Conveyor Network Research Articles

Kajian Beban Harian pada Jaringan Distribusi Penyulang Jelutung

A distribution network is a conveyor network that connects the load center substation with the customer. The distribution network functions to distribute electrical energy to customers according to the power and voltage needed. The distribution network line from the Aurduri GI Transformer Bay goes to the incoming to be lowered voltage from 150kv to 20kv. After the voltage is lowered, it is directly channeled to the Jelutung Feeder to find out the daily load on the distribution network. The population in this study is "Study of Daily Burden on the Distribution Network of Jelutung Feeders". The highest daily load is the electrical load that occurs at the highest time in 24 hours. This can be affected by household, industrial, commercial activities and weather conditions. Daily peak loads occur at certain times such as the afternoon. The lowest daily load usually occurs in the morning around 06.00 to 07.30. Average lowest current (I) R,S,T 92,275A and lowest power (P) 3.29Mw. While the average highest current is 212.7A and the highest power is 7.54Mw. The highest current in September was on the 15th with a power of 8.0 mw at 18.30.

Applications of simulation modeling in mining project risk management: criteria, algorithm, evaluation

Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.

Continuous control algorithms for conveyer belt routing based on multi-agent deep reinforcement learning

Introduction: We consider the problem of routing of piece cargo by a conveyor system. When moving cargo pieces, it is necessary not only to minimize the time of transportation, but also to minimize the energy spent on it. Purpose: Development of a routing algorithm that is adaptive to changes in the topology of the routing graph and is able to optimize the delivery time and the consumed energy. Results: We propose an algorithm based on multi-agent deep reinforcement learning that places agents at the vertices of a conveyor network graph and uses a new state value function. The algorithm has two tunable parameters: the length of the path along which the state value function is calculated, and the learning coefficient. Through the selection of parameters, we have revealed that the optimal values are 2 and 1, respectively. An experimental study of the algorithm using a simulation model has shown that it allows to reduce the number of collisions of moving objects to zero, demonstrates stable results for both optimized scores, and also leads to a lower energy consumption compared with the method used as a baseline. Practical relevance: The proposed algorithm can be used to reduce delivery time and energy when managing conveyor systems.

Towards Neural Routing with Verified Bounds on Performance

When data-driven algorithms, especially the ones based on deep neural networks (DNNs), replace classical ones, their superior performance often comes with difficulty in their analysis. On the way to compensate for this drawback, formal verification techniques, which can provide reliable guarantees on program behavior, were developed for DNNs. These techniques, however, usually consider DNNs alone, excluding real-world environments in which they operate, and the applicability of techniques that do account for such environments is often limited. In this work, we consider the problem of formally verifying a neural controller for the routing problem in a conveyor network. Unlike in known problem statements, our DNNs are executed in a distributed context, and the performance of the routing algorithm, which we measure as the mean delivery time, depends on multiple executions of these DNNs. Under several assumptions, we reduce the problem to a number of DNN output reachability problems, which can be solved with existing tools. Our experiments indicate that sound-and-complete formal verification in such cases is feasible, although it is notably slower than the gradient-based search of adversarial examples.The paper is structured as follows. Section 1 introduces basic concepts. Then, Section 2 introduces the routing problem and DQN-Routing, the DNN-based algorithm that solves it. Section 3 proposes the contribution of this paper: a novel sound and complete approach to formally check an upper bound on the mean delivery time of DNN-based routing. This approach is experimentally evaluated in Section 4. The paper is concluded with some discussion of the results and outline of possible future work.

Procedures of Detecting Damage to a Conveyor Belt with Use of an Inspection Legged Robot for Deep Mine Infrastructure

Conveying systems are responsible for a large part of continuous horizontal transportation in underground mines. The total length of a conveyor network can reach hundreds of kilometers, while a single conveyor usually has a route length of about 0.5–2 km. The belt is a critical and one of the most costly components of the conveyor, and damage to it can result in long unexpected stoppages of production. This is why proper monitoring of conveyor belts is crucial for continuous operation. In this article, algorithms for the detection of potential damage to a conveyor belt are described. The algorithms for analysis used video recordings of a moving belt conveyor, which, in case the of hazardous conditions of deep mines, can be collected, for example, by a legged autonomous inspection robot. The video was then analyzed frame by frame. In this article, algorithms for edge damage detection, belt deviation, and conveyor load estimation are described. The main goal of the research was to find a potential application for image recognition to detect damage to conveyor belts in mines.

Operating parcel transshipment terminals: a combined simulation and optimization approach

Parcel transshipment terminals are complex systems that consist of automatic conveyor networks and manual handling activities. Therefore, using discrete-event simulation to evaluate a terminal seems obvious and is often used in the literature. On the other hand, mathematical optimization represents a powerful method that has been successfully used to solve a wide range of logistical problems. Simulation allows for modeling logistics systems with almost unlimited complexity very close to reality, but finding the best system configuration is difficult and time-consuming. In contrast, mathematical optimization has the ability to make complex decisions and find (near) optimal solutions. Real-world logistic systems, however, can only be solved on a lower level of detail without stochastic behaviors. In this article, we present a modeling framework for the operational planning of a transshipment terminal that closely links both methods in order to make use of their complementary advantages. Thus, we are able to handle a large number of decisions, such as (un)loading dock and sorting destination assignments, and consider complex automatic sorting systems as well as manual handling activities with stochastic elements. The approach is evaluated on the example of a parcel transshipment terminal using three different input data scenarios.

Belt conveyor network design using simulation

In this paper simulation is applied to design belt conveyor networks at dry bulk terminals. Stochastic variations in ship interarrival times, shiploads and equipment availabilities enforce the use of simulation. Parameters that affect belt conveyor network designs like the network connectivity, storage policy and stochastic distributions are evaluated in this paper. One of the main findings is that installing the maximum number of connections does not necessarily lead to better performances. Another finding is that redundancy of piles (a pile is in reach of two stockyard machines) is more efficient than increasing the number of connections. In a case study, designs for belt conveyor networks were formulated and assessed using the simulation model developed.

Simulating the Various Subsystems of a Coal Mine

A set of simulation models of various subsystems of a coal mine was developed with the help of a new visual interactive simulation system of technological processes. This paper contains a brief description of this simulation system and its possibilities. The main possibilities provided by the simulation system are: the quick construction of models from library elements, 3D representation, and the communication of models with actual control systems. These simulation models were developed for the simulation of various subsystems of a coal mine: underground conveyor network subsystems, pumping subsystems and coal face subsystems. These simulation models were developed with the goal to be used as a quality and reliability assurance tool for new process control systems in coal mining.

Computerised Decision-Making Support System Based on Data Fusion for Machinery System’s Management and Maintenance

In the present fast-paced world of business in a highly competitive marketplace, the focus on increasing the efficiency of business processes seems to be a reasonable challenge. For this reason in order to optimize production costs, there is an increasing trend toward maximising the use of the operational capabilities of the equipment – technological line components – with the prevention of failure events and their consequences in the form of costly repairs or replacements. A condition-based maintenance (CBM) approach allows to globally monitor, maintain and control operation of the whole complex of equipment and/or processes. The CBM effectively supports decision-making process concerning their further use or determination of the optimum repair/replacement schedule. The presented decision support system is dedicated for an underground copper mine, where the network of belt conveyors is a critical part of the production process. Due to complexity of mechanical system, harsh mining environment and presence of many degradation factors, development of the effective CBM system seems to be justified. It requires the integration of data from different sources, adaptation of advanced data mining techniques, procedures or various diagnostic methods. Because of the multidimensional nature of diagnostic data and diversified technical configurations of the facilities, it was necessary to develop and implement multivariate analytical models based on artificial intelligence techniques. Consequently, it allows to achieve improvement of efficiency of transportation network and reduction of repairs costs and unplanned breakdowns. In this paper we will briefly refer to all these issues.

Novel Approaches for Processing of Multi-Channels NDT Signals for Damage Detection in Conveyor Belts with Steel Cords

Belt conveyors are one of the most popular methods of material transport in many branches of industry, especially in mining. The average length of mining belt conveyor is about 1000 m. Taking into account that total length of transportation ways in averaged mine can approach several dozen of kilometers and network of several conveyors may cover large area, maintenance of such specific transportation system is very difficult. In this work we propose an automatic multi-channel system for data acquisition and processing for damage detection in belts. Belts with steel cords are considered here, they consist of top and bottom rubber covers and steel cords in between them. Due to many reasons (mainly sharpness of transported materials) covers may be damaged and it may initiate degradation process or straight damages in steel cords. Properties of steel cords are therefore crucial for overall strength of belts, if they are damaged, it may cause catastrophic failure of the whole conveyor. So, monitoring of belts conditions is a crucial issue. We proposed a monitoring system that measure and process data from array of magnetic sensors. The system allows to acquire up to 24 channels of NDT signals and uses automatic algorithms to process them in order to get information about begin of the belt loop, location of joints of particular belt segments and the final location and size of damages related to corrosion or cuts of steel cords inside belts. These techniques will be presented in the paper. Our approach has been validated in a lignite mine for several conveyor belts.

A model and an analytical method for conveyor systems in distribution centers

The design and operation of high volume conveyor systems in distribution centers are important due to its high cost, large footprint and critical role in the system. However, there is no analytical model available. In this paper, we study the characteristics of the conveyor sortation system, develop a generic model of a complex conveyor network. We then use the Delay and Stock abstraction to develop an approximate analytical method using sample path analysis and dynamic network flow model. The decision variables include length of accumulation segments and the speeds of conveyor components aforementioned decision variables. This analytical solution provides faster analysis, insights and useful subgradient with respect to the decision variables.

MANAGEMENT OF TRAFFIC FLOW ON A CONVEYOR TRANSPORT

The analysis of control capability of the freight traffic volumes in coal mines, which use storage bunkers for averaging a flow from the mining sections, is carried out on the basis of imitation model of conveyor network with the use of predistribution of conveyor space, on the base of equipment SAUKL for the purpose of stabilizing the freight traffic volume and avoiding the losses during transportation.

Capacity analysis of a towline conveyor system in a distribution center

In a materials flow system, it is important to know the system loading capacity and identify bottleneck links in a short-or long-term planning horizon; and it is beneficial to optimise workforce allocation in order to achieve the best possible system performance under static or dynamic conditions. A multi-commodity maximum network flow model is developed in this paper to determine the flow capacity in a towline conveyor system and to optimise workforce allocation in the system. The proposed modelling approach in this paper uses three types of nodes and two types of arcs to address various types of linkages and processes within a towline conveyor network in a distribution centre. Multiple flow layers are applied to consider various flow paths and commodities. The proposed model and modelling approach can assist in capacity analysis and staffing allocation for a large-scale towline conveyor system in a distribution centre. An industrial case study is presented to illustrate the application of the modelling and analysis approach to determine the maximal flow of a towline conveyor system and identify improvement opportunities.

Simulative study of the decentralized control of complex conveyor networks

Logistics-Journal : referierte Veröffentlichungen, Vol. 2005, Iss. April - Decentralised controls offer advantages for the implementation as well as the operation of controls of steady conveyors. Such concepts are mainly based on RFID. Due to the reduced expense for appliances and software, however, the plant behaviour cannot be determined as accurately as in centrally controlled systems. This article describes a simulation-based method by which the performances of these two control concepts can easily be evaluated in order to determine the suitability of the decentralised concept.

Optimization-based planning heuristic for material flow congestion avoidance in conveyor network design

A model is developed to plan material flow congestion avoidance on a network of conveyors for handling discrete batches of items, e.g. scanned packages. Minimizing maximum material flow congestion is used as a guide to design the conveyor network by evenly distributing the flow of such batches by considering capacities of the conveyors and existing flow. Problems of this type are typically NP-hard which makes them unsolvable by standard mixed integer programming solvers. A method based on results from probability theory is used to solve the formulated problem. Experimental results are presented to demonstrate convergence within 10-100 iterations of the described method for most problems. The increase in CPU time is observed to be approximately linear with respect to the number of constraints and with respect to the number of binary variablesfor a constant number ofiterationsofthe algorithm. A procedure for estimation of bounds is derived to show the proximity of the obtained solution to an optimal solution.

On-line control strategies to minimize peak loads on mine conveyor networks using surge units with variable discharging capability

On-line control strategies to minimize peak loads on mine conveyor networks using surge units with variable discharging capability

A NEW FRAMEWORK FOR SIMULATION OF MATERIAL FLOWS ON MINE CONVEYOR NETWORKS

Mineral Resources EngineeringVol. 04, No. 03, pp. 265-295 (1995) No AccessA NEW FRAMEWORK FOR SIMULATION OF MATERIAL FLOWS ON MINE CONVEYOR NETWORKSJON C. YINGLING and ANIL KUMARJON C. YINGLINGDepartment of Mining Engineering, University of Kentucky, 234D Mining and Mineral Resources Building Lexington, KY 40506–0107, USA Search for more papers by this author and ANIL KUMARDepartment of Mining Engineering, University of Kentucky, 234D Mining and Mineral Resources Building Lexington, KY 40506–0107, USA Search for more papers by this author https://doi.org/10.1142/S0950609895000266Cited by:3 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractA number of state variables important to bulk material conveyor simulation models vary continuously with time, e.g. the position of material along the beltline or the level of material in a feeder, bunker, or discharging/receiving vehicle. Ostensibly, the generation of time histories of these state variables requires continuous simulation, and most belt simulation packages execute what is essentially a continuous simulation using various discretization approaches. However, since it is reasonable to assume that the derivatives of these continuous variables change at discrete points in time, one alternatively can model the system using a higher-order discrete approach. Such an approach is developed in this paper. Advantages offered by the new framework include (1) improved accuracy, (2) faster execution, (3) the ability to realistically interface with models of production or loadout operations, and (4) the ability to study the performance of a wide array of real-time control systems. The framework has been implemented using the event-scheduling interface to the SIMAN simulation language, but it could readily be employed with other discrete-event simulation languages. The framework is demonstrated in examples involving an integrated track/belt haulage system and a system for reduction of peak loads on gathering belts that involves real-time control of feeder discharge rates. FiguresReferencesRelatedDetailsCited By 3Discrete-Event Simulation of Continuous Mining Systems in Multi-layer Lignite DepositsTheodore N. Michalakopoulos, Christos P. Roumpos, Michael J. Galetakis and George N. Panagiotou1 Jan 2015Applying Queuing Theory and Simulation to a Gold Mine Locomotive Selection Problem in BrazilP. C. B. Magalhães and C. M. Vitorino14 December 2017 | OPSEARCH, Vol. 39, No. 1On-line control strategies to minimize peak loads on mine conveyor networks using surge units with variable discharging capabilityJ.C. Yingling, Z. Luo and J. Sottile1 Jan 1997 | IEEE Transactions on Industry Applications, Vol. 33, No. 1 Recommended Vol. 04, No. 03 Metrics History PDF download

Transfer function synthesis using current conveyors

Abstract A procedure for synthesizing active networks due to Hilberman (1968) is revisited in view of recent interest in current conveyors. It is seen that Hilberman's work provides a general procedure for designing RC current conveyor networks to have a specified voltage transfer function, An example is considered in which the current conveyors are implemented using the AD844.

Determining gathering belt capacities for bulk conveyor networks with multiple discrete loading sources

Belt conveyor systems used in handling bulk materials are often loaded intermittently or at varying rates. In some instances, these systems are also fed by multiple loading sources. With such systems, the possibility of loading from two or more sources superimposing must be addressed in specifying the conveyor capacities. Generally, discrete event simulation models have been advocated for specifying belt capacities in these circumtances. During this study, an analytical method is proposed for sizing the belts. It combines an exact expression for the probability distribution for loading and the binomial distribution for the probability that only some belts are loading simultaneously to form a compound distribution for the flow rate. The analytical method and a simulation model are compared for two belt sizing applications. Only minor differences in the belt sizes were evident. When loading sources are similar and flow controls are not present in the belt system, the analytical method would be preferred over the simulation approach because it is easier to apply and much more computationally efficient.

Comments on ‘Realization of current conveyor all-pass networks’

Comments on ‘Realization of current conveyor all-pass networks’