Productivity Improvement Model Using MPS and Preventive Maintenance in a Silica Sand Processing Company

Jarama R.; Torres V.; Montoya J.; Villanueva R. · Advances in Transdisciplinary Engineering (2026) · DOI: 10.3233/atde260712

Resumen

Silica sand processing is a critical link in construction supply chains, yet many medium-sized plants in emerging economies operate with chronic productivity gaps driven by reactive planning and maintenance. This study addresses that problem in a Peruvian silica sand processor by proposing an integrated improvement model that couples a hybrid demand forecasting system, a capacity-constrained Master Production Schedule (MPS), and a preventive maintenance plan for the bottleneck rotary dryer, all implemented within a single decision-support framework and validated through discrete-event simulation. The model aligns forecasted demand with finite capacity, embeds maintenance windows directly into the weekly schedule, and restructures maintenance routines around reliability data. Results show simultaneous gains in service and efficiency: the Demand Satisfaction Index and order fulfilment level increase from about 91% to 93%, while average hourly productivity rises from 6.96 t/h to 7.11 t/h without expanding installed capacity. Overall, the plant recovers previously lost operating hours at the bottleneck and closes a substantial share of its initial productivity gap using tools that are feasible for medium-sized, low-digitalization environments.

Instituciones: Universidad de Lima