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A proper record of the actual harvestable resource will be an essential prerequisite for the development of a preliminary harvest plan with the usable sites scheduled for harvest according to age, tonnage and location. A modest amount of harvesting, perhaps 20-40,000 green tonnes per year could be sustained from the existing resource, but to determine a reasonable estimate of the cost of harvesting and transporting this material should be based upon verified site data. A regional industry harvesting plan will also enable the modelling of resource flow over the first cycle of harvest, followed by the coppice regeneration for second and subsequent harvests. Overlaid upon this will be the wave of new planting that should be stimulated by the first cycle of harvesting and biomass payments. The West Australian mallee industry has a number of problems to resolve but new plantings are still being established every year, even though at a modest rate. 6.4.2 Operational planning and modelling Operational or Logistic models are typically used to focus on the supply of product from the field to the processing facility. In the sugar industry this has focused on reducing harvest to crush delays, improving capacity utilization, improving scheduling to match delivery to mill crushing capacity. These models describe the path followed by a consignment of cane with the aim to pinpoint bottlenecks (Gaucher et al 2003). Changes in the supply chain can be evaluated with a detailed description of the tasks of handling and delivering the material. Information is based on cutting, loading, transport equipment (size, number, hourly capacity, work schedule, distance, speed, downtime, etc). The approach can be used to investigate • impact of restructuring the supply system, e.g. by closing or opening transloading centres to modify distance from fields, • introducing new harvesting, transport and milling equipment, or • changing delivery allocations to match the harvest capacities of growers. In the Mallee Industry a logistics modelling approach has been adopted by McCormack et al (2009) who have modelled the cost per green tonne delivered to the mill based on various harvesting and transport options. This work highlights the operational difficulties in the Mallee Woody crop supply chain and was discussed in Section 3.2.3 of this report. Operational issues include: • The Plant itself (Small stem size, poor presentation to harvester with multiple crooked stems and high wood density) • Field layout (Two to four row belts, 100-200m apart with low yield of 40-80gt/ha of belt or 100-400 green tonnes per farm and long transport distances to roadside landing of 1-4km) • Harvest/Handling issues (difficulties in pouring, tipping and handling wood chips and associated leaf and twig and low bulk density). The logistics work undertaken by McCormack et al (2009) provides a start for conceptual logistics modelling. Chapter 7 of this report provides a comparative assessment of costs of harvest and transport of mallee based on current sugarcane harvest-haul models. 6.5 Models for Supply Chain Planning and Management - Examples for Sugarcane In Australia sugarcane supply chain modelling, planning and management tools have looked at a range of aspects as detailed in Higgins and Archer (2005) including: 149
• Harvest and transport logistics. • Business integration, information transparency and assessment of new payment formulas. • Assessment of product diversification and new markets through co-generation. This section provides a brief overview of these tools with some examples of their application in specific mill areas. The key message is that modelling provides a powerful tool to assess supply chain development and management, however, it needs to be site and situation specific and does not always ensure adoption for the reasons discussed in section 6.1 to 6.3. Most research has focused on logistical opportunities, particularly in the harvesting and transport sectors which provide more challenges than other sectors. Opportunities such as harvester/siding rosters, time of window harvesting, scheduling have benefits that are easy to quantify and assess and can be adopted without extensive changes to current systems (Higgins and Archer, 2005). Non logistical opportunities have focused on increased information transparency, building new markets or business process integration. While there have been many models developed within the Australian sugar industry they generally only consider activities or processes in a single sector (see Table 6.1). It is only relatively recently that there has been development of multi-sector models, focussing on the interface between the harvesting and transport sectors. Thorburn et al (2006) applied these modelling techniques in a participatory environment to allow groups within mill regions to more thoroughly evaluate diversification options of their sugar value chains in their region, and so move forward with more confidence and greater understanding than would have occurred with previous approaches. Table 6.1 Examples of the processes that have been modelled within the different sectors of the Australian sugar industry (Thorburn et al 2006). Sugarcane production Harvesting Transport Milling/Factory • Cane and sugar growth, responding to: − Nitrogen − Irrigation − Trash blanket dynamics • Statistical CCS and cane yield estimation • Harvest haul model • Harvesting group roster optimisation • Harvesting group-tosiding optimisation • Capacity planning tools for transport • Road transport schedule optimisation • Siding location and pad optimisation • Rail transport schedule optimisation and schedule checking simulation models • Raw sugar manufacture • Cane handling • Trash separation • Co-generation Underpinned by: • GIS techniques • Database techniques for whole-of-industry models • Field and satellite information • GPS and vehicle tracking 150
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Sustainable Biomass Supply Chain fo
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Foreword This report provides an as
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include business development (new p
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Acknowledgments The authors would l
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4.1 Product Options and Supply Chai
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Table 4.2 Assessment of current val
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Figure 3.4 Tracked rigid self-prope
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Executive Summary What the report i
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• Biomass production potential of
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• As the Industry expands, the mo
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Harvesting, transport and storage s
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Biomass processing, supply chain pl
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Key barriers to biomass industries
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Crop-Biomass Production Production
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Figure 1.1 The cropping and pasture
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Table 1.1 Mallee species used for p
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1.1.4 Growth Cycle Mallee System Ma
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northern New South Wales (where it
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Almost 80% of the industry now cuts
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Bark has relatively high ash but as
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Carbon sinks Planting of mallees to
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Table 1.5(a) State Land area devote
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out the fluctuations in farm income
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Mallee system Most of the mallee bi
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inconclusive result may have been d
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For a sustainable woody crop indust
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changed significantly since they we
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Figure 2.2 Biosystems Engineering p
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Whole-of-crop harvesting represents
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During the last decade the harvesti
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single row, as this would improve t
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2.2.2.2 Weight Sugar System The Aus
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Table 2.1 Harvester Comparison Tabl
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The quality of cut may be less impo
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ate than a 170 tonne/ha crop of sta
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Dry Leaf 6.1 - 3.5 17.0 58.9 53.2 T
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Bulk density will be a key consider
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Table 2.4 EM levels in cane supply
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L/T L/T 60 0.97 0.71 80 0.92 0.66 1
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Total 7.5-26 16.5 Mallee System The
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• waiting for mill delivery of em
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perhaps at 10 - 20 km intervals. Th
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transport arrangements, harvest gro
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contractors and growers, and the fa
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experience of the sugar industry wi
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Table 2.11 Alternative harvest paym
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onto the harvester. BR+F still send
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Repairs and maintenance 2.10 Capita
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Figure 2.14 and Table 2.14 describe
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Sichter et al. (2005)), harvest and
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Transport efficiencies may be possi
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3. Transport and Storage Systems Tr
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same time, the potential problems o
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Figure 3.3 Articulated self-propell
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• The harvester will not have any
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Figure 3.7 Gross mass compared with
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external factors dramatically impac
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Figure 3.11 The effect of haulout t
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3.3 Road Transport 3.3.1 Configurat
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Figure 3.15 shows an example of the
Page 121 and 122: Road distance one way < 20 km 70 km
Page 123 and 124: Haul distance is largely outside th
Page 125 and 126: 3.6 Recommendations The nature of t
Page 127 and 128: • The strategy offered lower tota
Page 129 and 130: sugarcane billets are such that wit
Page 131 and 132: • Transfer the whole tree product
Page 133 and 134: Figure 4.5(b) Energy balance of con
Page 135 and 136: 2010). Table 4.2 presents a summary
Page 137 and 138: 4.4.2 Activated charcoal Activated
Page 139 and 140: Nett Product Value ($/t) $475.00 $
Page 141 and 142: Table 4.9 presents an estimation of
Page 143 and 144: • Oil from leaf @ $2/kg • Synth
Page 145 and 146: • The mallee oil would be extract
Page 147 and 148: 5. Industry and Business Structures
Page 149 and 150: is conducted into tariff levels on
Page 151 and 152: Bx is % brix in first expressed jui
Page 153 and 154: Hildebrand (2002) estimated that th
Page 155 and 156: also has a flow on effect to the sp
Page 157 and 158: Sugar Industry Illustrative Example
Page 159 and 160: with super size multi-lift bins ove
Page 161 and 162: farmer vs. harvester) is the next l
Page 163 and 164: 6. Supply Chain Planning and Manage
Page 165 and 166: Figure 6.1 Building blocks of the s
Page 167 and 168: weighed against the costs of operat
Page 169 and 170: • There is close contact between
Page 171: 6.4 Planning, Management Tools and
Page 175 and 176: interface. The system allows users
Page 177 and 178: Case Study 6.2 - Model Application
Page 179 and 180: Relationships between sectors and p
Page 181 and 182: 7. Supply Chain Modelling and Econo
Page 183 and 184: It was assumed that there was a fif
Page 185 and 186: Table 7.2 Scenario two capital equi
Page 187 and 188: Table 7.4 Fuel burn rates harvester
Page 189 and 190: Figure 7.5 Effect of capital equipm
Page 191 and 192: Figure 7.7 Effect of annual tonnes
Page 193 and 194: 30 1.8 7.0 12.3 17.5 50 1.1 4.3 7.6
Page 195 and 196: 8. Conclusions and Recommendations
Page 197 and 198: Biomass bulk density has a large im
Page 199 and 200: Vehicles used for infield haulout w
Page 201 and 202: This can be compared with harvest a
Page 203 and 204: While diversification can add value
Page 205 and 206: Appendix 1: Comparative Assessment
Page 207 and 208: and transport conditions. Billet le
Page 209 and 210: that cane production is the most pr
Page 211 and 212: on sugar only, other proceeds (mola
Page 213 and 214: References Agnew, J 2002. A Partici
Page 215 and 216: Enecon 2001. Integrated Tree Proces
Page 217 and 218: Keating, BA, Antony, G, Brennan, LE
Page 219 and 220: Ridge, DR and Linedale, AL, 1997. T
Page 221: Willcox, T, Hussey, B, Chapple, D a
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