A world leader in the manufacturing of automobiles with expertise in body-in-white closures and exhaust systems hired PMI to analyze production with a concentration on skid and trolley optimization. The goal was to test the potential of the facility to achieve throughput goals while resolving operational issues including random sequencing, WIP control, and changeovers. With a formal simulation methodology, PMI pinpointed critical bottlenecks, chiefly at paint intake—and advised ideal levels of resources such as 70–90 skids, 358 trolleys, 3 forklifts, and 4 tow-trucks. The outcome was a validated flexible model for production that enables better decision-making and guarantees operational efficiency under different production conditions.
The company is a worldwide-recognized automotive industry leader. It is renowned for its know-how in the production of body-in-white closures, exhaust systems, and equipment for manufacturing closures. The company provides a complete, turn-key production system that is integrated in a full way and supports the customers from the earliest product design and tooling stages to the full-scale mass production stages. Their Full Vertical Approach provides for smooth coordination throughout all the manufacturing stages, and they are able to compress vehicle development lead times without sacrificing quality. By integrating innovative engineering capability with efficient production, the client has emerged as a go-to partner for many of the globe's leading automobile producers.
The major objectives of the simulation exercise were to:
Though possessing an integrated production system, the client was experiencing some operational issues that were affecting the consistency of throughput and efficiency.
In response to the client's intricate production issues, PMI embarked on a formal six-step simulation-driven methodology with the aim of providing actionable information and maximizing resource efficiency.
PMI initially ensured that client-supplied data was correct and carried out theoretical computations to calculate machine utilization, capacity throughputs, and batch performance.
The team examined rules of production, limitations, and patterns of product flow to conceptualize a versatile modeling system that would respond to changes in sequencing of products and configurations of systems.
PMI constructed a digital twin of the manufacturing line with the aid of simulation software typical in the industry. The model was cross-checked against static analysis to verify its behavior represented true plant operations.
Various scenarios were tested, including changes in skid and trolley counts, MHE deployment, and line performance under breakdown and recovery conditions.
Bottlenecks and resource levels for maximum output were tabulated through findings.
The project involved close coordination between PMI’s project team (1 Project Manager, 1 Engineer) and the client’s team (2 Project Coordinators), ensuring aligned objectives and smooth execution.
During the first phase, PMI performed a comprehensive static analysis to comprehend the client's system baseline capabilities. This included analyzing machine utilization considering changeovers, downtimes, and batch-building logic as per the model mix required.
Subassembly operations were paid special attention to, where batch size and setup time had a considerable impact on throughput. A dashboard was developed to graphically represent and analyze how batch formation affected overall production flow.
In conceptualization, PMI plotted all key production rules, WIP limits, and product flow situations. This phase enabled a flexible simulation model structure that could accommodate real-world dynamics like random sequencing, unexpected failures, and changing demand. The conceptual model ensured that the model would give not only information for the present configuration, but also a basis for ongoing improvement.
After the conceptual framework was complete, PMI created a detailed simulation model of the client's manufacturing system using sophisticated simulation software. This digital twin accurately mirrored line configurations, resource behavior, product flow rules, and downtime logic. The model was validated against static analysis outputs to ensure consistency with theoretical expectations and real-world data.
PMI subsequently simulated various what-if situations, with varied key parameters like the number of skids and trolleys, tow-truck travel times, and equipment availability. The simulation facilitated dynamic testing of the bottlenecks, such as the influence of breakdowns and the effect of recovery time.
It further facilitated the study of random product sequence and changeover effect. Through iterative testing, PMI determined performance enhancement opportunities without compromising on production targets.
The simulation showed that although the existing facility would be able to meet throughput requirements, some changes were needed in order to achieve maximum efficiency. Paint entry was found to be the main bottleneck because of its low capacity and high utilization. Secondly, an involuntary delay on the mainline, due to the long movement time of two trucks, was found to be a secondary bottleneck.
To facilitate easy recovery during breakdowns and WIP balance, PMI suggested keeping 70–90 skids and 358 trolleys. The study also concluded that at least 3 forklifts and 4 tow trucks were needed to facilitate effective material flow.
The simulation model also offered useful visualizations like time series plots, time-in-state diagrams, and utilization tables that were useful in validating suggestions and measuring improvements. With these findings, the client was able to make informed, data-supported decisions on equipment investments and working planning.
PMI helped the client make well-informed, data-driven choices on skid and trolley optimization, equipment deployment, and process enhancement through this comprehensive simulation study. The model not only validated that the current facility would be able to achieve throughput goals but also made explicit recommendations to overcome bottlenecks and minimize delays. Moreover, the versatile digital model is a valuable planning tool for future what-if scenarios, layout adjustments, or product mix variations, boosting the client's responsiveness and resilience in a changing manufacturing world.
Simulation-based strategy by PMI gave the client an end-to-end view of their manufacturing system's strength and limitations. By determining major bottlenecks and optimizing critical resources, the research yielded actionable insights that enhanced efficiency and facilitated strategic decision-making. This partnership demonstrates the capability of digital modeling and engineering know-how to drive operational excellence in intricate automotive production settings.
