Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 96-104 |
| Number of pages | 9 |
| Journal | Ingenieria e Investigacion |
| Volume | 38 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Apr 2018 |
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All Science Journal Classification (ASJC) codes
- Engineering(all)
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A continuous time model for a short-term multiproduct batch process scheduling. / Díaz-Ramírez, Jenny; Huertas, José Ignacio.
In: Ingenieria e Investigacion, Vol. 38, No. 1, 04.2018, p. 96-104.Research output: Contribution to journal › Article
TY - JOUR
T1 - A continuous time model for a short-term multiproduct batch process scheduling
AU - Díaz-Ramírez, Jenny
AU - Huertas, José Ignacio
PY - 2018/4
Y1 - 2018/4
N2 - 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.
AB - 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.
UR - https://doi.org/10.15446/ing.investig.v38n1.66425
UR - http://www.scopus.com/inward/record.url?scp=85045962062&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045962062&partnerID=8YFLogxK
U2 - 10.15446/ing.investig.v38n1.66425
DO - 10.15446/ing.investig.v38n1.66425
M3 - Article
VL - 38
SP - 96
EP - 104
JO - Ingenieria e Investigacion
JF - Ingenieria e Investigacion
SN - 0120-5609
IS - 1
ER -