A construction equipment manufacturer came to us with a problem. They were designing the layout of a new plant and needed to estimate their machine spacing requirements. The machines in transit were too large and costly to move after installation, so management needed to ensure their plant layout reserved enough space for staging work in-process (WIP) inventory. They knew the characteristics of the system, but needed help translating that information into reliable in-process inventory estimates to inform machine placement for their new facility. The machines were already in transit, so they needed answers quickly!
The manufacturer also sought answers to several secondary questions about their proposed system, including:
- Will the proposed system meet annual production targets?
- If so, when? With what margin of safety?
- How fast should raw materials be released for production?
- What system configurations minimize in-process inventory?
- What operating conditions have the greatest impact on system performance?
- How should parts be batched and routed through the system?
SIMCON Solution Strategy
After working with the client to define their challenges and desired outcomes, we proposed developing a simulation model of the future production system. Our engineering team went to work collecting prerequisite data and developing a 3D model to simulate their baseline configuration. Some of the features captured by the model include:
- Projected demand and annual production targets
- Material handling policies (part batching, transport, and routing logic)
- Machine properties for turning, milling, shaping, and washing operations
- Part-specific loading, unloading, and processing times
- Sequence-dependent changeover procedures, setup and teardown times
- Operator staffing and scheduling requirements
The model also tracked key performance metrics specific to the client’s unique challenges, such as:
- In-process inventory by machine
- Staging clearance time (time all raw materials released into production)
- Completion time and margin of safety
- Utilizations of operators, vehicles, machines, and equipment
- Holding costs for in-process inventory
We then began experimenting with alternative system configurations and operating policies to determine the impact on system performance. Attributes found to have the greatest effects were part batch sizes, release rates, and routing sequences. We utilized the optimization module within the simulation software to minimize the client’s in-process inventory and holding costs subject to meeting annual demand. Lastly, we documented the results and submitted a revised production plan that optimized system performance.
The Simulation Video:
Results and Key Takeaways
Simulation modeling and analysis was able to generate a wealth of knowledge about the client’s future manufacturing system. Simulations of the baseline configuration were able to illustrate exactly how their facility would operate over time and provide reliable quantitative data to support all of their design decisions. Some key takeaways from simulating the client’s original production plan include:
- Estimates of in-process inventory (and in turn spacing requirements) at each machine
- Projected annual order fulfillment at 70% of year, leaving safety margin of 3 months
- Identified material release rates, batch sizes, and routing sequences as key contributors to total in-process inventory
More importantly, the simulation model allowed us to experiment with alternative system configurations and optimize performance specific to their objectives. Changes to the client’s part routings, material release rates, and batch sizes drastically improved system performance:
- Optimizing batch sizes reduced in-process inventories by 55% in the baseline system configuration
- Rerouting select parts, slowing material release, and optimal batching slashed WIP by 85%
- Optimal configuration reduced estimated annual holding costs by over $600,000
The simulation model allowed the client to visualize their manufacturing system in action, track material flow and accumulation across the production line, monitor their system performance over time, test alternative configurations and operating policies, and optimize performance – all before installing their first machine!
Give us a call at 512-693-8280 or email us at firstname.lastname@example.org. We’d love to learn more about your manufacturing process challenges.