Smart Manufacturing Excellence in Emerging Economies: Evidence of a Successful Integration of SMED 4.0 and Machine Learning in the Operations of a Metal-mechanic Company in Peru

Pajares A.; Prado H.; Maradiegue F.; Pinzón-Hoyos F. · Mechanisms and Machine Science (2026) · DOI: 10.1007/978-3-032-11791-5_54

Resumen

In the metal-mechanical sector, Peruvian companies face a critical challenge: low productivity in processes such as turning, registering only 65.03% compared to the sector standard of 80%. The importance of this problem is reflected in its economic impact, generating annual losses of $88,991, and affecting a sector that represents 11.2% of the manufacturing GDP and employs 8.5% of the Economically Active Population. Previous efforts have shown that tools such as Standardized Work can increase productivity by up to 27%, while the application of TPM has reduced failures by more than 50%; however, these solutions are often applied in isolation, limiting their effectiveness. The main contribution of this study lies in being the first systemic and sequential integration of Standardized Work, SMED 4.0 and Planned Maintenance with Machine Learning support, specifically adapted to the operating conditions and budget constraints of Peruvian SMEs. This hybrid Lean-Industry 4.0 approach has been validated through simulation in Arena, demonstrating exceptional productive and financial impacts, with IRR between 68.90% and 81.14%. In conclusion, this strategic integration constitutes a viable solution to raise the competitiveness of Peruvian metal-mechanical SMEs to international standards. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Instituciones: Universidad Peruana de Ciencias Aplicadas