Abstract—The demand for the food industry has maintained
sustained growth in recent years. In Peru, as a consequence of
the high competitiveness in the food sector, it has reflected a
considerable contribution to the manufacturing GDP with 20%
and 2.6% to the national Gross Domestic Product (GDP).
However, the high demands of the market are not satisfied due
to problems such as the availability of machinery, mainly due to
high programming times, high frequency of machine stoppages,
among others. These problems generate large monetary losses
and a bad image in front of large potential customers. Thus, this
research work, taking as a case study an SME (Small and
Medium-Sized companies) of the food sector, seeks to provide
the application of the tools of the Lean Manufacturing (LM) and
Total Productive Maintenance (TPM) philosophies, to reduce
the high setup times and the high frequency of machine
stoppages that currently harm the company and generate an
impact of 3.95% in operational costs. The model was validated
using the Arena simulator, where a 30.83% reduction in
machine programming time and a reduction in machine stop
frequencies were obtained, which led to an improvement in
Mean Time to Repair (MTTR) indicators with a 21.60%
reduction and a 4.66% increase in Mean Time Between Failures
(MTBF). This new integration of engineering tools makes it
possible to solve the main problems faced by large companies in
the sector to meet market demands and adapt to new needs.
Index Terms—Lean, machine stoppages, Total Productive
Maintenance (TPM), food Sector, arena simulation
The authors are with Facultad de Ingeniería y Arquitectura Universidad
de Lima, Lima, Peru.
*Correspondence: 20161099@aloe.ulima.edu.pe (R.P.-P.)
[PDF]
Cite: Renzo Peralta-Pereda, Frank Zamora, Juan Quiroz-Flores, Martín Collao-Diaz, and Alberto Flores-Perez, "Application of Lean-Total Productive Maintenance Tools to Reduce Setup Times and Machine Stoppages on the Molding Line of an SME in the Food Industry," International Journal of Engineering and Technology vol. 15, no. 4, pp. 138-143, 2023.
