Assessing Shop Floor Layouts in the Context of Process Plans
Application of the proposed method
Three different systems were modeled to evaluate the response variables according to the control factors. For all three models, a make to order (MTO) production system was considered. A system for the job shop layout was modeled, another for the traditional cellular layout and a third for the virtual cell layout.
In the first stage of the simulation model, the MS Excel random tool was used to generate batches of pieces, and all the pieces were randomly generated from the 40 possible features. The process plans were generated from commercial data of machining times to execute each feature, assuming that the machines of the model are able to execute these features. Table 6 presents the time of execution each feature used in the model.
Table 6 Time of execution each feature.
| Item | Time (min) | Features | item | Time (min) | Features |
|---|---|---|---|---|---|
| 1 | 0,241274316 | Hole | 21 | 0,251327412 | Knurl |
| 2 | 0,326725636 | Hole | 22 | 0,753982237 | Knurl |
| 3 | 0,41469023 | Hole | 23 | 1,507964474 | Knurl |
| 4 | 0,622035345 | Hole | 24 | 2,261946711 | Knurl |
| 5 | 0,753982237 | Hole | 25 | 3,769911184 | Knurl |
| 6 | 2,226672688 | shoulder | 26 | 0,41887902 | Turn |
| 7 | 2,74633631 | shoulder | 27 | 1,316476922 | Turn |
| 8 | 2,90183953 | shoulder | 28 | 2,333754543 | Turn |
| 9 | 3,444728787 | shoulder | 29 | 4,069110485 | Turn |
| 10 | 4,210224073 | shoulder | 30 | 6,821744048 | Turn |
| 11 | 0,832998052 | slot | 31 | 0,897597901 | Face |
| 12 | 1,09479744 | slot | 32 | 1,361356817 | Face |
| 13 | 1,332796883 | slot | 33 | 1,914875522 | Face |
| 14 | 1,378589181 | slot | 34 | 2,558154018 | Face |
| 15 | 1,670213816 | slot | 35 | 3,291192304 | Face |
| 16 | 1,790575256 | 36 | 0,515417545 | Groove | |
| 17 | 2,064659863 | 37 | 0,652862223 | Groove | |
| 18 | 2,674408561 | 38 | 0,790306902 | Groove | |
| 19 | 2,740812469 | 39 | 0,927751581 | Groove | |
| 20 | 3,367707826 | 40 | 1,256637061 | Groove |
Each model contains the same number of machines, which can manufacture certain features. Each manufacturing system contains 10 machines, including 2 drilling machines, 2 conventional milling machines, 2 CNC milling machines, 2 conventional lathes and 2 CNC lathes. There are 8 operators and 3 suppliers.
In total, all models have 21 resources. With respect to the operators, some of them are dedicated to two different resources, while others are dedicated to only one resource. On the other hand, suppliers are responsible for transporting batches of parts from the entrance to each manufacturing system, transporting them to each machine and, finally, delivering them to the dispatch (exit) of each system. Table 7 presents the 5 different types of machines and the respective features that each machine can manufacture.
In total, all models have 21 resources. With respect to the operators, some of them are dedicated to two different resources, while others are dedicated to only one resource. On the other hand, suppliers are responsible for transporting batches of parts from the entrance to each manufacturing system, transporting them to each machine and, finally, delivering them to the dispatch (exit) of each system. Table 7 presents the 5 different types of machines and the respective features that each machine can manufacture.
Table 7 Types of machines and their operations.
| Machine | Operation | Process Plan WITHOUT | Process Plan WITH alternatives |
|---|---|---|---|
| 1 | Drilling machine | Hole | Hole |
| 2 | Milling machine | Shoulder, slot | Hole, shoulder, slot, pocket |
| 3 | CNC milling machine | Hole, shoulder, slot, pocket | |
| 4 | Lathe | Knurl, Groove | Turn, face, groove, knurl |
| 5 | CNC Lathe | Turn, face | Turn, face, groove, knurl |
In the system with job shop layout the similar resources are arranged in departments, which are the following: milling department, drilling department, CNC milling department, conventional lathes department, and CNC lathes department.
In this system an operator is available for each milling machine, conventional lathes and CNC lathes. For the CNC milling machine and drilling machine, the same operator operates these two machines. In general, the batch of parts enters the system and, according to its process plan, it is led from one department to another. If a department is fully occupied, the batch is held until some department machine is released.
The supplier integrates the transportation system, with the 3 suppliers transporting the batches of parts from one department to the other, from the beginning to the end of batch manufacturing. The supplier can transit between all departments, that is, as soon as a supplier is needed, the one that is available will meet the system's need.
In the manufacturing system with traditional cell layout, the cells were established by the criterion of the part type of each batch. That is, the parts are based on 40 different features, which are divided into two groups: features for cylindrical parts, and features for prismatic parts.
One of the control factors is the type of demand, which can be totally random, or controlled. Based on the type of demand, three types of cells were established. The first cell only manufactures prismatic parts, consisting of only one drill, one conventional milling machine and one CNC milling machine. In this way, batches of parts formed by strictly prismatic parts will be manufactured in this cell.
A second cell was established to manufacture parts that contain both prismatic features and cylindrical features. This cell is composed of one drill, one conventional milling machine, one conventional milling machine, one conventional lathe and one CNC lathe.
The third cell is designed to manufacture parts that only contain the cylindrical shape, being composed by one conventional lathe and one CNC lathe.
Each cell will have the presence of one supplier, who will be responsible for collecting the raw material at the beginning of the process and dispatching the finished product to the exit of each system. This supplier is dedicated, that is, it does not interact with the cell nor change cells.
Finally, the manufacturing system with virtual cell layout has the same physical distribution as the job shop layout. That is, the machines are distributed in departments, but the logic of the system changes.
When a batch of parts arrives in the system, the system checks all the resources that will be needed to make that batch. All the resources that will be required to make the batch are seized, which form a virtual cell.
As soon as the resources are no longer required to manufacture that batch, they are released and can thus be used by another batch of parts. With regard to suppliers, they have complete freedom to move between departments.
One of the control factors used in this work is related to the type of process plan, that is, if the process plan contains alternatives or not. In the case of a process plan with alternatives, a second resource option is defined for carrying out a given operation.
It was necessary to establish some parameters related to transportation times for each simulation model mentioned. A uniform distribution with a value of 30 to 60 minutes for transportation between departments was established for the job shop and virtual cell layouts, and a uniform distribution of 3 to 6 minutes for the batch to begin processing in the selected resource.
For the traditional cell layout, a uniform distribution of 3 to 6 minutes for cell entry was established, as well as a uniform distribution of 3 to 6 minutes for the start of the operation in each resource.
In addition to the mentioned transportation times, the distances between each resource and the speed with which the suppliers carry out the transportation were also established. In general, the distances were: (a) between the pieces of equipment = 5 meters; (b) from the system entry to the equipment = 10 meters; (c) between the equipment and the system exit = 20 meters. The speed with which the supplier performs the transportation was established at 5 meters per minute for all three models.
Regarding the setup times, the same values were adopted for both models, which were taken from the paper by Hamedi et al.: (a) drilling machine and lathe = 20 minutes; (b) milling machine, CNC milling machine, and CNC lathe = 35 minutes.
For the change of cutting tools in the drilling machine, conventional milling machines and CNC milling machines, a Poisson distribution with average value 60 was set as the interval, and the change time was a normal distribution of 5 to 10 minutes. The change of cutting tools in the conventional lathes and CNC lathes was established using a uniform distribution of 5 to 10 minutes for the change interval, and an Erlang distribution with mean equal to 2 for the duration of the tool change.
Another very important value in the model is the failure times of the resources. As already shown in Table 2 , maintenance times were established as a control factor in this research, with two levels: high and low. For the maintenance level to be considered high, the manufacturing system must have a maintenance program that seeks to ensure that the machines will not undergo failures and, therefore, the machines will always be available. On the other hand, if the system does not have a specific maintenance plan, it will be subject to resource failures, and this was considered as the low level.
For the drilling machines, conventional milling machines and CNC milling machines, the parameters established by Wang et al. were used, which establish a Weibull distribution (17,151; 71.4) in minutes for the interval between failures, and with constant repair time equal to 96 minutes. For conventional lathes and CNC lathes, 38,400 minutes fault interval values were used, with repair duration of 240 minutes.
In this system an operator is available for each milling machine, conventional lathes and CNC lathes. For the CNC milling machine and drilling machine, the same operator operates these two machines. In general, the batch of parts enters the system and, according to its process plan, it is led from one department to another. If a department is fully occupied, the batch is held until some department machine is released.
The supplier integrates the transportation system, with the 3 suppliers transporting the batches of parts from one department to the other, from the beginning to the end of batch manufacturing. The supplier can transit between all departments, that is, as soon as a supplier is needed, the one that is available will meet the system's need.
In the manufacturing system with traditional cell layout, the cells were established by the criterion of the part type of each batch. That is, the parts are based on 40 different features, which are divided into two groups: features for cylindrical parts, and features for prismatic parts.
One of the control factors is the type of demand, which can be totally random, or controlled. Based on the type of demand, three types of cells were established. The first cell only manufactures prismatic parts, consisting of only one drill, one conventional milling machine and one CNC milling machine. In this way, batches of parts formed by strictly prismatic parts will be manufactured in this cell.
A second cell was established to manufacture parts that contain both prismatic features and cylindrical features. This cell is composed of one drill, one conventional milling machine, one conventional milling machine, one conventional lathe and one CNC lathe.
The third cell is designed to manufacture parts that only contain the cylindrical shape, being composed by one conventional lathe and one CNC lathe.
Each cell will have the presence of one supplier, who will be responsible for collecting the raw material at the beginning of the process and dispatching the finished product to the exit of each system. This supplier is dedicated, that is, it does not interact with the cell nor change cells.
Finally, the manufacturing system with virtual cell layout has the same physical distribution as the job shop layout. That is, the machines are distributed in departments, but the logic of the system changes.
When a batch of parts arrives in the system, the system checks all the resources that will be needed to make that batch. All the resources that will be required to make the batch are seized, which form a virtual cell.
As soon as the resources are no longer required to manufacture that batch, they are released and can thus be used by another batch of parts. With regard to suppliers, they have complete freedom to move between departments.
One of the control factors used in this work is related to the type of process plan, that is, if the process plan contains alternatives or not. In the case of a process plan with alternatives, a second resource option is defined for carrying out a given operation.
It was necessary to establish some parameters related to transportation times for each simulation model mentioned. A uniform distribution with a value of 30 to 60 minutes for transportation between departments was established for the job shop and virtual cell layouts, and a uniform distribution of 3 to 6 minutes for the batch to begin processing in the selected resource.
For the traditional cell layout, a uniform distribution of 3 to 6 minutes for cell entry was established, as well as a uniform distribution of 3 to 6 minutes for the start of the operation in each resource.
In addition to the mentioned transportation times, the distances between each resource and the speed with which the suppliers carry out the transportation were also established. In general, the distances were: (a) between the pieces of equipment = 5 meters; (b) from the system entry to the equipment = 10 meters; (c) between the equipment and the system exit = 20 meters. The speed with which the supplier performs the transportation was established at 5 meters per minute for all three models.
Regarding the setup times, the same values were adopted for both models, which were taken from the paper by Hamedi et al.: (a) drilling machine and lathe = 20 minutes; (b) milling machine, CNC milling machine, and CNC lathe = 35 minutes.
For the change of cutting tools in the drilling machine, conventional milling machines and CNC milling machines, a Poisson distribution with average value 60 was set as the interval, and the change time was a normal distribution of 5 to 10 minutes. The change of cutting tools in the conventional lathes and CNC lathes was established using a uniform distribution of 5 to 10 minutes for the change interval, and an Erlang distribution with mean equal to 2 for the duration of the tool change.
Another very important value in the model is the failure times of the resources. As already shown in Table 2 , maintenance times were established as a control factor in this research, with two levels: high and low. For the maintenance level to be considered high, the manufacturing system must have a maintenance program that seeks to ensure that the machines will not undergo failures and, therefore, the machines will always be available. On the other hand, if the system does not have a specific maintenance plan, it will be subject to resource failures, and this was considered as the low level.
For the drilling machines, conventional milling machines and CNC milling machines, the parameters established by Wang et al. were used, which establish a Weibull distribution (17,151; 71.4) in minutes for the interval between failures, and with constant repair time equal to 96 minutes. For conventional lathes and CNC lathes, 38,400 minutes fault interval values were used, with repair duration of 240 minutes.
The procedure for the generation of production orders is presented in the flowchart of Figure 3 . Some parameters were established as common to the three models, considering that the objective of this work is to compare them.
Figure 3 Flowchart for generating the production orders.
Initially, the user specifies the simulation data, such as the type of plan, the number of batches to be simulated, the time of arrival of the next batch, and whether the system will have a maintenance plan. It is also necessary to specify which of the files generated in the previous step will be used in each simulation.
The arrival of a batch is the event that initiates the simulation process, since the arrival time of the first batch is equal to zero. Therefore, considering that batches of parts have already been specified in the previous stage, it is necessary that the model is able to differentiate each batch as to the type of features in each batch, the duplications of features and the quantity of parts in each batch.
Then, according to the features present in each batch of parts, the operations to be performed were specified. Based on the operations, the machines producing the batches can be established. Before checking the machines, it should be verified whether or not the process plan has an alternative.
If the user chooses a process plan without alternatives, the machine specified as the first option to manufacture that feature is selected. On the other hand, if the chosen plan was the one that contains alternatives, it is considered the work in process to select the machine. That is, if the plan has alternatives, before leading to the first or second machine option, the system checks the option that has the lowest queue.
The next stage, which corresponds to the determination of the machining time, is carried out taking into account the type of process plan chosen. In the plan with alternatives, the second machine option has a 40% penalty attached to the machining time. Once the times are defined, a supplier is required to transport the batch. Whenever it is necessary to enter the system, transport the batch to the next machine or deliver it to dispatch (exit), the supplier was requested. All the transportations that the supplier performs have defined routes and speeds and, thus, the transportation times of the batches of parts can be obtained.
Although all resources were considered available a priori, before carrying out the selected operation, the presence of in-process inventories in the resources was verified. If there is no work in process, the operation is performed immediately, otherwise the waiting time is counted and presented in the simulation report. Before starting machining the batch, the operator sets up the machine.
The batch only leaves the machine when all parts in the batch are machined. In the case of the process plan with alternatives, before leaving the machine, it is verified that the second machine option for the next operation is the same as the current machine. This is done by comparing the work in process in the selected resource to the next operation (first option) with the current resource (second machine option). If the second machine option selected for the next operation is the same as the current machine, an in-process inventory is evaluated to avoid machine change. In this way, the number of setups is significantly reduced.
Finally, it is verified that all operations were performed. If there are no more operations, the batch leaves the system, and its statistical data is collected.
When the simulation comes to an end, with all simulated batches, the report generated by the software is stored with the data that will be used in the calculation of the response variables.
The arrival of a batch is the event that initiates the simulation process, since the arrival time of the first batch is equal to zero. Therefore, considering that batches of parts have already been specified in the previous stage, it is necessary that the model is able to differentiate each batch as to the type of features in each batch, the duplications of features and the quantity of parts in each batch.
Then, according to the features present in each batch of parts, the operations to be performed were specified. Based on the operations, the machines producing the batches can be established. Before checking the machines, it should be verified whether or not the process plan has an alternative.
If the user chooses a process plan without alternatives, the machine specified as the first option to manufacture that feature is selected. On the other hand, if the chosen plan was the one that contains alternatives, it is considered the work in process to select the machine. That is, if the plan has alternatives, before leading to the first or second machine option, the system checks the option that has the lowest queue.
The next stage, which corresponds to the determination of the machining time, is carried out taking into account the type of process plan chosen. In the plan with alternatives, the second machine option has a 40% penalty attached to the machining time. Once the times are defined, a supplier is required to transport the batch. Whenever it is necessary to enter the system, transport the batch to the next machine or deliver it to dispatch (exit), the supplier was requested. All the transportations that the supplier performs have defined routes and speeds and, thus, the transportation times of the batches of parts can be obtained.
Although all resources were considered available a priori, before carrying out the selected operation, the presence of in-process inventories in the resources was verified. If there is no work in process, the operation is performed immediately, otherwise the waiting time is counted and presented in the simulation report. Before starting machining the batch, the operator sets up the machine.
The batch only leaves the machine when all parts in the batch are machined. In the case of the process plan with alternatives, before leaving the machine, it is verified that the second machine option for the next operation is the same as the current machine. This is done by comparing the work in process in the selected resource to the next operation (first option) with the current resource (second machine option). If the second machine option selected for the next operation is the same as the current machine, an in-process inventory is evaluated to avoid machine change. In this way, the number of setups is significantly reduced.
Finally, it is verified that all operations were performed. If there are no more operations, the batch leaves the system, and its statistical data is collected.
When the simulation comes to an end, with all simulated batches, the report generated by the software is stored with the data that will be used in the calculation of the response variables.
Figure 4 illustrates a flowchart of the activities performed in the simulation of the models of the three layouts.
Figure 4 Flowchart for the simulation of the three models.
During the simulation tests the models were simulated at a low speed in order to visualize possible faults, and verify if the model was performing correctly. For this stage of the simulation, animations were set up for the three models, and Figures 5 and 6 illustrate the animations created to aid the verification of the models.
Figure 5 Animation of the job shop and virtual cell layouts.
Figure 6 Animation of the traditional cell layout.
