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Simulation Using Arena for an Automobile Assembly Plant

By DinaMasannat Jan 13, 2013 1941 Words
SCHOOL OF TECHNOLOGICAL SCIENCES
INDUSTRIAL ENGINEERING DEPARTMENT

Simulation Project- IE532

* Table of Contents:

1. Introduction……………………………………………………………………………………………………..2

2. Approach………………………………………………………………………………………………………….3

3. Input Analyzer………………………………………………………………………………………………….9

4. Animation……………………………………………………………………………………………………….10

5. Results…………………………………………………………………………………………………………….11

4. Discussion……………………………………………………………………………………………………….15

5. Conclusion………………………………………………………………………………………………………16

* Introduction:

In this project a model was built to simulate processes of an automobile assembly plant, which is divided into three main departments:

1) The body shop: it is the first department of the plant, where the assembly process starts. In this department, two raw materials are received: a) The body side panels (BSP) b) The floor pan (FP).

Starting with the ‘BSPs’, these are fastened at the very beginning of the process by three sequential ‘toy tabbing’ workstations, then they are sent to a ‘Robogate line’ consisting of four parallel welding robots, in order to be welded. Each BSP is sent to the robot with the least number waiting in the queue. After that, BSPs are sent to ‘re-spot line’, which contains three sequential work cells; the first cell has two machines. Each BSP selects any of the 2 machines in a random order. The second cell also has the same 2 machines, but each BSP is sent to one of them according to a cyclical order. The third cell has only one machine. Finally BSPs are sent to manual assembly station.

Floor pans (FPs) are directly sent to the same manual assembly station, then one welded BSP is assembled with one FP to form the ‘car’s body’.

2) The paint shop: this is the second department, where the car body is to be painted. The first step is to pass the assembled ‘car’s body’ through a dipping tank in phosphate workstation. Then, it passes through prime tank in prime workstation. After that, the painted body is left for drying on an overhead conveyor. At the end of this department there is an inspection point, where 80% of the painted bodies go directly to the next department, and 20% go into a repair loop to be fixed. The repair loop has a maximum capacity for 10 cars, so when the line is full the cars should wait in a buffer.

3) Trim-chassis: this is the third and the last department, where the motor, transmission, steering, seats and wheels will be added to the painted car body.

* Approach:
We started our model working on the first department.
First of all, we started creating the BSPs using the ‘Create’ module. The creation time of each BSP is recorded using an attribute using ‘Assign’ module. Then, using a submodel, the three sequential toy tabbing processes are represented by 3 sequential ‘Process’ modules, each preceded by a buffer station. The entity is transferred from one process to the next buffer station using the arrow as the transfer time is considered to be zero. Entities are now routed using the ‘Route’ module to the next robogate line station, each in 2 minutes. A new submodel is used, where ‘Pickstation’ module is used to reflect the entity pick of the robot that has the minimum number waiting in a queue. After a robot is picked, entity is transferred to the robot’s buffer station and then to the robot itself, where it is processed.

After that, entities are transferred to the respot line station using the ‘Route’ module, each in 2 minutes. As before, a new submodel for this workstation is used, where three sequential cells are displayed using ‘Process’ modules, the first two with a set of resources defined in the ‘Set’ spreadsheet showing machines 1 and 2 used in this workstation, and a third cell represented by a ‘Process’ module with one machine used as a resource. Each cell is preceded by a buffer station and the transfer time within the workstation, between cells is considered to be zero.

Now, entities are transferred to the final workstation in this department (assembly) using the ‘Route’ module, each in 2 minutes. A submodel is again used to show this workstation. In this submodel, new entities are created using ‘Create’ module, referring to the FPs, each of the FPs is matched to a welded BSP using the ‘Match’ module. Then the matched entities are batched into one entity using the ‘Batch’ module. Assembly process is carried out by one operator using the ‘Process’ module. Now, car bodies are transferred to the paint station, located in the second department using the ‘Route’ module, each in 10 minutes.

The second department:

In this department (Paint Department), car bodies are transferred to a conveyor. This conveyor is made of cells, each of 2 m long. The 2 m long car accesses one cell of the conveyor using an ‘Access’ module. The body is now conveyed to the phosphate station. The car body now exits the conveyor and passes through phosphate tank (as a ‘Resource’), where it is processed for 10 minutes (from the data we have 100m long conveyor with 10m/minute speed) using the ‘Process’ module. Then, it is transferred to the prime station, after which it is transferred to the prime tank, where it is processed for 12 minutes (calculated as for the phosphate tank) using the ‘Process’ module as well. After that, car body is transferred to the drying station, then left to dry for 45 minutes (from the data we have 45m long conveyor with 10m/minute speed for 10 times).

Now, it takes 2 minutes to route the dried painted car body to transfer it to the inspection station using the ‘Route’ module. Here, car bodies are inspected using the ‘Process’ module. Then, using the ‘Decide’ module, 80% of the car bodies will pass the inspection and are routed to the final department in 10 minutes using the ‘Route’ module, while the remaining 20% are sent to the repair loop station and then to the repair process, where it is repaired by an operator. To show that the maximum capacity of the repair loop is 10 cars, we used another decide (2-way by condition) which will let the car pass to the repair station and then to the repair loop only if the number of cars in the repair loop are less than or equal to one, otherwise, car bodies will be sent to the buffer are represented by the ‘Hold’ module. However, as soon as one car goes out of the repair loop, there will be a place for a new car, this will activate a signal which releases one car from the buffer area using the ‘Signal’ module. After all, all passes and repaired cars are transferred to the final trim chassis station, located in the final third department, using the ‘Route’ module, each in 10 minutes.

The third and last department:

In the last department, painted car bodies gather at the final trim chassis station at the beginning. We used a submodel to show the process flow within the first workstation, where a motor is added using ‘Process’ module, then the car is transferred to the transmission buffer station, transmission is added using ‘Process’ module, the car is transferred to the steering buffer station, steering is added using ‘Process’ module again, then the car is transferred to seats station, seats are added using the ‘Process’ module as well, the car is transfer. All transfer times within this workstation are negligible. Now, we have completed the assembly process, and finished products are considered to be ‘Cars’; this is why a new entity type is assigned to these entities using the ‘Assign’ module. Finished cars gather at another point represented by the ‘Hold’ module. At the same time a truck is created by the ‘Create’ module, then it is held until exactly 10 cars gather at the first hold, this is represented by another ‘Hold’ module. Now, the truck picks up the 10 cars using the ‘Pickup’ module and transfers the cars in 30 minutes using the ‘Process’ module. The truck drops off the cars at a temporary inventory station, make span of each car is recorded using the ‘Record’ module and entities are disposed using the ‘Dispose’ module. The truck goes back to the hold area, while it trip number is recorded using the ‘Record’ module.

* Input Analyzer Data:
1. Toy Tabbing 1:

2. Robot 2:

3. Manual Assembly:

* Animation:

* Results:
1. The total number of cars leaving the model is 660 cars.

2. The average make span of a car in the model is 126.51 hours.

3. The average waiting time in a queue for the different queues is shown below:

4. The average number of entities waiting in a queue of different queues is shown below:

5. Different Resources’ Utilization is as follows:

6. The total number of trips performed by the truck is 67 trips.

7. The total cost of the repair operator:

Cost = cost per hour per use * resource’s utilization * total number of working hours = 5 * 0.064 * 8 * 30
= $ 76.8

8. Required Resources’ Capacity:

* Discussion:

After running the model and analyzing the results, we can discuss several topics including that of the make span, which was noticed that is relatively long for an automobile assembly line.

What is more, a lot of resources have lower than 70% utilization and some of them even do not reach the border of 20%, which grabs our attention and signals some needed modifications.

Also, the average number in queue for the matching module of the BSPs and FPs is the highest; this is due to the identical time between arrivals for both entity types, although BSPs undergo several processes, while FPs are transferred directly.

A comparison should be made between the number of cars leaving the model (670) and the market demand, to know how much is the facility satisfying its customers.

Considering some ways to reduce the costs, the following are worth mentioning:

1. Increasing the number of cars to be picked up by a single truck. This was implemented in our model, but an error message regarding the 150 entities was reported. However, this could be resolved or tested by using a full version of Arena.

2. If the inspector inspects better-quality-products which will pass the tests and result in fewer products that will go through the repair loop, which costs more than transferring the good parts directly to the final department.

3. Try to automate and optimize the transfer time between departments and workstations, which would reduce the average make span of the entities.

4. Since some resources have low utilization, these resources, if possible, can be substituted with other operators in the same department to do his/her job, or simply by merging such workstations with other ones in the same department utilizing only a single resource.

5. Reducing the transfer time of the truck by locating the ‘temporary inventory station’ at a nearer location to the facility.

6. Try to outsource (make or buy decisions) the Body Side Panels in order to eliminate the long operations done to them prior to their assembly.

7. In the ‘Robogate Line’, 4 robots are being used and one of them has zero utilization, while the others are of no more than 70% utilization, so we can get rid of some of the 4 robots.

* Conclusion:

After building and running the model, we can conclude the following: The system was represented with the best possible way to simulate an automobile assembly line. However, while building the model, various errors were encountered and then solved. The current model tends to be satisfying, although it has a lot of potential improvement areas discussed before.

Animation was a great tool added to clarify and illustrate processes and relationships between workshops and departments.

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