Fuel Consumption in Timber Haulage
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Original scientific paper – Izvorni znanstveni rad Fuel Consumption in Timber Haulage Radomír Klvač, Josef Kolařík, Marcela Volná, Karel Drápela Abstract – Nacrtak The paper presents an assessment of road timber transport by trucks, which included 132 truck-and-trailer units – three types of trucks (Tatra, Mercedes Benz and Iveco) with a selec- tion of trailers in the Czech Republic. The main aim of this work was to establish the effect of hauling distance in the individual types of timber-transport units on the fuel consumption per 100 km and on the specific fuel consumption per one transported cubic metre of timber. Any decrease of fuel consumption per unit of production can enhance environmental profile of secondary transport. Freight transport recorded conspicuous changes in the last ten years, and the analysis presented in this work provides important information useful in the planning and organization of road timber transport. During the study period, obsolete and inadequate truck-and-trailer units were continuously replaced with new units, which resulted in a con- siderable reduction in fuel consumption per unit of production (0.5 L/m3 ub). Keywords: haulage road, timber transport, truck, truck-and-trailer unit, fuel consumption 1. Introduction – Uvod transport units and classified them into the following groups: vehicle characteristics, trailer characteristics, Timber transport from the roadside landing to the road geometry, road surface, goal speed, gear change, customer represents a very demanding phase in the driving behavior, weather and road surface conditions. chain of timber supply in terms of energy and cost. It The above factors of technical and technological is characterized by several specific factors that influ- character have a considerable influence on the average ence its implementation and differentiate it from the fuel consumption of timber truck-and-trailer units, goods transport by trucks. In general, we can say that it is a one-way haulage, where it is very difficult or which may be double as compared with the common even impossible to utilize the timber-transport unit in road goods transport by trucks (Devlin 2010). its return run. The machines are specifically designed The number of information systems specialized in and can be used only to a limited extent for the haul- goods or bus transportation is high in the Czech Re- age of other goods. Also, they have to drive a larger public but the number of information systems special- part of the hauling distance on forest roads. Holzleit- ized in timber transport is low. Hauling timber from ner (2009) and Holzleitner et al. (2011) studied the op- the roadside landing features problems such as het- eration of timber-transport units by using the GPS/GIS erogeneity of the transported material, difficult utiliza- system and concluded that the share of their travel on tion of vehicles at their return run, seasonal character forest roads was 14%. The machines often have to of operations, climatic effects – all these resulting in a drive deep into the forests and have to be adapted ac- high rate of »empty« drives. Data processing, trans- cordingly. They have to work in difficult field condi- port optimization and necessity of flexible response to tions and therefore they are very frequently affected unexpected situations put high requirements both on by them as well as by extreme seasonal weather. This the information system and on timber haulage manag- is why the trucks are often equipped with the multi- ers. This is why an information system was designed, ple-wheel drive and heavy-duty engines. These spe- which tries to respond to the absence of information cific technological requirements considerably increase systems in the field of timber haulage (Klvač 2006). fuel consumption of timber-transport units. From the economic point of view, the share of tim- Svenson (2011) mentioned a range of technical fac- ber haulage in total timber supply chain costs may tors directly affecting the fuel consumption of timber- reach more than 30% (Favreau 2006). He mentions that Croat. j. for. eng. 34(2013)2 229 R. Klvač et al. Fuel Consumption in Timber Haulage (229–240) transport is the biggest cost item in round wood costs The structure of the assessed data related to this in Canada. In Sweden, Svenson (2011) says that 35% study was as follows: of total transportation costs are related to the fuel con- Þ Truck-and-trailer unit, inventory number pro- sumption of timber trucks. Economic data provided vided for non-commutability of data, by the contractor of timber-transport units, which Þ TTU operational centre, were the subject of our study, demonstrated that diesel Þ Trailer, inventory number, fuels accounted for the highest share in total costs Þ Total travel distance, km, (30%), followed by depreciation and leasing (20%) and repairs and maintenance (16%). Wages (15%), over- Þ Travel unloaded, km, head costs (13%) and other costs (5%) followed. The Þ Travel loaded, km, objective of implementation of the information system Þ Backhauling, % of kilometers driven loaded, was to conduct a basic analysis of individual types of Þ Volume of transported timber, m3 ub; softwood timber-transport units and based on the acquired data and hardwood, to find primary relations affecting transport efficiency Þ Number of loads per month and per day, and thus to find ways how to reduce the cost of timber Þ Average size of load, m3 ub, haulage. Þ Average hauling distance – one way distance, km, Any decrease of fuel consumption per unit of pro- Þ Fuel consumption in liters per month. duction can enhance environmental and economy profile of secondary transport. As the fuel cost makes Parameters that were calculated based on the above the largest part of total timber haulage costs, the aim data were as follows: of this work is to analyze the fuel consumption in the Þ Average fuel consumption per unit of produc- 3 individual types of truck-and-trailer units used in tim- tion, llm ub ber transport. Any replacement of obsolete and inad- Þ Average fuel consumption per 100 km, ll100 km equate truck-and-trailer units by new more efficient All data were checked at first and records contain- units can result in a considerable reduction of fuel con- ing gross errors caused by human factor at recording sumption per unit of production. were eliminated. Then the data were imported and organized within the spreadsheet software (Microsoft 2. Material and methods – Materijal Excel) and subsequently summarized for individual types of TTUs. In the period 2005 – 2009, considerable i metode changes occurred in the fleet of timber transport units A »tailor made« information system was designed with obsolete TTUs being put out of operation and in 2003, which can receive orders placed by customers, replaced by new TTUs where necessary. Old and tech- support the decision-making process of dispatchers by nically unfit Liaz TTUs were taken out of service first. using suitable truck-and-trailer units (TTU), make re- As the amount of data on these TTUs was not repre- cords of hauling performance, monitor production in sentative, the Liaz type of TTU was not statistically progress and summarize data in the form of databases. evaluated in this study. Types of truck-and-trailer In 2004, the system was characterized in the form of units assessed in this study were Iveco (represented diagrams so that designers would be capable of meet- by models ASTRA, MP260 and STRALIS), Tatra (rep- ing customer requirements (Klvač 2006). This informa- resented by Tatra 815 only), Mercedes Benz (models tion system was designed for larger companies with a 3344, 3341, 2644 and 3348). The data were aggregated greater number of vehicles dislocated on remote work- and analyzed according to truck manufacturers. places. All workplaces had an access to the system via The initial analysis was made with the use of pivot- client and worked with data on multiple levels related ing (contingency) tables and graphs. GraphPad Prism to the position in company or business interrelation- 5 (Motulsky 2007) was used for non-linear regressions. ship. Each position/client type had centrally set rights The software enables a very flexible choice of the re- and responsibilities in the system. A timber transport gression model, it has very good graphical capabilities company implemented the system at the beginning of and provides the possibility to compute and draw con- 2005 and data on each individual transportation case fidence intervals of the model. Prism 5 can eliminate started to be recorded from the end of the same year. outliers with the ROUT method (Motulsky and Brown The data was summarized for each TTU in monthly 2006). This method is based on a new robust non-lin- intervals for purposes of analytical assessment by the ear regression combined with outlier rejection. It is an company management. The monthly indicators of adaptive method that gradually becomes more robust TTUs were used in this study. as the method proceeds. Press et al. (1988) based their 230 Croat. j. for. eng. 34(2013)2 Fuel Consumption in Timber Haulage (229–240) R. Klvač et al. robust fitting method on the assumption that variation 2 548. The total number of TTUs assessed in the period around the curve follows a Lorenzian distribution 2005 – 2009 was 134 and the units were operated at rather than a Gaussian distribution. The Marquardt different places in the Czech Republic. In the period non-linear regression algorithm was adapted to ac- 2003 – 2004, we monitored only 21 trucks; this number commodate the assumption of a Lorenzian (rather increased in 2005 to 90. In the following years, the fleet than Gaussian) distribution of residuals. After fitting was gradually renewed and some old vehicles were a curve using robust non-linear regression, a threshold put out of operation.