Earthmoving Operations Research Articles

Design Optimization and Analysis of Trenching Excavator Bucket

This research centers on the design optimization and analysis of a trenching excavator bucket using ANSYS engineering simulation software. The study explores modifications, such as decreasing bucket height by 35mm and increasing side plate width to 12mm compared to the stock configuration1. The analysis primarily focuses on evaluating Equivalent Elastic Strain and Total Deformation using ANSYS to ensure improved digging performance and structural integrity. Excavator buckets are vital components in earth-moving operations, and their efficiency directly affects productivity and operational costs. By leveraging ANSY advanced capabilities, this study aims to propose an optimized bucket design that enhances trenching efficiency and durability. The findings provide valuable insights for manufacturers and engineers seeking to elevate excavator bucket technology and improve construction and mining operations through enhanced performance and cost-effectiveness.

Applying Systems Thinking to Research into Risk Factors Influencing Earthmoving Equipment Operation Safety in Construction Sites

Earthmoving operations in the construction process are complex environments that involve interactions between equipment, the workforce, and materials within an overarching construction plan. Over the past two decades, researchers in construction have focused on improving the safety of construction earthmoving equipment due to their omnipresence in the construction environment. Although previous studies have explored safety risks and the causes of accidents involving construction earthmoving equipment, their approaches were common and lacked a comprehensive perspective. Hence, this systematic literature review applies Rasmussen’s (1997) risk management framework using a systems thinking approach to identify and classify the risk factors influencing earthmoving equipment operation safety in construction sites. Utilizing a multistep methodology, this research first identifies 38 risk factors pertinent to earthmoving equipment operations and then classifies them based on systems thinking. Social network analysis (SNA) is employed to analyze the data. The results show that most research on earthmoving equipment safety focuses on monitoring construction sites, but very little on government and regulatory roles. When considering the interdependencies of risk factors, safety training is the most important factor, followed by the largely overlooked earthmoving machinery characteristics and manufacturer’s performance. The results of this review inform both the research community and industry practitioners regarding the less-understood aspects of earthmoving equipment operation safety and future research directions.

Automatic excavator action recognition and localisation for untrimmed video using hybrid LSTM-Transformer networks

ABSTRACT In mining and construction, excavators are integral to earth-moving operations. Accurate knowledge of excavator activities may be used in productivity analysis to streamline delivery. This paper presents a computer vision-based method for excavator action detection which can automatically inference the occurrence and time duration of excavator actions from untrimmed video captured from the excavator cab. The model uses a three-stage architecture consisting of a VGG16 feature extractor, a four-stage Transformer Encoder-Long Short-Term Memory (LSTM) module, and a post-processing component. The model’s predictive performance has been validated on the largest dataset among similar studies, comprising 567,000 frames filmed on-site at day and night. When tested on night and daytime videos, the model achieves accuracies of 90% and 70%, respectively, highlighting strong potential for practical implementation of the Transformer-LSTM network in excavator action detection. This study presents the first application of the combined Transformer-LSTM network for action detection in computer vision.

Fleet management for earthmoving operation in the phase of detail estimation using mixed integer nonlinear programming

ABSTRACT Earthmoving operations generally account for about a quarter of the construction budget in high-way constructions. Feasible planning is thus required for delivering the successful performance of such projects. Selecting the best fleet for the operation is one of the crucial factors affecting both duration and cost. However, owing to changing operating circumstances and the uncertainty of construction projects, this task is yet conducted based on the experience of site managers. The existing literature has witnessed that discrete event simulation (DES) and references such as the construction standard production rate (CSPR) are used to assist the decision-making. Those methods have shown limitations for practical application due to the need for expert knowledge of simulation modeling and time-consuming efforts for data collection. Accordingly, this study proposes a more efficient method of using mixed integer nonlinear programming (MINLP) in multi-objective problems, enabling optimal fleet information derivation based on given circumstances. The proposed method uses the CSPR-based mathematical equations for the consideration of productivity generated by the types and sizes of equipment. A comparative study of the proposed method and a DES approach was given for further discussions.

К РАСШИРЕНИЮ ЭКСПЛУАТАЦИОННЫХ ХАРАКТЕРИСТИК ЗЕМЛЕРОЙНО-ТРАНСПОРТНЫХ МАШИН

This article presents materials related to the development of a promising dump design for various types of bulldozers used on high-strength soils. The most important parameter of bulldozers is productivity, which depends on the amount of soil moved by the blade in one working cycle, characterized by the volume of the drawing prism. A characteristic sign of overloading of dumps is the slipping of tracks or tractor wheels. This phenomenon significantly affects the reliability of components and parts of bulldozers, reducing their productivity. To eliminate this, rotary dumps can be used, allowing them to be rotated at a certain angle in both directions relative to the longitudinal axis of the machine, but their restructuring is quite time-consuming and not always effective. The analysis of numerous sources made it possible to develop a prom-ising technical solution at the level of inventions, which makes it possible to efficiently perform earthmov-ing operations related to the treatment of high-strength soils. As a result of analytical studies, taking into account the cutting resistance force of 7 kN, the geometric parameters of the gear engagement (gear wheel-rail) were calculated, the engagement module was adopted m = 10 mm. Recommendations are given on the choice of gear wheel and rail material – 45 normalized steel. For angular rotations of the side sections of the blade, it is recommended to use a hydraulic cylinder with a double-sided rod with an internal cylinder diameter of dv = 40 mm and a rod diameter of ds = 20 mm, at a working fluid pressure of p=10 MPa. It is recommended that the blade rods be made of 80x60 Steel 85 pipe, which ensures their stability during the operation of the bulldozer blade.

Automatic Mass Estimation of Construction Vehicles by Modeling Operational and Engine Data

Earthmoving operations employ heavy-duty vehicles, including trucks and scrapers, to transport soil and rock on and off construction sites. Such construction activities are commonly scheduled and paid for based on the amount of earth moved. A number of metric and volumetric tools and techniques, including weighbridges, load–volume scanners (LVS), and strain gauges, have been developed to measure the payload of vehicles. These methods are costly, time-consuming, and labor-intensive, and may affect the production rate and cost of construction projects. This study develops an automatic mass estimation technique for on-road construction vehicles considering both operational and engine data. Acceleration rate, speed, and road slope are investigated as the operational variables, while engine load is considered as an engine attribute to estimate vehicle mass. A global positioning system-aided inertial navigation system (GPS-INS) and an engine data logger are integrated to collect the field data. Experiments are conducted on several construction vehicles to collect a wide range of data under various operational conditions. After assuring the quality of field data obtained in this study, artificial neural networks (ANNs) were developed to model the mass of construction equipment based on operational and engine parameters. The model was validated by comparing the estimated mass data with the actual values measured by a weighbridge in the experiment. The results show that the proposed model achieves greater than 90% accuracy in predicting the mass of on-road construction vehicles.

Integrated preventive maintenance and flow shop scheduling under uncertainty

This paper is concerned with stochastic scheduling of production and maintenance activities in a permutation flow shop setting. We present a two-stage stochastic mixed-integer program (SMIP) that adapts the conventional permutation flow shop scheduling problem for incorporating multiple preventive maintenance activities with various meter-based intervals. The model handles uncertainties in both processing times and the duration of maintenance activities. The concept of combining maintenance activities in scheduling problems is introduced and formulated, along with other practical considerations. The objective is to minimize the total expected cost associated with lateness penalties and maintenance resources. We use simulation–optimization (SO) for solving large-scale instances of the problem, and for validating the SMIP model. Through extensive computational experiments, we show that the SO method is superior in terms of efficiency and effectiveness and evaluate its sensitivity to the input data. Finally, a case study in earth-moving operations is presented, followed by managerial implications.

An Integrated Expert System for Linear Scheduling Heavy Earthmoving Operations

Heavy earthmoving operations are repetitive in nature and vulnerable to time-related restraints and uncertainties. Therefore, at the conceptual stage, scheduling these operations can take a linear form, known as linear schedule or line of balance (LOB). In such type of work, generating a preliminary line of balance for variable sequencing of activities is crucial. In this paper, an integrated expert system for determining preliminary linear schedules for heavy earthmoving operations at the conceptual stage is presented. The proposed system incorporates numerous factors that influence the analysis of earthmoving operations, which include geological and topographical parameters used to determine productivity rates at the conceptual stage. Also, the proposed system is capable of automatically generating a line of balance based on a stochastic scheduling technique via the metaheuristic simulated annealing intelligent approach to incorporate randomness and uncertainties in performing the associated activities. A parametric analysis is conducted in order to quantify the system’s degree of accuracy. An actual case project is then utilized to illustrate its numerical capabilities. Generating accurate linear schedules for heavy earthmoving operations at the conceptual design stage is anticipated to be of major significance to infrastructure project stakeholders, engineers, and construction managers by detecting schedule’s conflicts early in order to enhance overall operational logistics.

Key challenges in automation of earth-moving machines

A wheel loader is an earth-moving machine used in construction sites, gravel pits and mining to move blasted rock, soil and gravel. In the presence of a nearby dump truck, the wheel loader is said to be operating in a short loading cycle. This paper concerns the moving of material (soil, gravel and fragmented rock) by a wheel loader in a short loading cycle with more emphasis on the loading step. Due to the complexity of bucket-environment interactions, even three decades of research efforts towards automation of the bucket loading operation have not yet resulted in any fully autonomous system. This paper highlights the key challenges in automation and tele-remote operation of earth-moving machines and provides a survey of different areas of research within the scope of the earth-moving operation. The survey of publications presented in this paper is conducted with an aim to highlight the previous and ongoing research work in this field with an effort to strike a balance between recent and older publications. Another goal of the survey is to identify the research areas in which knowledge essential to automate the earth moving process is lagging behind. The paper concludes by identifying the knowledge gaps to give direction to future research in this field.

An expert system to optimize cost and schedule of heavy earthmoving operations for earth- and rock- filled dam projects

Success of major embankment dam construction projects is measured by the enormity of optimizing costs and schedules of selected heavy equipment based on their operational analyses. In this paper, the main objective is geared towards developing a knowledge-based decision support system for optimizing costs of heavy earthmoving operations and corresponding linear schedules at early design stages. Also, the proposed system is capable of generating an auto­mated linear schedule based on stochastic scheduling techniques. Thus, a meta-heuristic simulated approach utilizing a metropolis algorithm is implemented to assist in generating optimized line-of balances. The successful implementation of the proposed system will provide the user with optimum fleet of equipment for performing earthwork operations and linear scheduling for strategic planning purposes. Towards the end, an actual dam construction project is utilized to numerically validate the proposed system and quantify its degree of accuracy. Results presented in this study are an­ticipated to be of major significance to owners, designers, and construction managers specialized in embankment dams heavy earthmoving operations and would contribute to the database of fleet management systems by incorporating a novel system that integrates heavy equipment economical operational analyses with its corresponding line of balance.

Earthmoving Productivity in Urban Bridge Construction

Earthmoving operations in urban bridge reconstruction projects are analyzed to identify significant factors that impact relatively low productivity. The research project was conducted in the urban interchange reconstruction of Interstate Highway 235 (I-235) in Des Moines, Iowa. By using observational studies and a statistical analysis method, the factors were identified, including match factor, number of passes, and loading cycle time per bucket. Number of truck, match factor, travel time, and hauling distance were identified as the unique factors for the off-site earthmoving project, while the start time and travel time were significant factors for the on-site project. This research also identified significant factors for the truck bunching and showed that the match factor from the urban earthmoving project does not linearly correlate with the productivity of each truck. Reducing the hauling distance for urban earthmoving projects was the principal method for improving productivity.

Optimum scraper load time and fleet size for minimum emissions

Scrapers are commonly used in road construction, site formation, other earthmoving and surface mining operations. It is known that loading a scraper to capacity may not be best in terms of unit operational cost, because the load-growth curve for a scraper is nonlinear – the loading rate decreases with load time. However, there is no published research considering the effect of load time and fleet size on unit emissions, and what the corresponding optimal load time and fleet size might be. This paper shows that the optimum scraper load time for unit emissions may be the same or slightly less than that for unit cost depending on the scraper type and operation, while the optimum fleet size in terms of minimum unit emissions, is slightly higher than or the same as that in terms of minimum unit cost. Cost-load-time, emissions-load-time and hauling characteristics, particular for different equipment and operations, influence the conclusion. For practice purposes, it could be said that the optimal unit cost and unit emissions solutions essentially coincide. Case study site data, in conjunction with a scraper operational analysis, are used to demonstrate the optima. Both push-pull scrapers and push-loaded scrapers are considered.

Truck dispatching and minimum emissions earthmoving

Purpose – The dispatching of trucks in earthmoving and like operations is worthy of examination because of potential emission reductions and savings through the appropriate allocation of trucks to excavators and dump sites. The paper aims to discuss this issue. Design/methodology/approach – Truck dispatching is performed through linear programming (LP) and the effect of truck allocation on unit emissions and unit costs established. Number of trucks, unit cost and unit emissions are all considered as objective functions. A cut and fill operation on a road project provides a numerical case study. Findings – It is demonstrated analytically that the minimum unit emissions solution is the same as that for minimum unit cost. Numerical results from the case study, including sensitivity analyses on the underlying parameters, support this conclusion. Practical implications – The LP dispatching solution, based on minimizing truck numbers and unit costs, accordingly impacts the environment the least in terms of emissions. The paper's results will be of interest to those designing and managing earthmoving and like operations for production, cost and emissions. Originality/value – While LP has been used by others to examine optimum unit cost dispatching, this paper is original in examining the dispatching or truck allocation based on both unit cost and unit emissions, and showing the relationship between the optima for both.

Server-Customer Interaction Tracker: Computer Vision–Based System to Estimate Dirt-Loading Cycles

AbstractReal-time monitoring of heavy equipment can help practitioners improve machine-intensive and cyclic earthmoving operations. It can also provide reliable data for future planning. Surface ea...

Performance of Transportation Infrastructure

Performance of Transportation Infrastructure

Resuspension of Sediment as a Possible environmental Management Method for Coastal Lagoons and Aquaculture Ponds

Although efforts have been made to reduce nutrient loads from civil wastewater treatment and industry (including land-based fishfarms), many lagoons still have serious environmental problems. The solutions usually used for remediation or to counteract the effects of eutrophication are often expensive and have a heavy impact on the lagoon and surrounding environments. They include earth-moving operations, excavation of channels and openings to the sea, deviation of rivers and drainage channels in farmland [5-15]. Not only do they denature lagoon characteristics and alter the coastal belt, but their cost/benefit ratio may be high and their effects short-lasting. For example, underwater channels excavated to improve internal water circulation in lagoons may silt up in a few years and require frequent costly maintenance. In the case of algal blooms, harvesting and disposal are often tried [16-22], but these operations are costly and frequently conducted with inappropriate methods and timing. Contrary to theory, the disposal of harvested algae is difficult and industrial uses of this material are rarely found. As an alternative solution for the management of lagoon eutrophication, recent field experiments have been conducted to The surface layer of sediment accumulates bioavailable organic matter and with the intervention of microbes, provides nutrients for the development of opportunistic vegetation. Superficial sediment subject to frequent disturbance may undergo an increase in the oxidative mineralization rate of organic matter [25]. Oxidation accelerates nitrification and leads to predominance of nitrates over reduced forms, increasing denitrification (which occurs in anoxic microhabitats in an oxidative milieu), with the result that part of the nitrogen is lost as gases [26]. Resuspension may lead to oxidation of sediment iron to ferric oxides, which adsorb orthophosphates, removing them from interstitial water and the water column [27]. By virtue of the geo-chemico-physical effects it produces, resuspension leads to selection of microbial, plant and animal populations, in the opposite direction to the selection produced by eutrophication and dystrophy. Opportunistic macroalgae suffer phosphorus limitation and seagrasses that take up nutrients directly through their roots can recolonize the substrate [28]. Frequent disturbance of sediment does not have significant negative effects on the water column, such as increase in pH and nutrients or decrease in

Semi-Lagrangian reproducing kernel formulation and application to modeling earth moving operations

Lagrangian formulation has traditionally been introduced for solids under large deformation. Earth-moving operations on the other hand, involve excessive material deformation and damage that cannot be modeled by the Lagrangian formulation. In this paper, a Semi-Lagrangian reproducing kernel (RK) formulation is introduced for modeling earth-moving operations. von Neumann stability analyses of Lagrangian and Semi-Lagrangian Reproducing Kernel (RK) formulations are first performed. The analysis results show that Semi-Lagrangian weak form integrated by a direct nodal integration (DNI), resembling Smoothed Particle Hydrodynamics (SPH), leads to a tensile instability that is inconsistent with the material stability. On the contrary, Semi-Lagrangian RK weak form integrated using the stabilized conforming nodal integration (SCNI) exhibits consistent numerical stability and material stability. The stable time steps for Lagrangian and Semi-Lagrangian RK formulations using central difference are also estimated and an enhanced stability is observed when the weak forms are integrated by SCNI compared to that using DNI or one-point Gauss quadrature. Earth moving simulation is performed to demonstrate the applicability of the proposed Semi-Lagrangian RK formulations to excessive material deformation and fragment problems.

Improving forest operations planning through high-resolution flow-channel and wet-areas mapping

This article describes a mapping process designed to provide forest management with high-resolution flow-channel and wet-area maps for forest operations planning. The process requires digital elevation models (DEMs) and hydrographic data, and also portrays the likely depth to surface water across forested terrains away from any nearest surface-water features such as streams, rivers, lakes, and wetlands. Map applications involve layout of roads and trails, automated selection of best road–stream crossings, minimizing earth-moving operations during road construction, detailing in-block plans for temporary roads and channel crossings, and delineating habitats, machine-free zones and blocks for harvesting, tree planting, site preparation, and stand thinning. Map verifications centre on visual comparisons of map features with land-surface images, and these can be coupled with GPS tracking of wetland and wet-area borders, stream channels, and road-stream crossings. Further developments involve increasing the wet-areas map resolution and accuracy with LiDAR (Light Detection and Ranging) bare-ground DEMs and other fine-gridded DEMs, and expanding the applications to mapping of soils, soil properties and tree and crop productivity, to watershed and road-network management, to off-road trafficability, and to impact evaluations dealing with hydrological sensitivities and risks. Key words: forest operations planning, geographic information systems, digital elevation models, flow-channels, wet areas and depth-to-water maps, hydrological risks

Production prediction of conventional and global positioning system–based earthmoving systems using simulation and multiple regression analysis

Accurate estimation of construction production, which is composed of productivity and unit costs, allows construction planners and managers to have excellent control over current processes and to correctly predict the production of similar projects in the future. Due to the need for accurate production estimation, selection of the appropriate construction technology is a critical factor in the success of a project. This paper presents a methodology for developing a model capable of predicting productivity and unit costs using several procedures, such as actual data collection, input data generation using construction simulation, and multiple regression analysis. An earthmoving operation was analyzed to estimate the proposed methodology’s prediction of construction production. A global positioning system (GPS)–based earthmoving system was selected as the new construction technology to be compared with the conventional system, to evaluate the decision-making process at a jobsite. The proposed methodology is expected to provide users with a basis for selecting appropriate technology. The case study presented in this paper demonstrates how to utilize the proposed methodology and analyze its predicted results.

Comparison of two simulation methodologies in modeling construction systems: Manufacturing-oriented PROMODEL vs. construction-oriented SDESA

To facilitate the practice improvement by use of simulation tools in construction, the present research generalizes the main characteristics that differentiate a construction system from a manufacturing system in light of simulation modeling. The PROMODEL simulation platform which is influential and popular in manufacturing is chosen for (1) validating the newly developed construction simulation platform called SDESA (the Simplified Discrete-Event Simulation Approach); and (2) identifying the differences between manufacturing and construction simulations by applying PROMODEL alongside SDESA to typical construction systems. In modeling a simple earth-moving operation and a real site operation integrating concreting and waste handling practices, the validity of SDESA is cross checked by the established PROMODEL and SDESA is found to be more flexible and straightforward in addressing construction systems in terms of (1) representing vehicle-loop work flows, (2) modeling resource transit times between various locations on site, (3) deriving resource utilization rates, and (4) learning efforts and application time requirements. The comparisons made can be taken as guidance for helping construction practitioners (1) to distinguish the modeling needs between construction and manufacturing simulations and (2) to select the suitable simulation tools for practice improvement.