Teijo Palander

Impacts of interenterprise collaboration and backhauling on wood procurement in Finland

The impacts of interenterprise collaboration were evaluated by examining the solutions for four experimental wood procurement cases. Three cases are based on actual wood procurement organizations. The other case is a hypothetical situation that assumes the integration of the organizations. Analysis of these situations allowed a theoretical examination of the benefits of integrating the transportation systems of the three largest wood industries. Two different timber-flow models were used for planning the procurement management: one described one-way transportation situations and the other described backhauling situations. The impacts of backhauling were evaluated by analysing the results of the modelling exercises. Eight different optimal solutions were examined and summarized. Costs and transported volumes were calculated for the wood procurement operations and for the entire wood procurement process. Transportation distances were also calculated. The results showed as much as a 20% reduction in transport costs with interenterprise collaboration. The total cost reduction due to interenterprise collaboration of the entire wood procurement process was 4% of the total cost without collaboration. The difference between the lowest and the highest average transportation distance was 36% of the highest average distance. The use of backhauling decreased transportation costs by 2% of the costs without backhauling and the total wood procurement costs by 0.3% of the total costs without backhauling for both the traditional and the collaborative transportation process. Therefore, the economic efficiency of wood procurement was increased specifically as a consequence of interenterprise collaboration.

Metrics for Distribution Similarity Applied to the Bucking to Demand Procedure

Abstract In the computerized bucking to demand procedure bucking is done according to a given price list and demand matrix, which defines the demands for different log length-diameter class proportions. To achieve as good a log length-diameter distribution as possible, the computer compares demand and actual output to appropriately direct bucking. A comparison has been made with a variable called distribution level, which, however, is unable to distinguish between error that is close to the optimum log length-diameter class proportion and error that is further away. In addition, the distribution level does not distinguish between log length-diameter classes, even though error in one class can be far more undesirable than in another. In this study, bucking to demand using the distribution level was compared to bucking to value and bucking to demand using the penalty segmented distribution level, squared distribution level, chi-square formula and flexible penalty segmented distribution level. The bucking outcome employing these various techniques was achieved by using a bucking simulator and artificially generated stand and stem data. The results show that the best bucking outcomes were produced by methods with a squared error term, i.e. the squared distribution level, chi-squared formula and flexible penalty segmented distribution level. In addition, it was possible to direct error toward preferred log length-diameter classes without substantial loss in overall goodness of fit.

Modeling Backhauling on Finnish Energy-Wood Network Using Minimizing of Empty Routes

Abstract This study introduces a support method to use in modeling backhauling. The method minimizes a truck’s on-road driving while empty. The backhauling model is based on a commonly used timber transport allocation model. Here, this model is applied to a simulated energy- wood network. The resulting optimization provides two different delivery plans for two-way transportation: one with a constraint to minimize travel distances when empty and the other without this constraint. By applying the empty-route minimization method, the best return routes for trucks are determined beforehand with fewer alternatives then left to be solved by the backhauling model. The results prove that the method can be used to minimize empty-route driving, but further development of the empty-route minimization method is still needed before it can be used in combination with the optimization of backhauling. Therefore, the effects of empty-route minimization on the transportation distances with respect to stand and hauling alternatives are discussed. In addition, the possibility of increasing the profitability of transportation, through the use of the method to optimize energy-wood backhauling, is also discussed.

A computer-supported group decision-making system for timber procurement planning in Finland

Abstract A group decision-making model was designed to improve co-operation during the process of making decisions to support timber procurement goals. The model was used in a Finnish forest company with a district team and six local teams. Co-operation among managers in the wood procurement organization was supported by decentralized synchronous groupware (MetaFrame), a computerized system where communication takes place over the Internet. This groupware provided the foundation for the decision-making system. The main research objective was to survey the opinions of the local managers towards the use of the system; it was assumed that co-operation would improve between managerial levels. Another objective was to investigate whether the groupware increased communication efficiency during this co-operation. The results showed that opinions on the computer-supported process were positive. The timber procurement goals were more acceptable to local teams when the goals and opinions of the district managers could be integrated into the decision-making process, and timber procurement planning was also faster (by 2 days). Therefore, the groupware increased communication efficiency and improved timber procurement planning as a consequence of the facilitated group decision-making process.

Adaptive Procurement Guidelines for Automatic Selection of Renewable Forest Energy Sources within a Sustainable Energy Production System

An automatic forest-stand selection method was developed that integrates the procurement of profitable energy sources within a sustainable energy production system. We tested the method using a forest harvester simulator. We found that site-specific estimates of forest characteristics are important when predicting the potential of an energy-wood stand as a renewable energy source. Further, tree parameters can be combined with automatic stem measurements from a multiple-tree harvester to predict the energy-wood biomass in the stands. The selection process uses data from profitability studies. The selection process also uses environmental criteria to ensure that sufficient soil organic matter is left behind and to protect the soil against erosion. The integrated system of the harvester automatically adapts the system’s models and stand-selection rules to account for various site-specific stand parameters. Predicting the profitable and environmentally acceptable yield of stand biomass has great potential in sustainable forest resource management, but managers must decide whether the operational procurement guidelines provided by the stand-selection method is acceptable under their local real-world wood procurement conditions.

Optimisation of renewable forest fuel supply for more sustainable energy production of CHP plant in Finland

In this study, a potential fuel procurement planning model to sustainable energy production problems is considered. In Finland peat is commonly used as a fuel of energy plants. However, it is recently considered as non-renewable fuel. Therefore, we tested the model using Finnish Government’s peat fuel tax policy decisions for sustainable energy production. However, due to the complex nature of the renewable fuel-procurement problem, the optimisation model cannot be directly used to solve the problem in a manner that is relevant to the forest industry. Therefore, this model was combined with an energy-production model to better describe the combinatorial complexity of energy flows. The properties of the model are discussed and we present the examples of how the model works based on real-world data and optional fuel procurement constraints. The results show peat and forest fuel relationships which indicate that meeting peat tax targets may not be adequate for the future success of renewable energy production, because energy production costs are increasing and forest fuel procurement targets can not be achieved.

Applying polynomial regression modeling to productivity analysis of sustainable stump harvesting

ABSTRACT Modern computerized energy systems are necessary in economically sustainable wood procurement. Previous studies have shown that productivity variation increases for larger stump diameters of the lifted stumps and the changes can be either negative or positive. For this reason, new studies on stump harvesting should focus on robust productivity models for the computerized energy systems, which will provide economically sustainable stump procurement. This paper presents an estimation of two different productivity models using polynomial regression based on the machine, time, soil, stand, and biomass data. An unconstrained polynomial model yielded slightly decreasing productivity for diameters above 50 cm. Therefore, we fitted a constrained model that provided increased productivity for larger stumps up to 70 cm diameter. It is better justified by the theory, and the evidence against the constrained model was only slight (p > .05) within the diameter range of our data. Based on our comparison of the productivity measurements, the best practice model is discussed to enable an efficient computerized energy system for sustainable stump procurement.

Work system study of three stump-lifting devices in Finland

Stump and root wood procurement has increased in the twenty-first century in Finland. Potential amounts of techno-economically harvestable stump wood account for 2–11 TWh, depending on the cost-efficiency of the stump procurement. For increasing stump wood consumption of energy plants lifting technology of stumps requires further development. In this research, three stump-lifting devices were compared. These devices were connected to human–machine systems which operated in similar study stands. Based on the machine, time, stand, cost and biomass data, productivity and cost-efficiency of the stump-lifting devices were determined in the work system study. The productivity of stump lifting was 16.4 m³ sob/process-hour (7.1 tD/process-hour) to the stumps with a diameter of 40 cm on sites processed using Terosa stump-lifting device and Hakkilas biomass model were used in the system. Further, the stump-lifting costs with Terosa were around 37% (sob/E0-hour) lower than those of Väkevä and Xteho. In this respect the machinery equipped with Terosa provides the cost-efficient stump-lifting system. Based on herein reported study, it can be stated that Terosa is a promising stump-lifting device that enables cost-efficient extraction of stump wood.

Applying dynamic multiple-objective optimization in inter-enterprise collaboration to improve the efficiency of energy wood transportation and storage

In Finland, VR Group (the state-owned railway company) provides third-party logistics services (3PLs) for industrial customers. Their current static, single-objective optimization model does not support inter-enterprise collaboration to achieve optimal railway logistics. In this study, I introduce a collaborative decision-support method that can be applied to manage railway traffic under a scenario of increasing imports of Russian wood. Based on the data obtained to support this research, I describe railway traffic strategy scenarios in terms of 3PLs to account for the changed energy wood transportation and storage needs related to imported Russian wood. In the scenarios, the railway wagon rotation was adjusted to reach a globally optimal strategy that achieves efficient wood procurement logistics for the Finnish forest industry. These decisions were based on a comprehensive logistics analysis of the integrated wood demand and a supply chain model for southeastern Finland in the context of collaborative decision-making among members of the logistics chain. The model, which is based on dynamic multiple-objective linear programming, supports inter-enterprise collaboration because the adaptation of Russian wood imports to the regional railway transportation environment will require continuous, integrated optimization of the flows of wood and railway wagons.

Potential methods of adjustment to declining imports of Russian roundwood for the Finnish pulp and paper industry

Purpose – The purpose of this paper is to investigate optimal strategic decision alternatives for Finnish pulp production companies in response to rising export tariffs on Russian roundwood. Traditionally, increasing the domestic or Russian supply to pulp mills satisfied their wood requirements. However, once this conventional strategy could no longer be implemented (in 2008), the wood requirements were met by adjusting pulp production (reducing) and wood procurement (increasing domestic procurement).Design/methodology/approach – As the primary research data for the study, the procurement situation in 2005 was used to describe the conventional business strategy for purchasers of Russian or domestic roundwood. Possible business strategies were then simulated for changing pulp production by Stora Enso, with the goal of adjusting roundwood requirements, to develop a globally‐optimal strategy to solve the procurement problem.Findings – After removing production by the northernmost Finnish pulp mill, the autho...