Sustainable Smart Manufacturing: A Lifecycle Framework for AI-Enabled Industrial Transformation
Main article
Abstract
Smart Manufacturing (SM) has emerged as a paradigm-shifting response to the complexity, volatility, and sustainability demands facing global industry. Despite rapid progress in artificial intelligence (AI), the Industrial Internet of Things (IIoT), digital twins, and large language models, most manufacturing innovations remain siloed at the level of individual processes or functional units, with limited enterprise-wide coordination. This study addresses that fragmentation by proposing a unified four-layer lifecycle framework that maps AI-enabled capabilities across strategy and organization, product value chains, management support processes, and digital infrastructure. A systematic literature review of 120 peer-reviewed sources published between 2015 and 2026 is conducted following PRISMA guidelines, and the reviewed works are analysed across 14 thematic clusters. The evidence shows that value-chain intelligence has matured considerably, but strategic alignment, closed-loop data integration, and sustainability-oriented capability development remain comparatively underdeveloped. The paper advances an actionable five-stage transformation roadmap and discusses policy implications for enterprises operating in emerging economies. The framework contributes to both the theoretical consolidation of SM research and the practical orchestration of sustainable digital transformation.
