Abstract
Due to outgrowing competitiveness on the market, supply chain analysis and optimization become a matter of utmost importance in maximizing global system revenue and customer service levels. In this paper a discrete event simulation model is developed to address system analysis for a multiproduct, multiechelon biomass supply chain case study. The performance metrics considered are: percentage lost sales by product type, biomass pre-treatment facility utilization and downtime probability, average inventory level by product type at each level of the supply chain. The system is subject to machine failure and works under demand uncertainty. The study focuses on the way biomass demand variation and machine failure probability influence those metrics. The supply chain analysis shows that as biomass demand increases the service level deteriorates (the production plant is most affected by the increasing load). System performance can be improved using enhanced maintenance of the biomass pre-treatment plant (reducing downtime probability). System optimization leads to overall increase performance and increase service level.
| Original language | English |
|---|---|
| Pages (from-to) | 462-466 |
| Number of pages | 5 |
| Journal | Computer Aided Chemical Engineering |
| Volume | 30 |
| DOIs | |
| Publication status | Published - Jul 2 2012 |
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All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Computer Science Applications
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Multiproduct, multiechelon supply chain analysis under demand uncertainty and machine failure risk. / Mureşan, Mirela; Cormoş, Cǎlin Cristian; Agachi, Paul şerban.
In: Computer Aided Chemical Engineering, Vol. 30, 02.07.2012, p. 462-466.Research output: Contribution to journal › Article
TY - JOUR
T1 - Multiproduct, multiechelon supply chain analysis under demand uncertainty and machine failure risk
AU - Mureşan, Mirela
AU - Cormoş, Cǎlin Cristian
AU - Agachi, Paul şerban
PY - 2012/7/2
Y1 - 2012/7/2
N2 - Due to outgrowing competitiveness on the market, supply chain analysis and optimization become a matter of utmost importance in maximizing global system revenue and customer service levels. In this paper a discrete event simulation model is developed to address system analysis for a multiproduct, multiechelon biomass supply chain case study. The performance metrics considered are: percentage lost sales by product type, biomass pre-treatment facility utilization and downtime probability, average inventory level by product type at each level of the supply chain. The system is subject to machine failure and works under demand uncertainty. The study focuses on the way biomass demand variation and machine failure probability influence those metrics. The supply chain analysis shows that as biomass demand increases the service level deteriorates (the production plant is most affected by the increasing load). System performance can be improved using enhanced maintenance of the biomass pre-treatment plant (reducing downtime probability). System optimization leads to overall increase performance and increase service level.
AB - Due to outgrowing competitiveness on the market, supply chain analysis and optimization become a matter of utmost importance in maximizing global system revenue and customer service levels. In this paper a discrete event simulation model is developed to address system analysis for a multiproduct, multiechelon biomass supply chain case study. The performance metrics considered are: percentage lost sales by product type, biomass pre-treatment facility utilization and downtime probability, average inventory level by product type at each level of the supply chain. The system is subject to machine failure and works under demand uncertainty. The study focuses on the way biomass demand variation and machine failure probability influence those metrics. The supply chain analysis shows that as biomass demand increases the service level deteriorates (the production plant is most affected by the increasing load). System performance can be improved using enhanced maintenance of the biomass pre-treatment plant (reducing downtime probability). System optimization leads to overall increase performance and increase service level.
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U2 - 10.1016/B978-0-444-59519-5.50093-9
DO - 10.1016/B978-0-444-59519-5.50093-9
M3 - Article
VL - 30
SP - 462
EP - 466
JO - Computer Aided Chemical Engineering
JF - Computer Aided Chemical Engineering
SN - 1570-7946
ER -