TY - JOUR
T1 - Mathematical Model for Production Scheduling and Deadline Compliance in the Sausage Industry
AU - Camila, Romero Bravo
AU - Antony, Mora Asanza
AU - Andres, Ortega Andrade
AU - Kevin, Fajardo Parra
AU - Pablo, Flores Siguenza
AU - Rodrigo, Guaman
N1 - Publisher Copyright:
© 2025 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2025
Y1 - 2025
N2 - The increasing complexity of production processes in the food industry requires advanced planning strategies to enhance efficiency and ensure timely order fulfillment. Challenges such as idle times, capacity constraints, and material waste can significantly impact production performance, making optimization essential for maintaining competitiveness. To address these challenges, this study develops a mathematical model based on Mixed-Integer Linear Programming (MILP) to optimize production scheduling and ensure compliance with delivery deadlines in sausage manufacturing. Implemented through an interactive dashboard in Excel with VBA, the model enables users to input product demand and target production dates, generating optimal solutions for synchronizing production stages and maximizing resource utilization. The results include precise calculations for the quantities required at each production stage, optimized start and end times, and an efficient allocation of products to available machines. Additionally, line and bar charts illustrate process times per area and product distribution, enabling the identification of bottlenecks and supporting strategic decision-making. The integration of Solver and VBA in Excel proves to be a cost-effective and adaptable solution to enhance competitiveness in high-demand environments with limited resources.
AB - The increasing complexity of production processes in the food industry requires advanced planning strategies to enhance efficiency and ensure timely order fulfillment. Challenges such as idle times, capacity constraints, and material waste can significantly impact production performance, making optimization essential for maintaining competitiveness. To address these challenges, this study develops a mathematical model based on Mixed-Integer Linear Programming (MILP) to optimize production scheduling and ensure compliance with delivery deadlines in sausage manufacturing. Implemented through an interactive dashboard in Excel with VBA, the model enables users to input product demand and target production dates, generating optimal solutions for synchronizing production stages and maximizing resource utilization. The results include precise calculations for the quantities required at each production stage, optimized start and end times, and an efficient allocation of products to available machines. Additionally, line and bar charts illustrate process times per area and product distribution, enabling the identification of bottlenecks and supporting strategic decision-making. The integration of Solver and VBA in Excel proves to be a cost-effective and adaptable solution to enhance competitiveness in high-demand environments with limited resources.
KW - Mathematical Model
KW - Optimization
KW - Production Scheduling
KW - Resource Allocation
UR - https://www.scopus.com/pages/publications/105019305855
U2 - 10.18687/LACCEI2025.1.1.2153
DO - 10.18687/LACCEI2025.1.1.2153
M3 - Artículo de la conferencia
AN - SCOPUS:105019305855
SN - 2414-6390
JO - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
JF - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
IS - 2025
T2 - 23rd LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2025
Y2 - 16 July 2025 through 18 July 2025
ER -