Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions
Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-09-01
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| Series: | Frontiers in Energy Research |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fenrg.2018.00100/full |
| _version_ | 1798045425165402112 |
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| author | Bhavna Sharma Robin Clark Michael R. Hilliard Erin G. Webb |
| author_facet | Bhavna Sharma Robin Clark Michael R. Hilliard Erin G. Webb |
| author_sort | Bhavna Sharma |
| collection | DOAJ |
| description | Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period: (1) bale-delivery scenario with biorefinery uptime varying from 20 to 85%; (2) pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%; and (3) pellet-delivery scenario with depot and biorefinery uptime at 85%. In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical. |
| first_indexed | 2024-04-11T23:21:52Z |
| format | Article |
| id | doaj.art-3818800260504fbebe69a8017c5b2a87 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-04-11T23:21:52Z |
| publishDate | 2018-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-3818800260504fbebe69a8017c5b2a872022-12-22T03:57:26ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2018-09-01610.3389/fenrg.2018.00100395761Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational DisruptionsBhavna Sharma0Robin Clark1Michael R. Hilliard2Erin G. Webb3Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United StatesQMT Group, Knoxville, TN, United StatesEnergy & Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, United StatesEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United StatesLignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period: (1) bale-delivery scenario with biorefinery uptime varying from 20 to 85%; (2) pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%; and (3) pellet-delivery scenario with depot and biorefinery uptime at 85%. In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.https://www.frontiersin.org/article/10.3389/fenrg.2018.00100/fulloperational disruptionsbiorefinerypre-processingbiomassdepotssimulation |
| spellingShingle | Bhavna Sharma Robin Clark Michael R. Hilliard Erin G. Webb Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions Frontiers in Energy Research operational disruptions biorefinery pre-processing biomass depots simulation |
| title | Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions |
| title_full | Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions |
| title_fullStr | Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions |
| title_full_unstemmed | Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions |
| title_short | Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions |
| title_sort | simulation modeling for reliable biomass supply chain design under operational disruptions |
| topic | operational disruptions biorefinery pre-processing biomass depots simulation |
| url | https://www.frontiersin.org/article/10.3389/fenrg.2018.00100/full |
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