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2.4 Harvester Performance Monitoring To ensure harvesting machines are suited to their operating conditions and crop characteristics they are working in, and are achieving optimum productivity their performance must be evaluated. Performance is a measure of some output or behaviour and is the first step to improving productivity. The information that is collected can help match appropriate machinery to site conditions and determine if machines are performing optimally. 2.4.1 Loss Processes Sugar System The process of harvesting sugarcane to produce a product low in or free of extraneous matter (EM) has always been accompanied by the loss of millable cane. This loss increased considerably with the change from whole-stalk to ‘chopped cane’ harvesting and has been exacerbated with the move into green-cane harvesting with the increased demand for removal of EM (Brotherton 2002). There has always been an industry awareness of the cane loss problem, but the magnitude of losses has been hidden to a large extent by the invisible nature of the loss. That is, desiccated billets through the extractor fan are difficult to identify and cane and sugar loss is difficult to measure. Industry has demanded increased machine throughput, and this has, to some extent, overridden the effectiveness of measures to minimise cane loss in harvesting. Harvesting losses occur throughout the harvesting process, from feeding and gathering through to chopping, cleaning and transferring to infield haulouts. Whilst losses have generally been presented as cane loss, the loss of Pol (a sucrose approximation) and loss of CCS (recoverable commercial sugar) have become more relevant indicators in recent years as these are the intended products of the current industry. These parameters also respond to stalk degradation and deterioration that are omitted in cane loss. Brotherton (2002) considered that an accurate, absolute magnitude of loss is necessary for economic evaluation of harvesting losses. The Australian sugar industry has invested significant resources in the assessment and measurement of losses during cane harvesting. Table 2.7 shows the typical losses from various components of the harvester during harvesting. Table 2.7 Typical cane losses during harvesting (SRDC, 2004) Process Losses Losses Range, % Average, % Gathering 1-2 1.0 Basecutter 1-3 2.0 Feedtrain/Chopper 2-6 4.5 Extractor 3.5-15 9.0 55
Total 7.5-26 16.5 Mallee System There is no quantitative data on losses during harvesting as the prototype harvester has not undergone commercial testing. The main loss processes would include gathering, chipping and spillage during transfer to the infield transport. As there is no separation of the product on the harvester, there are no losses from this process like in sugarcane harvesting. Losses during gathering may include branches, twigs etc expelled during felling and feeding. The aim is to have minimal gathering losses as whole branches, limbs etc would need to be cleaned up to avoid contamination of neighbouring crops. This clean-up would add significantly to the cost of harvesting if it was a measurable quantity. There may also be losses of chip thrown out of the chipper mechanism. It is likely that the losses as a percentage of harvested material will be insignificant, as shown in Figure 2.6 in section 2.3.1. 2.4.2 Real-time monitoring systems Sugar System The manufacturers approach to performance monitoring of sugarcane harvesters during harvesting has been to provide only the condition analysis of the mechanical components such as the engine and hydraulic circuitry. For example, engine hours, engine speed, oil temperature and hydraulic oil level, temperature and component pressures (chopper, basecutter, feed train) are available. The only condition reported on performance with respect to machine-crop interaction is basecutter height and primary extractor fan speed. Measuring field and other variables affecting machine performance is necessary to encourage more efficient harvesting, reducing costs and increase industry profitability through reducing field losses of cane and juice during mechanical harvesting. Hildebrand (2002) viewed recovery of any substantial loss of sugar in the field during harvest as being the most obvious and potentially the least costly economic gain available. Therefore, a major opportunity for the sugar industry is to significantly increase industry profitability without increased capital investment. This can be achieved by reducing field losses of cane and juice during mechanical harvesting. Adopting Harvesting Best Practice (HBP) with attention to extractor fan speed, pour rate, feed train and chopper speed synchronisation, basecutter height control and row profile, row length and cane presentation has two main outcomes. It increases the amount of cane delivered to mills and reduces the potential for environmental impacts associated with sugar juice entering waterways causing de-oxygenation (SRDC 2004). Agnew (2002) reported that better and timelier feedback is vital to overcome the flawed harvesterpayment system and enable negotiation of the best possible job at an acceptable price for individual blocks. Various technologies have been researched and developed to provide machine performance feedback or automate machine operations to favour higher harvesting efficiency and higher sugar recovery. These include automatic basecutter height control, synchronising component speed with ground speed, cane loss monitoring, ground speed and pour rate monitoring, harvester efficiency and cane yield monitoring. The aim of these technologies is to optimise on-the-go, the interaction between 56
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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
Page 27 and 28: Crop-Biomass Production Production
Page 29 and 30: Figure 1.1 The cropping and pasture
Page 31 and 32: Table 1.1 Mallee species used for p
Page 33 and 34: 1.1.4 Growth Cycle Mallee System Ma
Page 35 and 36: northern New South Wales (where it
Page 37 and 38: Almost 80% of the industry now cuts
Page 39 and 40: Bark has relatively high ash but as
Page 41 and 42: Carbon sinks Planting of mallees to
Page 43 and 44: Table 1.5(a) State Land area devote
Page 45 and 46: out the fluctuations in farm income
Page 47 and 48: Mallee system Most of the mallee bi
Page 49 and 50: inconclusive result may have been d
Page 51 and 52: For a sustainable woody crop indust
Page 53 and 54: changed significantly since they we
Page 55 and 56: Figure 2.2 Biosystems Engineering p
Page 57 and 58: Whole-of-crop harvesting represents
Page 59 and 60: During the last decade the harvesti
Page 61 and 62: single row, as this would improve t
Page 63 and 64: 2.2.2.2 Weight Sugar System The Aus
Page 65 and 66: Table 2.1 Harvester Comparison Tabl
Page 67 and 68: The quality of cut may be less impo
Page 69 and 70: ate than a 170 tonne/ha crop of sta
Page 71 and 72: Dry Leaf 6.1 - 3.5 17.0 58.9 53.2 T
Page 73 and 74: Bulk density will be a key consider
Page 75 and 76: Table 2.4 EM levels in cane supply
Page 77: L/T L/T 60 0.97 0.71 80 0.92 0.66 1
Page 81 and 82: • waiting for mill delivery of em
Page 83 and 84: perhaps at 10 - 20 km intervals. Th
Page 85 and 86: transport arrangements, harvest gro
Page 87 and 88: contractors and growers, and the fa
Page 89 and 90: experience of the sugar industry wi
Page 91 and 92: Table 2.11 Alternative harvest paym
Page 93 and 94: onto the harvester. BR+F still send
Page 95 and 96: Repairs and maintenance 2.10 Capita
Page 97 and 98: Figure 2.14 and Table 2.14 describe
Page 99 and 100: Sichter et al. (2005)), harvest and
Page 101 and 102: Transport efficiencies may be possi
Page 103 and 104: 3. Transport and Storage Systems Tr
Page 105 and 106: same time, the potential problems o
Page 107 and 108: Figure 3.3 Articulated self-propell
Page 109 and 110: • The harvester will not have any
Page 111 and 112: Figure 3.7 Gross mass compared with
Page 113 and 114: external factors dramatically impac
Page 115 and 116: Figure 3.11 The effect of haulout t
Page 117 and 118: 3.3 Road Transport 3.3.1 Configurat
Page 119 and 120: 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
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sugarcane billets are such that wit
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• Transfer the whole tree product
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Figure 4.5(b) Energy balance of con
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2010). Table 4.2 presents a summary
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4.4.2 Activated charcoal Activated
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Nett Product Value ($/t) $475.00 $
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Table 4.9 presents an estimation of
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• Oil from leaf @ $2/kg • Synth
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• The mallee oil would be extract
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5. Industry and Business Structures
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is conducted into tariff levels on
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Bx is % brix in first expressed jui
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Hildebrand (2002) estimated that th
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also has a flow on effect to the sp
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Sugar Industry Illustrative Example
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with super size multi-lift bins ove
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farmer vs. harvester) is the next l
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6. Supply Chain Planning and Manage
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Figure 6.1 Building blocks of the s
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weighed against the costs of operat
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• There is close contact between
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6.4 Planning, Management Tools and
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• Harvest and transport logistics
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interface. The system allows users
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Case Study 6.2 - Model Application
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Relationships between sectors and p
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7. Supply Chain Modelling and Econo
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It was assumed that there was a fif
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Table 7.2 Scenario two capital equi
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Table 7.4 Fuel burn rates harvester
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Figure 7.5 Effect of capital equipm
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Figure 7.7 Effect of annual tonnes
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30 1.8 7.0 12.3 17.5 50 1.1 4.3 7.6
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8. Conclusions and Recommendations
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Biomass bulk density has a large im
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Vehicles used for infield haulout w
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This can be compared with harvest a
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While diversification can add value
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Appendix 1: Comparative Assessment
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and transport conditions. Billet le
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that cane production is the most pr
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on sugar only, other proceeds (mola
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References Agnew, J 2002. A Partici
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Enecon 2001. Integrated Tree Proces
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Keating, BA, Antony, G, Brennan, LE
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Ridge, DR and Linedale, AL, 1997. T
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Willcox, T, Hussey, B, Chapple, D a
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