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Title: Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions

Abstract

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 varyingmore » 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.« less

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division
  2. QMT Group, Knoxville, TN (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Energy & Transportation Science Division
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Bioenergy Technologies Office
OSTI Identifier:
1474612
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Energy Research
Additional Journal Information:
Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 2296-598X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS

Citation Formats

Sharma, Bhavna, Clark, Robin, Hilliard, Michael R., and Webb, Erin. Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions. United States: N. p., 2018. Web. doi:10.3389/fenrg.2018.00100.
Sharma, Bhavna, Clark, Robin, Hilliard, Michael R., & Webb, Erin. Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions. United States. doi:10.3389/fenrg.2018.00100.
Sharma, Bhavna, Clark, Robin, Hilliard, Michael R., and Webb, Erin. Tue . "Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions". United States. doi:10.3389/fenrg.2018.00100. https://www.osti.gov/servlets/purl/1474612.
@article{osti_1474612,
title = {Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions},
author = {Sharma, Bhavna and Clark, Robin and Hilliard, Michael R. and Webb, Erin},
abstractNote = {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.},
doi = {10.3389/fenrg.2018.00100},
journal = {Frontiers in Energy Research},
number = 1,
volume = 6,
place = {United States},
year = {2018},
month = {9}
}

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