As one of the leading suppliers of vehicle impact systems for North America, AGS Automotive Systems has six plants throughout Canada and the United States.The Stoney Creek facility assembles the GMT-900 model front bumper for the Chevrolet Silverado Light Duty and Heavy Duty pickup truck models. As the sole supplier of this component for General Motor’s GMT-900 series vehicles, finished front bumper assemblies are sequenced and shipped just-in-time to five GM plants all across North America.
In order to handle such a wide variety of product styles and meet service level requirements from each customer, AGS must employ sophisticated production line processes and tracking systems to monitor individual product metrics.
Anticipating increasing demand for vehicles, AGS planned to install a new advanced conveyor system for its dedicated production line. Before the system went on-line, its handling capacity and production rate must be validated to ensure delivery targets could be satisfied.
In addition, the company must determine the proper number of fixtures and buffer inventory capacity at intermediate stages. This was essential for operating the new system reliably without interruption, allowing it to integrate seamlessly into the existing facility.
The model mimicked a high level view derived from CAD drawings. Model users have complete access to essential parameters through a series of detailed spreadsheets, including:
Adjustment of these parameters would have a direct impact on the performance of the assembly line system.
A set of customized reports track machine utilization, throughput, and volume, providing immediate feedback. The system’s overall effectiveness was validated by running simulation trials with different scenarios, each containing a set of pre-defined parameters, and comparing the change in results between scenarios.
AGS successfully pinpointed bottleneck workstations on the new assembly line through analysis of individual stations’ idle time, blocked time, and average work queue reports generated by the simulation. This allowed AGS to concentrate its resources on improving a smaller area with the greatest potential impact on overall system performance.
Experimental trials conducted on the simulation model were able to determine the fewest number of fixtures required to satisfy minimum throughput specifications, lowering effective capital investment for the new assembly line.
Further experimental trials concluded that changes in cycle time variability, rework quantity, machine downtime, and material shortage have statistically significant impact on throughput of varying degrees. With this knowledge of the assembly line’s characteristics, AGS could predict the effects of unforeseen events and make informed decisions dynamically.
The flexible nature of this simulation tool allowed AGS to easily examine alternative process flows and workstations arrangements for future growth. Furthermore, it could also be adapted to simulate other assembly line systems in the plant, making the simulation a cost-effective planning tool for the long-term.