The plastic manufacturing sector, particularly small and medium enterprises (SMEs), is a critical component of the global economy, significantly contributing to economic growth, innovation, and employment. Despite their importance, these enterprises face numerous challenges that hinder their production processes, including recurrent machine breakdowns, operational inefficiencies, and lack of effective visual management systems. Addressing these issues is vital for the survival and growth of SMEs in this sector, especially in the context of the disruptions caused by the COVID-19 pandemic.

To tackle these challenges, this study proposed a comprehensive model integrating Lean Manufacturing and Total Productive Maintenance (TPM) methodologies, specifically tailored for SMEs in the plastic sector. The model includes the implementation of 5S for workplace organization, autonomous maintenance to empower operators with routine maintenance tasks, planned maintenance for systematic equipment upkeep, and visual management to enhance workplace communication and efficiency. These components were designed to streamline production processes, reduce waste, and improve overall operational efficiency.

The implementation of this model yielded significant improvements in key performance indicators. The reprocessing rate per burn mark decreased from 2.20% to 1.36%, operational efficiency increased from 57.69% to 85.10%, mean time to repair (MTTR) was reduced from 5.314 hours to 2.69 hours, and downtime decreased from 9.45 minutes to 5.15 minutes. These results demonstrate the effectiveness of the proposed model in enhancing production efficiency and reliability, ultimately leading to cost savings and increased competitiveness for SMEs.

The academic and socio-economic impact of this research is substantial. Academically, it bridges a gap in the literature by providing a practical framework for the integration of Lean and TPM methodologies in SMEs. Socio-economically, the model contributes to the sustainability and growth of SMEs, which are essential for economic development and job creation. The successful implementation of the model in the case study serves as a replicable benchmark for other enterprises in the sector.

In conclusion, this study underscores the importance of adopting comprehensive, data-driven approaches to address operational challenges in SMEs. It calls for further research to explore the integration of advanced technologies, such as digitalization and artificial intelligence, with Lean and TPM methodologies to drive continuous improvement and innovation in the manufacturing sector. Future studies should also focus on validating the model across different industries and operational contexts to enhance its applicability and impact.