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White Paper

Simulation based Validation of a New Automotive Final Assembly Plant Design Abstract A discrete-event simulation project was undertaken to assess the ability of a new plant to perform as per the set output levels. The model was aimed at providing a clear picture of the number of automobile parts that could be produced with the planned resources and also to identify major bottlenecks in the plant. Interaction of the model with the subassembly lines was the key in determining system output. Utilization of resources, hourly throughput from the plant, repair area utilization and test area line speed optimization were among the significant results obtained from the model. The model & associated results served as a tool that could be used for experimenting with what-if scenarios and looking ahead even before plant is fully constructed.

1. Introduction The company had planned to build a new automobile manufacturing plant in the northern part of India. Post construction, the plan was to have the final assembly facility produce three models & operate at a planned throughput of 68 JPH. The project was carried out in two phases – phase 1 to cater to 45 JPH target and phase 2 for 68 JPH target. Objectives of the project: • Test the system for net 45 JPH and 68 JPH • Identify bottlenecks and key areas of potential concern • Validate resource (carriers, conveyors etc.) requirements • Evaluate these resources at boundary limits – reject rates, downtimes etc. • Other specific what-if analysis 2. System Review TCF (same as Final Assembly System) stands for Trim, Chassis, and Final in an assembly plant. Once the BIW (or body in white) has been painted it goes to TCF. Trim is all of the components such as glass, fabric, plastic panel, etc that allow the vehicle to look the way that it does. Chassis is where the components that operate the vehicle are installed (axle, engine, IP, etc). Final is the final assembly area where the vehicle has the wheels, fuel, alignment and testing completed prior to shipping. The process is flow from Body Shop (BIW metal assembly of the vehicle) to Paint Shop (Paint, where the vehicle is painted and sealed) and then TCF (where the final assembly is completed and the engine is married to the chassis).

2 3. Methodology The simulation tool ‘Simul8’ was used to model the TCF plant. This is because of the ease in modeling and the user friendly excel interface features of Simul8. The simulation model was designed according to the process sequence with the given number of stations, pitch, number of parallel testing lines, repair booths and interaction with the various sub assembly lines. The entire system was broadly divided into these sections – trim line, chassis area, decking line, final line and test area. In case of a breakdown in any line, the entire section is stopped. Initial analysis was conducted to assess the effect of the given downtime on each area. After verifying that the downtime was within allowable limits to produce target throughput, hangers required at each area was estimated. Sub assemblies were merged with the main line to provide required parts at the correct station on the line. Having optimal number of hangers is the key for proper functioning of the system. The sub assemblies modeled for this TCF model are the doors line, Instrument Panel (IP) line, Engine Dressing Unit (EDU) along with a pony pack system (clubs EDU and the decking section). Also skillet requirement to carry the body from trim through decking was evaluated. Another notable requirement was that of optimizing RGVs used for transfer of engines from pony pack to the main line. Table 1. Optimized Hanger Count

The model was used to assess the adequate amount of buffer required on the chassis lines. The system was designed in such a manner that there were buffers between trim-decking and between decking-final lines. These buffers are important so that the model does not stop immediately during a breakdown. The model gave average number of bodies in the chassis buffer and hence the optimum buffer size. Table 2. Buffer Recommendations

3 The model played a very important role in determining the line speed of each test line and the repair area requirement. After the body comes out of the final line, repair units are routed to the repair area and good units go through test stations. Tests performed are the End of Line (EOL) test, CAL, Underbody test, Water test and Squeak Rattle test. Parts rejected after each test station are routed to the respective repair area. After undergoing repair, they are rerouted to the test line. Test line speeds have to be considerably high to accommodate for repaired units to join the line again. Maximum accumulation at repair areas was analyzed. Many of these complexities were visible because the simulation model was a replica of the real system. Table 3. Test and Repair Area Analysis

A significant outcome was the analysis of long downtime in the system. The effect of long downtime and subsequent stoppage of each area was analyzed to take steps that cushion for those losses in the overall system.

Fig 1: Long Downtime Analysis Fig. 2 shows a snapshot of the model.


Fig 2: Model Snapshot

4. Results  The simulation model proved as an effective validation tool for the new TCF plant since many intricacies of the system were made visible.  Hourly throughput of the model provides an indication of the jobs completed every hour across the run period and the randomness in the model (Fig 3).  Time in state chart provides a versatile view of how each area is subjected to utilized, starved and idle states. This is very important as it helps us quickly find the system bottleneck. Many decisions such as increasing / decreasing capacity of any area, downtime reduction etc. can be taken with the reference of the TIS chart (Fig 4).  Other charts such as buffer statistics chart and Power & Free statistics charts were provided as model output to enable deep dive analysis.


Fig 3: Hourly Throughput

Fig 4: TIS Chart depicting TIS of each area

Note: Several area names, numbers and details have been omitted and/or modified from this white paper to protect confidentiality of the client’s information. Additionally, this document is confidential and should not be shared with anyone without consent from Production Modeling India.



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