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Then, the distributions calculated using EasyFit were used in the simulation model as the processing time of each process and were placed inside the intelligent objects, as shown in Figure 7. SimioTM software experiments are used to define a set of scenarios to be executed using the model. The experiment is formed by scenarios, which are composed by control variables (such as the size of every input inventory) and output variables (as throughput, cycle time and WIP). For the project, throughput, WIP, and cycle time were the output variables that were analyzed. The obtained values were compared to the actual values of the case studies (provided in the value stream maps) to validate if the model was correct. The expressions that were used are the following: Throughput = sinkshipment.Inputbuffer.NumberEntered CT = EntParts.TimeInSystem.Average WIP = EntParts.NumberInSystem.Average Two models for each Plant (C and D) were then created using the base model but substituting vacuum drying for conventional drying (air drying plus kiln drying) to determine the impact on TH, WIP and CT of the production line. The number of vacuum kilns used for drying and to meet demand was determined by the total throughput that each plant has per year divided by the number of cycles per year the kilns have. The processing times were gathered from the results of the drying times analysis (Section 3.1). Two models were created: one using vacuum drying with air drying and another using only vacuum drying. The inventory amount used was gathered from the critical WIP calculated for the base model as mentioned in 3.3.1.3. The simulation model for Plant C and D were both run for a period of 13 weeks to simulate an approximation of the time required to produce the inventory of each company (time line of the VSM). Each scenario was run with 30 replications because SimioTM needs a minimum of 30 replications to gather more accurate statistical results. 59PDF Image | Impact of Vacuum-Drying on Efficiency of Hardwood Products
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