2000 SIMULATION AS A TOOL FOR RESOURCE MANAGEMENT

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Zayed and Halpin,Name Symbol Function,This element is always preceded by Queue Nodes. Before it can commence units must be available at each. Combination COMBI of the preceding Queue Nodes If units are available. Activity they are combined and processed through the activity If. units are available at some but not all of the preceding. Queue Nodes these units are delayed until the condition. for combination is met, This is an activity similar to the COMBI However units. Normal Activity arriving at this element begin processing immediately. and are not delayed, This element precedes all COMBI activities and provides a. Queue Node location at which units are delayed pending combination. Delay statistics are measured at this element,It is inserted into the model to perform special. Function Node functions such as counting consolidation marking. and statistic collection,It is used to define the number of times of the.
Accumulator,system cycles,Indicates the logical structure of the model and. Arc direction of entity flow,Figure 1 Basic CYCLONE Modeling Elements. The sub objectives of this study are as follows tower two belt conveyors two cement silos and a dis. charge unit This facility serves an area of approximately. 1 Study of each component of the batch truck pump 15 miles radius The production capacity of the plant was. cycles rated as approximately 40 cy hr, 2 Development of a Micro CYCLONE model for Figure 2 shows the flow diagram for the concrete. these processes batch plant and the transit mixer cycles The material is. 3 Collection of data about the duration of each withdrawn from the storage area to fill the batch hopper. activity to estimate both deterministic and random through conveyor belt 1 There is a scale for measuring the. times intrinsic to the model aggregate weight in the hopper tower before discharging to. 4 Simulation of the performance and productivity for the transit mixer through the conveyor belt 2. various numbers of trucks and various distances, 5 Calculation of the optimum number of trucks 4 MODEL DESCRIPTION. corresponding to the various distances, 6 Construction of the contour lines for the optimum The model developed consists of several cycles for the.
travel areas around the batch plant following resources as indicated in Figure 3. 7 Development of decision making tools for, concrete batch plant management to decide the 1 Conveyor 1 is used to transport the aggregates. optimum resource combination with minimum from the storage area to the storage hopper It has. production time and cost three different operations namely waiting for the. aggregates transporting the aggregates and,3 MODELING CONTEXT maintenance. 2 A hopper is used for storing the different types of. In order to address the decision making environment a aggregates It receives the aggregates from con. batch plant transit mix delivery operation located in veyor 1 and stores them for feeding to conveyor 2. Lafayette Indiana was studied The observed facility After feeding conveyor 2 it waits for Conveyor 1. consisted of storage bins for sand and gravel a hopper to provide re supply. Zayed and Halpin,Transit Mixer,Return to Reload,Conveyor 2. Concrete Batch Delivery,Plant Storage Area,Conveyor 1. Transit Mixer,Transit Mixer,Transit Mixer,Travel to Site Pump.
Figure 2 Flow Diagram for the Concrete Batch Plant and the Transmit Mixer. 24 43 42 45,Truck Mixer,7 4 Hopper 29 Conveyor 2 31 41. 8 5 28 0 93,34 35 37 38 47,Conveyor 1,34 Truck Waiting 43 Truck Available Under Plant. 1 Cement Available 11 Truck Maintenance,12 Truck Maintenance 2 45 Truck Available. 3 Hopper Empty 35 Move Truck to Pump,46 Truck Departure. 4 Feed Hopper 14 Admixture Available 36 Space Available. 24 Water Available 47 Pump Remaining Concrete,5 Hopper Occupied 37 Truck Ready to Unload.
27 Load Available 38 Unload Truck into Pump 48 Concrete Available. 6 Conveyer Available, 28 Conveyer Available 39 Pump Available 49 Crew Available. 7 Maintenance, 29 Transport Load 40 Truck Returning to Pump 50 Spread Finish Concrete. 8 Dummy One, 9 Dummy Two 31 Load Truck 41 Plant Available 60 Counter. 10 Maintenance 33 Travel to Site 42 Truck Moving to Plant 51 End. Figure 3 Micro CYCLONE Schematic Model for Concrete Batching Plant. Zayed and Halpin, 3 Conveyor 2 transports the aggregates from the c Visual or graphical tests. hopper to the truck mixer It waits for the truck Scatter plot indicates that the straight line. mixer Following truck loading maintenance is is a good fit for the data. done 7 of the time After feeding the truck Normality assumption for the residual is. mixer it waits for the hopper to be available achieved and approximately good. 4 The truck mixer transports the concrete from the Constancy assumption for the residual is. plant to the placement sites To load the truck approximately good. mixer cement aggregates water admixtures and Independence assumption for the residual. conveyor 2 should be available After the truck is approximately good. mixer is loaded it travels to the site where there is d Adequacy of the model. a 15 probability maintenance will be done while Lack of fit LOF test is done for this data. waiting for the pump To deliver the concrete to where there are replications in this data The. the pump a truck mixer and a space should be probability of LOF test is p 0 203 that. available beside the pump After unloading the indicates that the model is adequate for this. truck mixer returns back to the plant There is a data. 5 probability that maintenance will be done 2 The Return Time was also calculated by regres. prior to returning to the plant for reload sion between Return time and distance The. 5 The pump receives the concrete from the truck model is. and supplies it into the pump pipes to the place, ment sites After this operation the pump waits Returning Time min 0 019 1 4003 Distance.
for other truck mixers to deliver concrete miles, 6 Laborers in the placement sites where the concrete. is received from the pump pipes do the spreading Note pushing the intercept to be zero resulted in. operation After finishing the spreading opera insignificant model. tions labor crews finish the concrete surface, 7 These tasks are done repetitively Statistical Analysis. a Test the Linear Relation, 5 DURATION OF SIMULATION ACTIVITIES F value 178 64 with probability p 0 0001. Then 1 is O K at 5 level of significance, In order to build a management decision making tool data and there is a linear relation between hauling. were collected for the duration that were required for simu time and distance. lating the truck cycle i e loading unloading hauling b Relative Variation. returning and delay times for truck mixer In addition r square 0 934 where this is an indicator. transport times for sand and gravel and other concrete that the reduction in variation is small. ingredients in the batch plant were also required c Visual or graphical tests. Scatter plot indicates that the straight line, 1 The Haul Time was calculated by conducting a is a good fit for the data.
regression analysis relating time and distance for Normality assumption for the residual is. various distances The regression model is achieved and approximately good. Constancy assumption for the residual is, HaulingTime min 0 0571 1 6006 Distance approximately good. miles Independence assumption for the residual,is approximately good. Note pushing the intercept to be zero resulted in d Adequacy of the model. insignificant model Lack of fit LOF test is done for this data. where there are replications in the data The, Statistical Analysis probability of LOF test is p 0 1876 that. a Test the Linear Relation indicates that the model is adequate for this. F value 259 06 with probability p 0 0001 data, Then 1 is O K at the 5 level of signifi 3 Loading and Unloading times are calculated as. cance and there is a linear relation between BETA distributions from collected data by using a. hauling time and distance Beta curve fitting program. b Relative Variation 4 Other times were estimated as deterministic or. r square 0 9511 where this is an indicator triangular distributions by the plant manager. that the reduction in variation is small,Zayed and Halpin.
5 Others are estimated as BETA distributions using selected as the feasible region of solutions The same trend. the VIBES Program Abourizk 1991 means that a solution should have cost and productivity. that are more than the previous solution to keep it in the. 6 RESOURCES COST ESTIMATION feasible region Therefore when a solution combination of. cost and productivity is more than that of the previous. Cost estimation for the resources that were critical to the solution it can not be eliminated since we do not know if it. models presented was used to conduct sensitivity analysis is feasible or not. by using different resource combinations The costs that. are estimated are as follows 8 1 Selecting Feasible Solutions. Truck cost is estimated as 150 hr The criteria for eliminating infeasible solutions are shown. Conveyor Belt 1 cost is estimated as 70 hr graphically in Figure 4 In this figure the cost and produc. Conveyor Belt 2 cost is estimated as 40 hr tivity combinations are drawn for different sensitivity. Sand Gravel Hopper cost is estimated as 30 hr analysis results of the simulation model for 5 miles dis. tance The points provide examples of the resulting sensiti. 7 SIMULATION SENSITIVITY ANALYSIS vity analysis solutions Each solution or point has a value. for the productivity and a value for the cost per concrete. Sensitivity analysis was done for the model by varying cubic yard The bold lines represent the connection bet. different resources The selected resources were those that ween the cost value and the productivity value for the. had zero or close to zero percent idleness This percent feasible solutions and the thin lines represent the connec. means that these resources are critical in a sense that they tion between the cost value and the productivity value for. control the process Therefore changing them may affect the infeasible solutions e g negative cost productivity. the production and cost of the operation The resources slope For example point 1 solution 1 has a lower cost. were varied in the model as follows than point 2 solution 2 where it has a higher productivity. than the same point This means point 1 is more feasible. of trucks 3 5 than point 2 This also means that any solution line with a. of pumping spaces 1 2 negative slope intersecting the solution line representing. of conveyor 1 1 2 point 1 could be logically eliminated because it has a. of conveyor 2 1 2 higher cost and lower productivity than point 1 Therefore. of hopper loads 4 5 points 2 9 10 and 11 are eliminated because of point 1. of combination is 232 combination Point 8 is eliminated because of point 7 where it has the. hauling and returning distance was incremented same productivity and larger in cost Point 3 is eliminated. by 2 miles starting from 3 mile to 15 miles due to point 4 where they are equal in productivity and. point 4 is less in cost On the other hand points 1 4 5 6. 1000 cycles were simulated using the Micro, and 7 could not be eliminated because the solution lines do. CYCLONE program, not intersect In other words each solution has a higher. cost and a higher productivity than the previous one. Simulation was done to analyze the batch plant operation. Therefore one point can not eliminate the other These. by investigating these resource combinations and distances. solutions are feasible and the best solution is one of them. in the model This analysis is discussed in the following. The best solution may not be the lowest cost solution The. same procedure of selecting the feasible solutions is. followed for the sensitivity results for all the assigned. 8 SIMULATION RESULTS ANALYSIS, distances These sets of solutions corresponding to. different distances are indicated in Figure 5,Micro CYCLONE was used to simulate the model with. various resource combinations as noted above Micro. 8 2 The Productivity Unit Cost Chart, CYCLONE provides a sensitivity analysis report that.
includes the productivity and unit cost for each resource. Based on the criteria explained in Figure 4 the sets of. combination or alternative This report is done for each. feasible solutions according to their unit cost productivity. distance starting from 3 miles and incremented by two up. and different combination of resources are drawn in Figure. to 15 miles This generates 232 alternative solutions These. 5 In this figure the productivity is drawn against the unit. solutions were analyzed to eliminate infeasible solutions. cost for each feasible solution The feasible solutions pro. Sensitivity results were analyzed to eliminate the solutions. ductivity for each of the distances 3 5 7 and 9 miles are. that have high cost and low productivity After this screen. close to each other On the contrary the feasible solutions. ing the set of solutions that had the same trend in cost and. productivity for each of the distances 11 13 and 15 miles. productivity e g low cost and high productivity was. Zayed and Halpin,31 17 Point 2,31 30 97 Point 3,30 25 30 25 Point 4. 29 22 Point 5,29 28 95 29 06,28 56 28 71 Point 6,27 51 27 71. SIMULATION AS A TOOL FOR RESOURCE MANAGEMENT Tarek M Zayed Daniel W Halpin Division of Construction Engineering And Management School of Civil Engineering Purdue University West Lafayette IN 47907 1294 U S A ABSTRACT The decision making process is a very essential part of any construction operation Simulation can be used as a tool to assist construction managers in making informed

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