Productivity Improvement Model in the Garment Industry: Application of Standardized Work and Poka Yoke with Artificial Vision

Abstract

Peru’s highly competitive garment sector, where microenterprises account for 88.4% of all enterprises, the main barrier to sustainability is low productivity, driven by high rework rates and operational errors. To address this problem, this research proposes an improvement model that combines Standardized Work to unify processes with a Poka Yoke technological solution using artificial vision for real-time defect prevention. This dual approach addresses the root causes of inefficiency, merging a core principle of Lean Manufacturing with an accessible Industry 4.0 tool designed for implementation in resource-constrained environments. The validation of the model demonstrated its remarkable effectiveness, achieving transformative results: the sewing rework rate was drastically reduced from 28.43% to 8.94%, the labeling rework rate were reduced from 18.02% to 3.88%, the production cycle time was optimized from 23.74 to 16.54 min per garment, with a 173.74% increase in productivity. These results not only confirm the validity of the model, but, due to its basis in universal principles and scalable technology, they also guarantee high applicability and replicability in other micro and small companies in the sector, offering a clear path towards a qualitative leap in productivity and competitiveness.