Haulage Costs Research Articles

Integrated Planning of Timber Extraction and Hauling Activities by using Network 2000 Program

Planning of forest transportation is a complex problem that requires effective and harmonious design and implementation of various forest operations including extraction, loading, and hauling of forest products. These operations constitute a significant part of the total cost of producing forest products; therefore, developing the most appropriate (minimum cost/maximum net profit) transportation plan has increasing importance for the economic aspect. Computer-aided models can be used to plan the transportation of forest products and systematically searching for the most suitable solution. In this study, a network analysis-based Network 2000 program was used to determine the optimum routes with minimum forest operation costs and maximum net profit of forest products considering two logging truck types (medium and large size). In the solution process, two farm tractors (4x2 and 4x4) for extraction operation and two loaders (tracked and rubber-tired) for loading operation were evaluated. The alternative with the minimum cost was determined using the Network 2000 program. The study was implemented in Kınık Forest Enterprise Chief (FEC) located in the city of Bursa in Turkey, while considering five landing areas where various forest products (i.e. log, mine poles, industrial wood, and paper wood) were extracted from the six harvesting units and hauled to two forest depots. In the study, the optimum solution was searched for two scenarios where only the forest depot which is commonly used in the Kınık FEC was considered in the first scenario while the forest depot of the neighboring enterprise in the region was also evaluated in the second scenario. The results obtained from the first scenario indicated that using large-size tractor reduced the hauling cost by 8% which led to over 1000 TRY reduction in the total cost of forest operations. The hauling cost and total forest operation cost obtained in the second scenario was about 16% and 2% less than that of the cost obtained in the first scenario for the case of large-size truck. On the other hand, total net profit of the forest products received in the second scenario was about 35000 TRY more than that of the net profit received in the first scenario for the case of large-size truck. The optimum farm tractor for skidding operation was successfully selected by the Network 2000 program considering terrain conditions in the harvesting unit and availability of the equipment. Likewise, optimum loader was also determined by considering distribution of the forest products on the landing areas.

Assessing the Economic Viability of the Mechanized Removal of Understory Beech during a Shelterwood Harvest

Abstract Beech bark disease is a pathogenic complex that has been spreading throughout the American beech’s range since the 1800s. A litany of negative consequences have manifested from the infestation of this disease, many of which deteriorate the ecological functions of forestland. This case study sought to analyze the cost structure for removing a recalcitrant beech understory via mechanized shelterwood harvesting. High-resolution data regarding the day-to-day operation of harvesting equipment was collected using daily production journals. Interviews were conducted with the logging company owner and maintenance supervisor to gather additional information required to calculate machine costs, overhead, job specific costs, and trucking costs. The yield from this harvest was 527 metric tonnes of sawtimber and 4,893 tonnes of clean chips. The total harvesting cost equated to $4,651/ha, with the cost attributed to removing beech at $204/ha. Despite the additional cost of beech removal, the logger generated a total profit of $5,965 and a return on investment of 7.5%, allowing us to conclude that mechanized harvesting can be a viable beech removal strategy given the forest stocking and market conditions that are in place.

Transportation cost analysis on alternative wood feedstocks for manufacturing wood-plastic composites

This study evaluated and analyzed transportation costs for manufacturing wood-plastic composites (WPCs) using wood flour and wood pellet feedstocks. The study area ranged from Maine (ME) to Massachusetts (MA) in the Northeast region of the United States (US). Wood mills in ME were the raw material providers, and the WPC manufacturers in ME and MA were the destinations. The methodologies included the Origin-Destination (OD) cost matrix feature in ArcGIS to find least-cost pathways from each facility to each destination; baseline scenarios based on trucking costs, travel distances, and wood feedstocks; and sensitivity analyses to study the effects of fluctuating input variables (travel distance, shipment weight, and shipping costs over distance) to the shipping costs by weight. Accordingly, the best and worst-case scenarios were identified. The OD-cost matrix showed that shipping feedstocks from southern ME required shorter travel distances than from other regions because of proximity. Transporting wood pellets in a truck would reduce shipping costs by at least 25% compared to wood flour. The shipping costs by weight were inversely related to the shipment weight. The shipment weight of wood pellets was higher than flour in a truck trailer with fixed volume. It is foreseen that the transportation of wood pellets as opposed to wood flour would be economical.

Perceptions of Log Truck Weight Regulations Among Loggers and Forest Industry in Georgia, USA

Abstract Georgia and other southern states have far lower gross vehicle weight (GVW) limits for log trucks than other US regions and other countries. Low GVW limits result in high hauling costs and truck traffic. In 2020, including tolerances, five-axle log tractor-trailers were allowed 38,102 kg (84,000 lb) GVW in Georgia. Telephone surveys of 30 loggers and 32 forest industry representatives from the state of Georgia were conducted to measure perceptions of weight regulations and assess support for alternative weights and configurations. The four alternatives included five axles, 39,916 kg (88,000 lb); six axles, 41,277 kg (91,000 lb); six axles, 45,359 kg (100,000 lb); and seven axles, 45,359 kg (100,000 lb) GVW. The majority of loggers and forest industry representatives stated that GVW limits for log trucks were too low. The average preferred GVW limits were 39,621 kg (87,350 lb) and 40,545 kg (89,387 lb) for loggers and forest industry, respectively. Loggers and forest industry supported the five-axle 39,916 kg (88,000 lb) configuration whereas many loggers opposed both 45,359 kg (100,000 lb) configurations. Loggers, forest industry, and policymakers should work to modernize weight laws to reduce hauling costs, maintain or improve safety, and protect public infrastructure.

Design and Evaluation of Asphalt Concrete Incorporating Plastic Aggregates Fabricated Using 3D Printing Technology.

Environmental protection and sustainability have been a serious challenge due to the excess amount of waste plastic, and the inefficient methods of its disposal. This study aims at exploring the feasibility of using plastic material in asphalt concrete followed by the design and evaluation of modified asphalt mix. Four different types of asphalt mixtures were made by mixing mineral aggregates with plastic aggregates of different shapes and sizes. The conventional dense-graded asphalt concrete incorporating mineral aggregates was selected as control material, whereas the other three types of asphalt mixtures were produced by substituting 3D-printed plastic aggregates for mineral aggregates. Marshall characteristics were utilized to evaluate the volumetric and mechanical properties of the asphalt mixtures. Test results show that the asphalt mixture containing solid plastic aggregate appears to have a 14.3% reduction in bulk density, thereby potentially reducing the haul costs. Due to the angular shape of the aggregate, the stability for the asphalt mixture containing the 3D-printed aggregate is 1.95 times higher than that for the asphalt mixture incorporating all mineral aggregates. The addition of the plastic printed aggregate enhances the strain capacity to achieve failure of the asphalt mixture. However, caution should be taken when incorporating the hollow or fine printed aggregates into the asphalt mixture due to their variation of volumetric properties.

Integrated Energy System Optimal Operation in Coal District With Hydrogen Heavy Trucks

The coal industry contributes significantly to the social economy, but the emission of greenhouse gases puts huge pressure on the environment in the process of mining, transportation, and power generation. In the integrated energy system (IES), the current research about the power-to-gas (P2G) technology mainly focuses on the injection of hydrogen generated from renewable energy electrolyzed water into natural gas pipelines, which may cause hydrogen embrittlement of the pipeline and cannot be repaired. In this paper, sufficient hydrogen energy can be produced through P2G technology and coal-to-hydrogen (C2H) of coal gasification, considering the typical scenario of coal district is rich in coal and renewable energy. In order to transport the mined coal to the destination, hydrogen heavy trucks have a broad space for development, which can absorb hydrogen energy in time and avoid potentially dangerous hydrogen injection into pipelines and relatively expensive hydrogen storage. An optimized scheduling model of electric-gas IES is proposed based on second-order cone programming (SOCP). In the model proposed above, the closed industrial loop (including coal mining, hydrogen production, truck transportation of coal, and integrated energy systems) has been innovatively studied, to consume renewable energy and coordinate multi-energy. Finally, an electric-gas IES study case constructed by IEEE 30-node power system and Belgium 24-node natural gas network was used to analyze. The results show that by introducing the proposed hydrogen production technology, typical daily operating costs are effectively reduced by 7.7%. Under China’s carbon emissions trading system, the operating costs of hydrogen heavy trucks have been reduced by 0.95 and 4.68% respectively, compared with electric vehicles and diesel trucks. Under Europe’s stricter carbon emissions trading system, the percentages of cost reduction are 2.56 and 9.12%, respectively. The above technical results verify the feasibility, economy, low carbon, and effectiveness of the proposed mechanism.

Case-based reasoning system for prediction of fuel consumption by haulage trucks in open-pit mines

The shovel-truck system is commonly used in open-pit mining operations. Truck haulage cost constitutes about 26% of open-pit mining costs as the trucks are mostly powered by diesel whose cost is escalating annually. Therefore, reducing fuel consumption could lead to a significant decrease in overall mining costs. Various methods have been proposed to improve fuel efficiency in open-pit mines. Case-based reasoning (CBR) can be used to estimate fuel consumption by haulage trucks. In this work, CBR methods namely case-based reasoning using forward sequential selection (CBR-FSS), traditional CBR, and Naïve techniques were used to predict fuel consumption by trucks operating at Orapa Mine. The results show that the CBR method can be used to predict fuel consumption by trucks in open-pit mines; the predicted values of fuel consumption using the CBR-FSS technique gave much lower absolute residual values, higher standardised accuracy values, and effect sizes than those of other prediction techniques on all the datasets used. The system will enable mine planners to know the fuel consumed per trip and allow them to take mitigation measures on trucks with high fuel consumption.

Pricing Anomalies and Arbitrage in Container Transport in India

Intermodal transportation requires multiple entities to manage diverse resources under complex regulations and contracts. In this paper, we carry out a multidisciplinary cross-functional analysis of container rail haulage pricing and operations in India. We discover that the total haulage cost of a container train unduly depends on the position of the containers within the train, which is referred to here as position arbitrage. The main objective of this paper is to introduce and analyze this new concept of arbitrage for the first time in the literature. We derive the limits to the arbitrage, present management insights and empirical results, and explain that the arbitrage is undesirable because of its adverse effects on the efficiency of the container supply chain. With a real case, we empirically show that container train operators can save an average of 450 million INR annually by exploiting the arbitrage. On completion of dedicated freight corridors, the annual total value of the arbitrage can increase by one billion Indian rupees. This research is also beneficial for the railways to understand the implications of haulage pricing on operational efficiency and also for the port operators and shippers to understand the implications of the arbitrage for their operations.

Methods and techniques for energy efficiency assessment of geotechnological facilities at opencast mines based on the in-depth analysis

The article addresses energy efficiency of geotechnological facilities at opencast mines. The energy intensity of basic processes in solid mineral mining by the opencast method using the cyclical technologies takes up to 60–70% of the total mining and haulage cost. Given the mining technology is selected, and the stripping and excavations directions and procedures are determined, the potential for reduction in the geotechnology energy intensity lies in a proper choice of models of mining/haulage equipment, its duty and operation conditions. First of all, it is required to develop an energy efficiency methodology. This article reveals the possibility and potential of actual energy efficiency improvement in mines using the most widespread opencast method. The proposed approach assumes the in-depth analysis as an essential factor of the energy efficiency improvement of geotechnology facilities at opencast mines. The in-depth analysis should ensure real-time monitoring and assessment of energy consumption governed by the duty and operation conditions of the main mining and haulage equipment. The implementation of the proposed approach requires appropriate methods and techniques to take into account all factors that affect the mining and haulage equipment performance. This makes it possible to evaluate energy efficiency with due regard to the energy consumption and the nature of this energy integration by shares in the energy flows within the technology process. The studies emphasize that energy saving is a conventional key objective in mining. To this effect, it is required to ensure mechanical availability of mining and haulage machines, to monitor fuel consumption, to plan and control energy intensity based on the expected extraction volume per planned period. In the meanwhile, the research implemented reveals that opencast mines can essentially improve their energy efficiency in case of an appropriate backup with the relevant methods and techniques.

Multi-Product Shipment and Production Scheduling Mathematical Model under Different Distribution Policies

Nowadays, integration of production and distribution has been important in the supply chain. Besides, due to their limited lifespan, integration in the supply chain of perishable items has led to more studies. This study aims to present integrated production and shipment models under full truckload capacity (TL) and less than truckload (LTL) policies combining perishable and non-perishable products in a supply chain, simultaneously. The optimization objective is to minimize the total relevant cost of manufacturer such as the production setup, inventory holding, and transportation costs per time unit. After presenting the models, different numerical example has been used to evaluate based on the change of truck capacity, lifespan as well as costs, and increasing the number of perishable products via Gams software. The results obtained illustrate that the priority of policies TL and LTL depends on the capacity of the truck and shipping costs.

HAULAGE ANALYSIS IN THE AIM OF THE COMBINED SYSTEM APPLICATION ON THE LEAD AND ZINC MINE "SASE" SREBRENICA

<p>One of the most important influencing factors on the economy of mines with surface and underground exploitation is the correct choice of haulage technology of ore and waste.<br><br>The paper analyzes the haulage of ore and waste in the Lead and Zinc Mine “Sase” Srebrenica and determines the optimal haulage length on the four excavation blocks for the application of the new haulage system by using the mine trucks from the aspect of set criteria, increasing capacity and reducing haulage costs through the techno – economic analysis and optimization.The optimal haulage length is determined through the calculations of the loader capacity and the possible choice of the truck<br>depending on the stated criteria.</p>

Linking Federal Forest Restoration with Wood Utilization: Modeling Biomass Prices and Analyzing Forest Restoration Costs in the Northern Sierra Nevada

Over half of California’s forestland is managed by the US Forest Service, and the agency has identified a need to scale up forest restoration treatments in the state to one million acres per year by 2025. However, the high costs of mechanical fuel reduction and lack of markets for biomass pose significant barriers to accomplishing this target. The objectives of this case study were: (1) to identify costs of forest restoration treatments on federally-managed land in the Northern Sierra under a variety of harvesting scenarios and haul distances to biomass facilities, and (2) to understand what market prices for biomass must be offered to support such efforts. We modeled silvicultural prescription and harvesting options, machine productivity and costs, and transportation costs to assess economic thresholds. Biomass harvest, chip, and haul costs ranged from $55/bone dry ton to $118/bone dry ton, depending on the harvesting system scenario and distance from the biomass disposal site. Results suggest that the cost of forest restoration far exceeds current market prices for biomass, and additional investment is needed to adequately pay for federal forest restoration in California. Additional takeaways include that biomass outlets closer to supply sources can reduce both haul costs and production costs, and local wood utilization campuses can play a key role in supporting forest restoration.

Lactose: Use, measurement, and expression of results

Lactose has different uses in the dairy, food, and pharmaceutical industries. Being aware of the different forms of lactose and their concentrations can be very helpful in managing dairy product quality, properties, and manufacturing efficiency. Correct measurement and reporting of lactose concentration in milk and other dairy products will be of increased importance in the future as more value-added uses of lactose are developed and as milk lactose data are used in farm management decision making. Lactose should be reported as anhydrous lactose because lactose data will be used to make increasingly important decisions in dairy processing, dairy product labeling, and milk production in the future. Lactose also plays an important role in milk synthesis within a cow. Milk production factors and dairy cattle breed selection influence the amount of high value fat and protein produced per unit of lactose. If the off-farm value of lactose remains low, more attention may be focused on using ultrafiltration to process milk and leave 50 to 60% of the lactose and water from milk at the farm to recover the energy value of the lactose as feed and reduce the hauling cost of the high value components of milk to a dairy product manufacturing factory. Many methods exist to determine lactose concentration, but the most important methods are enzymatic assays, HPLC, and mid-infrared analysis. New, value-added uses for lactose need to be developed. Consistent and accurate methods of lactose measurement and consistent expression of lactose results will support this development process. Starting in January 2017, the USDA Federal Milk Market Laboratories began reporting lactose content of milk as anhydrous lactose and discontinued the reporting of lactose by difference.

Feature-based selection of carsharing relocation modes

One-way and free-floating carsharing systems must be rebalanced to achieve a high service level, and thus generate benefits for users and society. In practice, vehicles can be relocated with multiple different modes (e.g., by truck or by driving them), but a single mode is sufficient in many instances. Obviously, a single mode is preferred from a computational standpoint: The routing problems are less complex since less synchronization is necessary, and thus solve much faster. It remains an open question which features drive the decision on the best mode, and if operators can decide a priori whether hybridization of several modes is beneficial/necessary, and which modes one should hybridize among. We build a classifier based on linear regression which predicts the costs for all individual modes. The advantage of this approach is that cost estimates (i) can be used as a feature in other approaches, and (ii) allow operators to estimate the necessary budget upfront. However, cost estimates cannot be used directly to determine key drivers for modal choice. We, thus, use logistic regression and decision trees for determining the best mode. These approaches are better at determining relevant features that explain which mode is preferred in an instance. We find that the most important features to decide between modes are vehicle and truck costs per kilometer as well as their velocities, and the average number of vehicles that shall be relocated per day (that is, the imbalance of the system). In most instances, the decision is between driving vehicles to rebalance them and rebalance staff by biking, or loading vehicles onto a truck. Hybridization proves useful in ≈20% of all instances, and a simple rule-based classifier is able to predict correctly that hybridization is necessary in most instances.

Adaptive memory red deer algorithm for cross-dock truck scheduling with products time window

PurposeThe cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks.Design/methodology/approachThis research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time.FindingsTheory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window.Research limitations/implicationsThe consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies.Originality/valueFor the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.

ANALISA PRODUKTIVITAS DAN BIAYA OPERASIONAL ALAT BERAT PADA PROYEK PEMBANGUNAN STREET-RACE CIRCUIT MANDALIKA

The Mandalika circuit project is a large-scale construction project built in the Mandalika Special Economic Zone (SEZ), Central Lombok, West Nusa Tenggara (NTB). The 4.31 kilometer racetrack will have 19 bends, so it requires heavy equipment to improve the quality production and increase project efficiency. The analysis conducted to obtain the hourly productivity, operating cost, income and profit of excavators, dump trucks, motor grader, vibrator roller, and water tanker used in the worksite of Mandalika circuit. The hourly productivity for structural cut with a depth of 2 to 4 meter of excavator is 17.778 m3/h and dump truck 11.755 m3/h. The excavator production for stockpiling from excavated sources is 30.521 m3/h, dump truck 13.171 m 3/h, motor graders 1839.780 m 3 /h, vibrator roller 90.414 m 3 /h and water tankers truck 71,142 m 3/h. Motor grader production for road body preparation work is 362,222 m3/h, vibrator roller 126,851 m3/h and water tanker truck 62,250 m3/h. The hourly operating cost for the excavator is Rp. 718,048,581, motor grader Rp. 670,416,081, vibrator roller Rp. 609,423,907, and water tanker truck Rp. 380,806,081. The income and profit from the use of heavy equipment are Rp. 39,488,806,755 and Rp. 3,589,981,523.05.

A Truck Allocation Optimization Model in Open Pit Mining to Minimize Investment and Transportation Costs

In this research we developed an optimization model to determine truck allocation in open pit mining. The objective function is to minimize a total cost consists of investment and transportation costs. Investment cost is the purchase price of truck in early mining project according to the number of truck needed in each route. The transportation cost consists of fix cost for operators’ wages and variable cost in the form of fuel cost of trucks and shovels. The selection of truck types with different specifications is an important factor in the continuity of materials transportation by considering the costs incurred The model is solved using Oracle Crystal Ball Software for 5000 iterations. The result of optimization shows that Truck 75570 is selected to transport for route 1 and Route 4, Truck 75174 is selected to transport for Route 2, Truck 772 is selected to transport for Route 3, Truck 777F is selected to transport for Route 5, and Truck 7547 is selected to transport for Route 6. The total cost resulted from the optimization is IDR 295,783,073,068.69.

Design improvement of pallet in automotive industry

In automotive manufacturing industry, supplies of different parts are required to construct products. Products are manufactured as per a company’s production targets, and in the effort to do so, some that are sent from suppliers must arrive on time and accordingly. The process of delivery incorporates the use of shuttles where parts are packed into pallets and then sent to warehouses. High demand yields high production that implies high trucking costs. The more pallets used in the transport of goods, the more shuttles are used and the higher the trucking costs. Based on observations of problems, the low effectiveness of the transporting process of goods, among others, is factored by the less than maximum pallet design giving rise to unused spaces within shuttles upon shipment.

Determination of semi-mobile in-pit crushing and conveying (SMIPCC) system performance

In-pit crushing and conveying (IPCC) systems are currently receiving more attention as a result of the existing characteristics of open-pit mining operations and what is likely to happen in the future. The use of trucks and shovels for loading and hauling has been used as a dominant system in open-pit and open-cast mines due to their large-scale operations compared with other mining methods. Presently, it has become more required than ever to minimise the cost of truck haulage, which reports for approximately half of the operating costs of the mining operation. Therefore, trucking costs can be considerably minimised by installing the crushers inside the pits. With the increased popularity of IPCC systems, it is necessary to investigate the overall performance and productivity of the systems. This paper employs mine productivity index (MPi) to determine the productivity of semi-mobile IPCC. From this study, it is evident that a reduction of number of loading equipment necessitated an increase in shovel’s bucket size and reduction of the trucks by 33%. Additionally, this study found that the scenario with more than one loading equipment has a higher MPi of 71% compared with the scenario with one loading equipment having an MPi of 67%. Further, SMIPCC scenarios record better MPi compared with the current truck-shovel transportation system which has an MPi of 67.14%.

Open-pit mine truck fuel consumption pattern and application based on multi-dimensional features and XGBoost

The fuel consumption cost of open-pit mine trucks accounts for up to 22% of the total cost. However, research on the fuel consumption of mine trucks has been hindered by low monitoring accuracy and unclear fuel consumption patterns. Based on the fuel consumption per cycle of mine trucks, this study analysed the fuel consumption of 5179 transportation cycles with three types of mine trucks. First, a regression analysis was applied to reveal the non-linear pattern of the fuel consumption caused by multi-dimensional features, such as haulage distance, lifting height, and operation time per cycle. Then, based on multi-dimensional features and the XGBoost algorithm, a prediction model for the fuel consumption of mine trucks was proposed, and the R-squared and mean absolute percent error index values were determined to be 0.93 and 8.78%, respectively. The experimental results showed that the lifting height, load, and haulage distance were the key factors influencing the fuel consumption of mine trucks. The fuel consumption of mine trucks during queuing cannot be ignored. These results can be applied to formulate reasonable fuel consumption assessment indicators, truck dispatch strategies, and cost budget plans.