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Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland
•A linear programming model developed to optimise wood biomass supply chains for Ireland.•It uses MC to determine harvesting, chipping, storage and transportation costs.•It analyses two supply chain scenarios and two truck configurations specific to Irish conditions.•Low wood MC increases supply cos...
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Published in: | Applied energy 2015-01, Vol.137, p.338-351 |
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description | •A linear programming model developed to optimise wood biomass supply chains for Ireland.•It uses MC to determine harvesting, chipping, storage and transportation costs.•It analyses two supply chain scenarios and two truck configurations specific to Irish conditions.•Low wood MC increases supply cost due to longer transport distances.•Optimal truck loads can be achieved by controlling wood MC.
In the coming years, Ireland will continue to face an increasing demand for wood biomass as a renewable source of energy. This will result in strained supply/demand scenarios, which will call for new planning and logistics systems capable of optimizing the efficient use of the biomass resources. In this study, a linear programming tool was developed which includes moisture content (MC) as a driving factor for the cost optimisation of two supply chains that use short wood and whole trees from thinnings as material feedstock. The tool was designed and implemented to analyse the impact of moisture content and truck configurations (5-axle and 6-axle trucks) on supply chain costs and spatial distribution of the supply materials. The results indicate that the inclusion of wood chips from whole trees reduces the costs of wood energy supply in comparison with only producing wood chips from short wood to satisfy the demand, with 9.8% and 10.2% cost reduction when transported with 5-axle and 6-axle trucks respectively. Constraining the MC of the wood chips delivered to the power plant increases both transport and overall supply chain costs, due, firstly to an increase in the haulage distance and secondly, to the number of counties providing the biomass material. In terms of truck configuration, the use of 6-axle trucks resulted in a 14.8% reduction in the number of truckloads and a 12.3% reduction in haulage costs in comparison to the use of 5-axle trucks across the MC scenarios analysed. |
doi_str_mv | 10.1016/j.apenergy.2014.10.018 |
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In the coming years, Ireland will continue to face an increasing demand for wood biomass as a renewable source of energy. This will result in strained supply/demand scenarios, which will call for new planning and logistics systems capable of optimizing the efficient use of the biomass resources. In this study, a linear programming tool was developed which includes moisture content (MC) as a driving factor for the cost optimisation of two supply chains that use short wood and whole trees from thinnings as material feedstock. The tool was designed and implemented to analyse the impact of moisture content and truck configurations (5-axle and 6-axle trucks) on supply chain costs and spatial distribution of the supply materials. The results indicate that the inclusion of wood chips from whole trees reduces the costs of wood energy supply in comparison with only producing wood chips from short wood to satisfy the demand, with 9.8% and 10.2% cost reduction when transported with 5-axle and 6-axle trucks respectively. Constraining the MC of the wood chips delivered to the power plant increases both transport and overall supply chain costs, due, firstly to an increase in the haulage distance and secondly, to the number of counties providing the biomass material. In terms of truck configuration, the use of 6-axle trucks resulted in a 14.8% reduction in the number of truckloads and a 12.3% reduction in haulage costs in comparison to the use of 5-axle trucks across the MC scenarios analysed.</description><identifier>ISSN: 0306-2619</identifier><identifier>EISSN: 1872-9118</identifier><identifier>DOI: 10.1016/j.apenergy.2014.10.018</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Biomass ; Biomass supply chain ; Cost analysis ; Demand ; Logistics planning ; Moisture content ; Payload efficiency ; Supply chains ; Truck configuration ; Trucks ; Wood ; Wood chips</subject><ispartof>Applied energy, 2015-01, Vol.137, p.338-351</ispartof><rights>2014 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c426t-4e64a271f8dffe2f3b850259702747239fb64249173ad8d0dd104679a4b7bf9a3</citedby><cites>FETCH-LOGICAL-c426t-4e64a271f8dffe2f3b850259702747239fb64249173ad8d0dd104679a4b7bf9a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Sosa, Amanda</creatorcontrib><creatorcontrib>Acuna, Mauricio</creatorcontrib><creatorcontrib>McDonnell, Kevin</creatorcontrib><creatorcontrib>Devlin, Ger</creatorcontrib><title>Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland</title><title>Applied energy</title><description>•A linear programming model developed to optimise wood biomass supply chains for Ireland.•It uses MC to determine harvesting, chipping, storage and transportation costs.•It analyses two supply chain scenarios and two truck configurations specific to Irish conditions.•Low wood MC increases supply cost due to longer transport distances.•Optimal truck loads can be achieved by controlling wood MC.
In the coming years, Ireland will continue to face an increasing demand for wood biomass as a renewable source of energy. This will result in strained supply/demand scenarios, which will call for new planning and logistics systems capable of optimizing the efficient use of the biomass resources. In this study, a linear programming tool was developed which includes moisture content (MC) as a driving factor for the cost optimisation of two supply chains that use short wood and whole trees from thinnings as material feedstock. The tool was designed and implemented to analyse the impact of moisture content and truck configurations (5-axle and 6-axle trucks) on supply chain costs and spatial distribution of the supply materials. The results indicate that the inclusion of wood chips from whole trees reduces the costs of wood energy supply in comparison with only producing wood chips from short wood to satisfy the demand, with 9.8% and 10.2% cost reduction when transported with 5-axle and 6-axle trucks respectively. Constraining the MC of the wood chips delivered to the power plant increases both transport and overall supply chain costs, due, firstly to an increase in the haulage distance and secondly, to the number of counties providing the biomass material. In terms of truck configuration, the use of 6-axle trucks resulted in a 14.8% reduction in the number of truckloads and a 12.3% reduction in haulage costs in comparison to the use of 5-axle trucks across the MC scenarios analysed.</description><subject>Biomass</subject><subject>Biomass supply chain</subject><subject>Cost analysis</subject><subject>Demand</subject><subject>Logistics planning</subject><subject>Moisture content</subject><subject>Payload efficiency</subject><subject>Supply chains</subject><subject>Truck configuration</subject><subject>Trucks</subject><subject>Wood</subject><subject>Wood chips</subject><issn>0306-2619</issn><issn>1872-9118</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkU9vGyEQxVHVSHWTfoWKYy7rDCyG3Vsiq_kjReqlPSMWBhd3vWyAreRvHxyn5_Y0mqffe5rRI-QrgzUDJm_2azPjhGl3XHNgooprYN0HsmKd4k3PWPeRrKAF2XDJ-k_kc857AOCMw4os2ziVFMcxTDt6iCGXJSG1VcSpUDM5WtJif58UH3ZLMiXEKdMSK-xwfCPiXMIhZKRDiAeTM83LPI9Han-ZMNEx7mpqsJnW5SnhWC1X5MKbMeOX93lJft5_-7F9bJ6_Pzxt754bK7gsjUApDFfMd8575L4dug3wTa-AK6F42_tBCi56plrjOgfOMRBS9UYMavC9aS_J9Tl3TvFlwVx0vdPiWG_AuGTN5GajWs5q1n-grO0AOllReUZtijkn9HpO4WDSUTPQp0r0Xv-tRJ8qOem1kmq8PRux_vwnYNLZBpwsupDQFu1i-FfEKwUxmk0</recordid><startdate>20150101</startdate><enddate>20150101</enddate><creator>Sosa, Amanda</creator><creator>Acuna, Mauricio</creator><creator>McDonnell, Kevin</creator><creator>Devlin, Ger</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7SU</scope><scope>7TA</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>JG9</scope><scope>L7M</scope><scope>7ST</scope><scope>7U6</scope><scope>SOI</scope></search><sort><creationdate>20150101</creationdate><title>Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland</title><author>Sosa, Amanda ; Acuna, Mauricio ; McDonnell, Kevin ; Devlin, Ger</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c426t-4e64a271f8dffe2f3b850259702747239fb64249173ad8d0dd104679a4b7bf9a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Biomass</topic><topic>Biomass supply chain</topic><topic>Cost analysis</topic><topic>Demand</topic><topic>Logistics planning</topic><topic>Moisture content</topic><topic>Payload efficiency</topic><topic>Supply chains</topic><topic>Truck configuration</topic><topic>Trucks</topic><topic>Wood</topic><topic>Wood chips</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sosa, Amanda</creatorcontrib><creatorcontrib>Acuna, Mauricio</creatorcontrib><creatorcontrib>McDonnell, Kevin</creatorcontrib><creatorcontrib>Devlin, Ger</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Applied energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sosa, Amanda</au><au>Acuna, Mauricio</au><au>McDonnell, Kevin</au><au>Devlin, Ger</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland</atitle><jtitle>Applied energy</jtitle><date>2015-01-01</date><risdate>2015</risdate><volume>137</volume><spage>338</spage><epage>351</epage><pages>338-351</pages><issn>0306-2619</issn><eissn>1872-9118</eissn><abstract>•A linear programming model developed to optimise wood biomass supply chains for Ireland.•It uses MC to determine harvesting, chipping, storage and transportation costs.•It analyses two supply chain scenarios and two truck configurations specific to Irish conditions.•Low wood MC increases supply cost due to longer transport distances.•Optimal truck loads can be achieved by controlling wood MC.
In the coming years, Ireland will continue to face an increasing demand for wood biomass as a renewable source of energy. This will result in strained supply/demand scenarios, which will call for new planning and logistics systems capable of optimizing the efficient use of the biomass resources. In this study, a linear programming tool was developed which includes moisture content (MC) as a driving factor for the cost optimisation of two supply chains that use short wood and whole trees from thinnings as material feedstock. The tool was designed and implemented to analyse the impact of moisture content and truck configurations (5-axle and 6-axle trucks) on supply chain costs and spatial distribution of the supply materials. The results indicate that the inclusion of wood chips from whole trees reduces the costs of wood energy supply in comparison with only producing wood chips from short wood to satisfy the demand, with 9.8% and 10.2% cost reduction when transported with 5-axle and 6-axle trucks respectively. Constraining the MC of the wood chips delivered to the power plant increases both transport and overall supply chain costs, due, firstly to an increase in the haulage distance and secondly, to the number of counties providing the biomass material. In terms of truck configuration, the use of 6-axle trucks resulted in a 14.8% reduction in the number of truckloads and a 12.3% reduction in haulage costs in comparison to the use of 5-axle trucks across the MC scenarios analysed.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.apenergy.2014.10.018</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomass Biomass supply chain Cost analysis Demand Logistics planning Moisture content Payload efficiency Supply chains Truck configuration Trucks Wood Wood chips |
title | Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland |
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