Dynamic Evolution and Chaos Management in the Integration of Informatization and Industrialization

The accelerating digital transformation necessitates a paradigm shift in manufacturing, requiring a structured transition from traditional to smart manufacturing. To address the challenges of fragmented integration, this study proposes an evolutionary model known as the integration of informatization and industrialization (TIOII) that systematically analyzes the dynamic interactions among product, technique, and business integration using a back-propagation neural network approach. A significant research gap exists in understanding how the chaotic and nonlinear interactions between these dimensions influence enterprise stability and adaptability. Prior studies have primarily focused on static models, failing to capture the evolutionary and dynamic nature of TIOII. To address this gap, this study employs stability theory and chaos theory to uncover the mechanisms through which TIOII disrupts pre-existing equilibrium states, leading to chaotic fluctuations before stabilizing into new structural configurations. This research also incorporates robust control theory to formulate strategies for enterprises to effectively manage instability and uncertainty throughout this transformation process. The findings reveal that TIOII is not a linear progression but an iterative process marked by instability and self-organized restructuring. The proposed model successfully explains the intricate, nonlinear interactions and evolutionary trajectories of TIOII dimensions, demonstrating that enterprise transformation follows a chaotic yet structured pattern. Moreover, the robust control methodology proves effective in mitigating uncontrolled instability, offering enterprises practical guidelines for refining investment strategies and adapting business operations amidst disruptive changes. This study enhances the theoretical understanding of industrial transformation by revealing the pivotal role of chaos in transitioning from stability to new stability, contributing to research on complex adaptive systems in enterprise management. The findings highlight the necessity of proactive strategic reconfiguration in technology, management, and product development, enabling enterprises to restructure investment strategies, refine business models, and achieve resilient, innovation-driven growth.

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Publication Details

Journal
Systems
Published
2025-02-21
DOI
https://doi.org/10.3390/systems13030148
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic Evolution and Chaos Management in the Integration of Informatization and Industrialization

Zhang Fang, Jianhua Zhu, Bo Sun
Systems
Economic and Technological Innovation
article

Dynamic Evolution and Chaos Management in the Integration of Informatization and Industrialization

Zhang Fang, Jianhua Zhu, Bo Sun
article en

Abstract

The accelerating digital transformation necessitates a paradigm shift in manufacturing, requiring a structured transition from traditional to smart manufacturing. To address the challenges of fragmented integration, this study proposes an evolutionary model known as the integration of informatization and industrialization (TIOII) that systematically analyzes the dynamic interactions among product, technique, and business integration using a back-propagation neural network approach. A significant research gap exists in understanding how the chaotic and nonlinear interactions between these dimensions influence enterprise stability and adaptability. Prior studies have primarily focused on static models, failing to capture the evolutionary and dynamic nature of TIOII. To address this gap, this study employs stability theory and chaos theory to uncover the mechanisms through which TIOII disrupts pre-existing equilibrium states, leading to chaotic fluctuations before stabilizing into new structural configurations. This research also incorporates robust control theory to formulate strategies for enterprises to effectively manage instability and uncertainty throughout this transformation process. The findings reveal that TIOII is not a linear progression but an iterative process marked by instability and self-organized restructuring. The proposed model successfully explains the intricate, nonlinear interactions and evolutionary trajectories of TIOII dimensions, demonstrating that enterprise transformation follows a chaotic yet structured pattern. Moreover, the robust control methodology proves effective in mitigating uncontrolled instability, offering enterprises practical guidelines for refining investment strategies and adapting business operations amidst disruptive changes. This study enhances the theoretical understanding of industrial transformation by revealing the pivotal role of chaos in transitioning from stability to new stability, contributing to research on complex adaptive systems in enterprise management. The findings highlight the necessity of proactive strategic reconfiguration in technology, management, and product development, enabling enterprises to restructure investment strategies, refine business models, and achieve resilient, innovation-driven growth.

SystemsVol. 13(3)
Harbin Institute of Technology (CN), He University (CN), Honghe University (CN)
Social Science Planning Project of Shandong Province
Openalex Percentile: Top 95%
Economic and Technological Innovation
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