Optimising Factories and Layouts for Improved Manufacturing Outcomes

Challenge

Optimising the design of new factories or reconfiguring existing ones to maximise efficiency poses a significant challenge for designers. Facilities need to be designed right first time for long-term use. They also need to satisfy system constrains and account for competing priorities such as cost, throughput and factory footprint.

Considering all the various combinations of stations, layouts, schedules and available resources leads to a large number of possible factory configurations that need to be considered when identifying optimal designs that satisfy requirements and are robust to uncertainty.

An aerospace OEM wanted to design a new assembly line with a process flow consisting of over 400 interconnected tasks distributed across stations, which varied in task duration and resource constraints. They recognised that their traditional approach to design, using a spreadsheet with nominal parameters, was insufficient in meeting their requirements for production rate. They also needed to consider the cost and footprint constraints for the assembly line, something that couldn’t be captured with their traditional approach.

Solution

We worked with the designers to develop a fully parameterised model of the new assembly line including stations and the different task schedules within them. This model was used to perform a fully transient simulation of the production to quantify carious performance metrics, including throughput, machine utilisation rates and cost over time.

The model was used to evaluate over 4 million assembly line designs in two days. Multi-objective optimisation was also performed to identify several different optimal configurations that made different trade-offs between key performance metrics. Uncertainty in process times was injected into the model to better understand real-world performance which enabled sensitivity analysis to be conducted, identifying critical processes that lead to bottlenecks and reduced efficiency.

Impact

This approach enabled the designers to consider significantly more potential designs to understand the art of the possible and identify several more optimal configurations. This included a configuration that would increase monthly throughput by 25% for only a 3% increase in cost, enabling them to achieve their requirements and create significant cost savings over the production lifespan.

It also provided stakeholders with a deeper understanding of the impact that different processes had on the overall performance of the assembly line. More informed, evidence-based decisions could therefore be made about areas to prioritise to provide the greatest impact on efficiency.