Packline Case Study

Slide 1: 

Background A demonstration model of a packaging line was built to focus on a classical use of simulation. Model Purpose To test the effect of bin/buffer capacity and reliability on production throughput. Driving question: Which improvement opportunity should be pursued? Key model inputs Production rate for each machine Fill ratios; i.e., bags per carton, cartons per case Time Between Failures for each machine Time To Repair for each machine Bag Buffer Capacity; i.e., maximum allowed bags Experiment Factor Bags Buffer Capacities Time To Repair System Performance Measure Production Per Hour View the Video for an in-depth discussion. Case Study: Packing Line Experiment – Buffer Capacity versus Reliability CRITICAL MEASUREMENT: Production Per Hour Experimental factor: Time to Repair for each machine * Experimental factor: Capacity of buffer key issues summary experiment results strategic assessment

Slide 2: 

Increasing the Buffer capacity, or the machine reliabilities, can increase production throughput. These increases have a cost. When machines upstream of the bag Buffer fail, bags in the Buffer are depleted. When machines downstream of the bag Buffer fail, bags accumulate until the maximum size of the Buffer. Case Study: Packing Line Experiment – Buffer Capacity versus Reliability Machines upstream of the buffer Machines Downstream of the buffer key issues summary strategic assessment experiment results

Slide 3: 

Case Study: Packing Line Experiment – Buffer Capacity versus Reliability The Experiment A Designed experiment was run with the model to test the effect on throughput of different levels of Buffer size and Time to Repair. Summarizing the Results The results show that different buffer sizes do not matter much when the reliability factor is 1. As the reliability factor increases (longer time to repair), the buffer size matters more and more. But there is a diminishing return with greater buffer capacity. In the worst reliability case (the bottom two plots), buffer capacities at 500 bags or greater yield the same throughput. At low levels of Time to Repair (high reliability), increased Buffer Capacities have no effect on production throughput. At medium levels of Time to Repair (medium reliability), increased Buffer Capacities has a minimal effect, up to 500 bags. Larger capacity yields no additional benefit. At high levels of Time to Repair (poor reliability), increased Buffer Capacity has a significant effect, up to 500 bags. Larger capacity yields no additional benefit. key issues summary experiment results strategic assessment

Slide 4: 

Buffer size vs process variability This model illustrates how simulation is the perfect tool for quantifying potential increases in throughput due to larger buffer (increased decoupling of starving and blocking effects) versus increased reliability. key issues summary Case Study: Packing Line Experiment – Buffer Capacity versus Reliability strategic assessment experiment results