Simulation of processes in a mining enterprise with Tecnomatix Plant Simulation



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Simulation of processes in a mining enterprise with Tecnomatix Plant Simulation Vladimir Medvedev

Simulation of ore extraction on the open mountain works Page 2

Simulation objective To verify current control algorithms of the mining complex To simulate the mine operation and to predict how changing parameters influence: Overal throughput Bottlenecks Quality of ore dynamics To find the set of parameters which provide the proper mine operation Page 3

Simulation model Simulation model include one of tecnological complex of the mountain works Simulation model represent the following processes: Ore extraction Ore storage Internal ore transportation Ore shipment (to railcar) Page 4

Simulation model Contents: Objects Ore storage Truck motion simulation Routing and control Page 5

Simulation model Simulation model include the following objects: Truck parking area Trucks Excavating machines Ore storage places Shipment excavator Transport network На следующих слайдах объекты рассмотрены более подробно Page 6

Truck parking area All trucks are automatically generated at this point in the beginning of simulation and further proceed to the transport network All trucks end at this point when simulation finishes (a specified number of shifts passes) Area contain the full set of truck parameters: Number of trucks Truck models Truck payload Truck speed Page 7

Trucks Trucks travel through the mine transport network Each truck has the following attributes: Maximum payload Current payload Average quality of ore in the truck body Speed coefficient Assigned number Target location Starting location Assumptions: Current road situation is not considered in routing methods Engine characteristic curve is not considered (computation may not be totally correct, for example when driving along the lengthy ascending grade) Page 8

Excavating machines Excavator is a stationary equipment (it does not change location during the simulation run) Loads extracted ore into a truck and sets a target destination Loading duration 3 minutes Weigth of loaded ore depend on truck s maximum payload (90 tons) Ore quality from0 to70percent All parameters are random values with normal distribution law Several trucks may wait for processing in a queue before an excavator 0 85 35 70 Ore quality 90 95 Ore weigth Page 9

Simulation model Contents: Objects Ore storage Truck motion simulation Routing and control Page 10

Ore storage places Is an intermediate place for ore storage defined with the following attributes: Capacity Truck processing time (3 minutes) Quality of ore (high or average, accept trucks only with target ore quality) Consists of two zones, for incoming and outgoing ore flow. Each zone is represented by a 3D-mattrix: Parametric dimensions Each element stores a quality of ore in the appropriate volume cell The maximum weight of each cell is defined (40 tons) If outgoing zone is empty and incoming zone is full, they exchange places Page 11

Ore storage incoming flow Zone is filled with extracted ore in the following sequences: By horizontal layers By rows of a layer Be cells of a row All cells (except of the last one in each row) are filled completely (40 tons) The last cell in a row can be filled partially (weight is computed and known) When ore (from the next truck) is added to the partially filled cell, ore quality is averaged When the whole layer is full, it s being floated (ore quality averaging) Page 12

Storage areas quality averaging Quality averaging is performed by layers: Average quality of ore in the layer is calculated (M) A new quality for each cell is calculated with the following formula: f av_ij average quality in a cell f ij source quality value M average ore quality in a layer k averaging coefficient f av_ij =f ij (f ij M) k, Degree of averaging is set with coefficient k: whenk= 0 averaging is not performed whenk= 1quality in each cell equals to average layer quality (M) Page 13

Storage areas outgoing flow Excavator takes ore out of a storage by colomns, starting from the top cell and loads ore to a truck Ore quality inside a truck is averaged Loading process continues until a truck is full or storage is empty Page 14

Ore shipment area Trucks bring ore with required quality and unload it to the shipment site Excavator loads ore from the shipment site into railcars Operation process is the same like at storage areas except: Excavator loads ore continuously (while shipment site contains ore) Loading time of one railcar is specified Page 15

Contents: Objects Ore storage Truck motion simulation Routing and control Page 16

Road network Network represents a set of roads, each road has two main attributes: Length Gradient (upslope, downslope, flat) Trucks speed depends on the current gradient and truck load: 10 km/hwhen driving up 30 km/hwhen driving down or up horizontally Also nominal speed is multiplied by a coefficient which depends on a type of the truck. Road network object also performs an automatic routing of trucks Page 17

Transport network Excavator 1 Excavator 2 Excavator 3 Storage 1 Parking Storage 2 Disposal pile2 Shipment knots roads default roads Disposal pile1 A fragment of road network Page 18

Contents: Objects Ore storage Truck motion simulation Routing and control Page 19

Routing and control Decision of truck s destination is made once truck leaves the source object (parking, excavator, storage, disposal or shipment). For each truck objects which can load and unload it are defined. Current setting is: 3 trucks are assigned to transfer ore from each excavator (9 in total) 9 trucks transfer ore from storage areas to shipment When setting new destination for a truck each possible destination object estimates how much it needs this particular truck. Estimation value depends on: Weight of ore in truck s body Ore quality Object s status (i.e. how full is the storage) Object with the maximum estimation value is selected as the new destination Page 20

Simulation model Some elements of the model Setting of parameters Output of results Page 21

Main frame The main frame shows the basic layout with road network This view visualizes trucks driving along the network roads Control elements are grouped to appropriate buttons and dialogs Page 22

A snapshot during a simulation run Page 23

What s behind the model Road network inside Page 24

What s behind the model Objects representing equipment and areas (picture shows a storage area) Page 25

What s behind the model Control algorithms (methods) Page 26

What s behind the model Object parameters Page 27

Simulation model Some elements of the model Setting of parameters Output of results Page 28

Setting parameters Parameters of the model can be defined with designed user interface[ [ or directly in object properties Page 29

User dialog interface Simulation can be controlled from the dialog menu (start/stop/reset, toggle animation etc) Page 30

Simulation model Some elements of the model Setting of parameters Output of results Page 31

Output of results Results of a simulation run is shown in the form of numerical values and also diagrams and charts Quality of ore extracted by excavator Page 32

Output of results Volume of ore shipped 10.000 тонн Occupation of storage places Outgoing flow Incoming flow Zone swap Page 33

Output of results Simulation results in the following table with integral truck mileage with division by empty/full trucks driving up/down/flat: The same data set is available for each individual truck Later this information may be used for many calculations: truck wear and amortization fuel consumption planning of truck maintenance and repair many other factors [ Page 34

Output of results Some results are shown right in dialog windows of individual objects: Utilization Number of loaded trucks Number of trips etc Page 35

GANTT charts Time Resources Operation time Page 36 Truck parameters: Location Truck id number weight /quality

Диаграммы Ганта заказы (2) List of trucks Time Operation time Truck driving time Page 37

Conclusion Page 38

The prototype model created represents a real mine, however some processes are non fully implemented. Below are some assumptions. Quality of ore extracted by excavator is completely random, there is no dependency in sequence of buckets. Storage area models does not fully represent the functionality of real storages Shipment control logic is simplified Truck routing algorithm is simplified and does not represent all regulations in a mine Page 39

Created model may be used for: Optimization of a set of technological equipment in the mine Finding the optimum method to average the quality of ore Optimization of throughput and utilization of mine sites Planning of repairs and maintenance Estimating operational costs Planning the quality of ore shippings Page 40

Thanks! Page 41