Evaluation of Truck Dispatch System and its Application using GPS in Opencast Mines- a Case Study of Indian Mines

Truck haulage now a days is the most common means which is used for moving ore/waste in open-cast mining operations. The truck haulage is usually the costliest unit operation in a truck shovel open cast mining. The advancement in computer coding technology has advanced to a point where there are many truck dispatching systems which will give the potential of advancing truck-shovel productivity and future savings. By trying a dispatching system in any mine can give operational increase in production by minimizing waiting times and can give other beneficial advantages and can also be obtained through good monitoring, optimal routing. The capacity of the employed truck-shovel fleet counts on the dispatching methodology in use, the intricacy of the truck shovel system and a number of other variables. It is a very common situation in mining that considerable number of analysis of the available techniques is undertaken before dispatching is done. In many number of cases, computer simulation is the better applicable and effective method of relating the alternative dispatching strategies. Keeping this in mind computer programs are developed using C++ language for the monitoring of the equipment performance in truck dispatch system in opencast mines. To study about the truck dispatch system (TDS), we have made a choice to make it on the shovel dumper combination using GPS. In TDS system the computer monitors the location and status whether the dumper is full or empty and its heading, velocity of each vehicle in the fleet. The system analyses production numbers, such as haul routes, historic data about drive time to a specific shovel location and the cycle time and time taken to make a complete trip, trip from the shovel to the dump site and back

Development of computer based equipment performance monitoring systems in open cast mines

Truck haulage is the most common means used for moving ore/waste in open-pit mining operations, but it is usually the most expensive unit operation in a truck shovel mining system. The state-of-the-art in computing technology has advanced to a point where there are several truck dispatching systems which offer the potential of improving truck-shovel productivity and subsequent savings. Introducing a dispatching system in a mine can achieve operational gains by reducing waiting times and obtain other benefits through better monitoring, optimal routing and grade control. Efficiency of the employed truck-shovel fleet depends on the dispatching strategy in use, the complexity of the truckshovel system and a variety of other variables. It is a common situation in mining that considerable analysis of the available strategies is undertaken before dispatching is adopted. In most cases, computer simulation is the most applicable and effective method of comparing the alternative dispatching strategies. To develop a computer based equipment performance monitoring systems in open cast mines. We have made a choice to make it on the shovel dumper combination using GPS. The computer monitors the location and status (full or empty, heading, and velocity) of each vehicle in the fleet. The system analyzes production statistics, such as haul routes, historic data about drive time to a specific shovel location, and cycle time how long it takes to make a round trip from the shovel to the dump site and back. The system then correlates these data to most efficiently route all the vehicles. The computer based equipment performance monitoring of equipments of open cast coal mine on an offline monitoring basis. This system starts from the counting of the number of trips dumpers. It has very good features such as it is easy to learn, very good user interface capability. The success of the system is totally dependent on the availability and incorporation of the data into the system .If the data will no be available then the system cannot provide good result. The data which has been incorporated into the system also should be correct, other wise it will provide wrong information to the management. There is a huge scope for further development of this kind of system such as incorporation of other equipment such as dragline, dozer, etc. It can also be used for equipment maintenance system and also for inventory control. The program written in C compiler has been written on the basis of GPS data of the time, loading, unloading points in the mine. It gives us the availability, utilization, idle time and breakdown time for the shovel dumper system. The data taken is on the basis of the data selected for a whole shift

Development of a Computer Oriented Algorithmic Approach for Opencast Mine Dispatch System

Truck haulage is the most common means used for moving ore/waste in open-pit mining operations, but it is usually the most expensive unit operation in a truck shovel mining system. The state-of-the-art in computing technology has advanced to a point where there are several truck dispatching systems which offer the potential of improving truck-shovel productivity and subsequent savings. Introducing a dispatching system in a mine can achieve operational gains by reducing waiting times and obtain other benefits through better monitoring, optimal routing and grade control. Efficiency of the employed truck-shovel fleet depends on the dispatching strategy in use, the complexity of the truck-shovel system and a variety of other variables. It is a common situation in mining that considerable analysis of the available strategies is undertaken before dispatching is adopted. In most cases, computer simulation is the most applicable and effective method of comparing the alternative dispatching strategies. To develop a computer based algorithm for despatch systems in open cast mines, the program asks the user to enter the number of trucks initially assigned to each shovel site. Experiments are made to investigate the effects of several factors including the dispatching rules, the number of trucks operating, the number of shovels operates, the variability in truck loading, hauling and return times, the distance between shovels and dump site, and availability of shovel and truck resources. The breakdown of shovel and trucks are modeled using exponential distribution. Three performance measures are selected as truck production, overall shovel utilization and overall truck utilizations. But, the main factors affecting the performances are the number of trucks, the number of shovels, the distance between the shovels and dump site, finally the availability of shovel and truck resources. Also, there are significant interaction effects between these main factors

A simulation model for truck-shovel operation

A truck-shovel mining system is a flexible mining method commonly used in surface mines. Both simulation and queuing models are commonly used to model the truckshovel mining operation. One fundamental problem associated with these types of models is that most of the models handle the truck haulage system as macroscopic simulation models, which ignore the fact that a truck as an individual vehicle unit dynamically interacts not merely with other trucks in the system but also with other elements of the traffic network. Some important operational factors, such as the bunching effect and the influence of the traffic intersections, are either over simplified or ignored in such a macroscopic model. This thesis presents a developed discrete-event truck-shovel simulation model, referred to as TSJSim (Truck and Shovel JaamSim Simulator), based on a microscopic traffic and truck-allocation approach. The TSJSim simulation model may be used to evaluate the Key Performance Indicators (KPIs) of the truck-shovel mining system in an open pit mine. TSJSim considers a truck as an individual traffic vehicle unit that dynamically interacts with other trucks in the system as well as other elements of the traffic network. TSJSim accounts for the bunching of trucks on the haul routes, practical rules at intersections, multiple decision points along the haul routes as well as the influence of the truck allocation on the estimated queuing time. TSJSim also offers four truck-allocation modules: Fixed Truck Assignment (FTA), Minimising Shovel Production Requirement (MSPR), Minimising Truck Waiting Time (MTWT) and Minimising Truck Semi-cycle Time (MTSCT) including Genetic Algorithm (GA) and Frozen Dispatching Algorithm (FDA)

High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization

Disertační práce je zaměřena na optimalizaci průběhu pracovních operací v logistických skladech a distribučních centrech. Hlavním cílem je optimalizovat procesy plánování, rozvrhování a odbavování. Jelikož jde o problém patřící do třídy složitosti NP-težký, je výpočetně velmi náročné nalézt optimální řešení. Motivací pro řešení této práce je vyplnění pomyslné mezery mezi metodami zkoumanými na vědecké a akademické půdě a metodami používanými v produkčních komerčních prostředích. Jádro optimalizačního algoritmu je založeno na základě genetického programování řízeného bezkontextovou gramatikou. Hlavním přínosem této práce je a) navrhnout nový optimalizační algoritmus, který respektuje následující optimalizační podmínky: celkový čas zpracování, využití zdrojů, a zahlcení skladových uliček, které může nastat během zpracování úkolů, b) analyzovat historická data z provozu skladu a vyvinout sadu testovacích příkladů, které mohou sloužit jako referenční výsledky pro další výzkum, a dále c) pokusit se předčit stanovené referenční výsledky dosažené kvalifikovaným a trénovaným operačním manažerem jednoho z největších skladů ve střední Evropě.This work is focused on the work-flow optimization in logistic warehouses and distribution centers. The main aim is to optimize process planning, scheduling, and dispatching. The problem is quite accented in recent years. The problem is of NP hard class of problems and where is very computationally demanding to find an optimal solution. The main motivation for solving this problem is to fill the gap between the new optimization methods developed by researchers in academic world and the methods used in business world. The core of the optimization algorithm is built on the genetic programming driven by the context-free grammar. The main contribution of the thesis is a) to propose a new optimization algorithm which respects the makespan, the utilization, and the congestions of aisles which may occur, b) to analyze historical operational data from warehouse and to develop the set of benchmarks which could serve as the reference baseline results for further research, and c) to try outperform the baseline results set by the skilled and trained operational manager of the one of the biggest warehouses in the middle Europe.