement. Energy consumption per unit of output value decreased from 465.12 kgce per ten thousand yuan to 316.71 kgce per ten thousand yuan, enhancing energy utilization by 31.9%. In the digital intelligent shaping demonstration workshop, the per capita output value grew from 0.455 2 million yuan per person to 1.046 6 million yuan per person, a 129.9% increase in production efficiency. The product yield rate improved from 95.1% to 97.6%, a 2.6% quality increase, and energy consumption per unit of output value was reduced from 1 759.83 kgce per ten thousand yuan to 1 144.87 kgce per ten thousand yuan, resulting in a 34.9% increase in energy utilization. Significant improvements were achieved in terms of production efficiency, product quality, and energy utilization.

Conclusion Textile printing and dyeing industry already gets a basic digital foundation and information level, with the process of deploying advanced computer numerical control equipment with functions such as equipment communication, status monitoring, process monitoring and fault diagnosis in weaving, dyeing, sizing, color matching, auxiliaries' transmission and distribution and dyestuff transmission and distribution. The popularity of software systems such as enterprise resource planning (ERP), manufacturing execution system (MES) and scheduling system (APS) applied in enterprise procurement, production, marketing and management can provide a timely channel to understand the operation status of workshop production, and significantly reduce the defective rate of products and improve the production operation level of enterprises. The future development and innovation direction of the textile printing and dyeing industry is based on the needs of production enterprises to increase efficiency, reduce consumption, and optimize management. By perceiving production data to form industry domain knowledge, creating a common operation and management platform, and strengthening the application and promotion of this platform in upstream and downstream enterprises, it aims to integrate the supply chain, production chain, and sales chain, forming a collaborative operation and management system for the entire value chain.

Key words: textile printing and dyeing, industrial upgrading, digital manufacturing, full-service production process, human-machine collaboration