A continuous time model for a short-term multiproduct batch process scheduling
In the chemical industry, it is common to find production systems characterized by having a single stage or a previously identified bottleneck stage, with multiple non-identical parallel stations and with setup costs that depend on the production sequence. This paper proposes a mixed integer product...
- Autores:
-
Díaz Ramírez, Jenny
Huertas, Jose Ignacio
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/67552
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/67552
http://bdigital.unal.edu.co/68581/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
MIP modeling
goal programming
batch process scheduling
short-term scheduling
mathematical formulation
Monte Carlo simulation
programación entera mixta
programación de la producción por lotes
industria química
modelación matemática
simulación Monte Carlo
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | In the chemical industry, it is common to find production systems characterized by having a single stage or a previously identified bottleneck stage, with multiple non-identical parallel stations and with setup costs that depend on the production sequence. This paper proposes a mixed integer production-scheduling model that identifies lot size and product sequence that maximize profit. It considers multiple typical industry conditions, such as penalties for noncompliance or out of service periods of the productive units (or stations) for preventive maintenance activities. The model was validated with real data from an oil chemical company. Aiming to analyze its performance, we applied the model to 155 instances of production, which were obtained using Monte Carlo technique on the historical production data of the same company. We obtained an average 12 % reduction in the total cost of production and a 19 % increase in the estimated profit. |
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