Workshop Layout Optimization Based on Improved SLP Method and Intelligent Algorithms: Literature Review and Innovative Directions

Abstract

In recent years, research on production workshop layout optimization has advanced rapidly in the context of intelligent manufacturing, with the integration of traditional Systematic Layout Planning (SLP) and intelligent algorithms emerging as a mainstream trend. This paper reviews the latest developments in workshop layout optimization, including: (1) The fusion of SLP and intelligent algorithms (e.g., genetic algorithms, sparrow search algorithm, particle swarm optimization), significantly improving logistics efficiency and non-logistics relationships; (2) The application of digital twins and immersive technologies (VR/AI), enabling dynamic adaptive adjustments and human-machine interaction validation; (3) The gradual incorporation of safety and sustainability factors into layout optimization. However, existing research still faces limitations such as insufficient dynamic adaptability, inadequate consideration of human factors, and lack of green metrics. To address these gaps, this paper proposes an "Intelligent-Human-Green" (IHG) collaborative optimization framework, combining dynamic multi-objective intelligent algorithms (e.g., a hybrid sparrow search-NSGA-III algorithm), VR-based human-factor safety assessment, and lifecycle carbon emission quantification. This framework aims to advance workshop layouts toward autonomous decision-making, dynamic adaptation, and sustainability. It holds significant potential for applications in discrete manufacturing, food and pharmaceutical industries, and high-risk workshops, with expected improvements of 25% in logistics efficiency, over 10% reduction in carbon emissions, and enhanced safety responsiveness.