Factory optimisation through simulation

I led this group project during my time at the University of Bristol. We investigated the possibility of optimising a factory producing scissor jacks. We chose two conflicting KPIs: production cost and delivery reliability. This choice was based on a predetermined production scenario: supplying jacks to several compact car manufacturers in France. The production consisted of several operations illustrated below:

Estimation of process duration

For each operation involved in manufacturing the scissor jack, we estimated the duration for a single operation, either by modelling the process in Fusion 360, or using videos of manufacutring processes as a reference.

Simulation in Anylogic

We simulated the factory using two discrete event simulations in Anylogic.

Simulation 1:

First, we simulated the production of jacks over the course of a day, accounting for employee absences.

Simulation 2:

Next, we simulated the delivery of jacks to customers on a weekly basis, accounting for machine downtime.

Delivery reliability vs mean daily production

We discovered that the the quantity and allocation of workers influenced both KPIs, resulting in a multi-objective optimisation problem. We observed that the delivery reliability was highly sensitive to the mean daily production of jacks and variability in the order quantity. In contrast, the variability of daily production is not a significant factor in delivery reliability.

Effect of altering allocation of workers

We performed a heuristic parameter variation experiment to quantify the effect of altering the allocation of workers on both KPIs. From this we identified a non-dominated solution. For a given value of reliability, we achieved a cost saving of approximately 0.12 EUR per jack, compared with other possible solutions for the allocation of workers.

Reflection

In hindsight, having worked in manufacturing environments for 4 years since graduating university, this project entailed a massive simplification of the manufacturing process. In reality, there are many factors which would affect cost and delivery reliability, which were simply not considered during this project:

Machine downtime
% of parts meeting tolerances
Rework
Process improvement
Training levels of operators
Material cost fluctuations