Model to reduce the cost of production in a bottling company using the EOQ, Linear Programming and Aggregate Planning
Many companies require the implementation of operations engineering models to optimize processes in Peru. Companies often order production lots based on current inventory or orders from their vendors. The implementation of EOQ allows the development of a methodology to determine optimal production q...
| Authors: | , , |
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| Format: | article |
| Publication Date: | 2022 |
| Country: | Perú |
| Institution: | Universidad Peruana de Ciencias Aplicadas |
| Repository: | UPC-Institucional |
| Language: | Spanish |
| OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/669150 |
| Online Access: | https://doi.org/10.18687/LEIRD2022.1.1.16 http://hdl.handle.net/10757/669150 |
| Access Level: | Open access |
| Keyword: | Aggregate planning EOQ Linear programming operations engineering Production Planning https://purl.org/pe-repo/ocde/ford#2.11.04 |
| Summary: | Many companies require the implementation of operations engineering models to optimize processes in Peru. Companies often order production lots based on current inventory or orders from their vendors. The implementation of EOQ allows the development of a methodology to determine optimal production quantities in such a way that inventory and costs are reduced. It is desired to bring theoretical implementations of EOQ, Linear programming and aggregate planning to real industrial situations and observe their interrelationships. The present work develops a case study in which EOQ (Economic Order Quantity) based on unknown demand, Linear Programming and aggregate planning was implemented to a water bottling company located in Peru to reduce its costs. Simulations carried out using two different programs show that the information provided by EOQ, Aggregate Planning and Linear Programming reduce labor costs by 42% and the costs of ordering production by 47%. It is concluded that the EOQ and aggregate planning tools manage to reduce unnecessary costs in small and medium-sized companies. |
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