Advanced simulation techniques have gained considerable attention from the industry to optimize existing manufacturing processes i.e., forging with low capital expenditure to achieve net-zero targets and reduce operating expenses. In this study, a hybrid advanced simulation approach was investigated to optimize the large-scale forging process. First, a discrete event simulation was conducted as part of the Lean Six Sigma process optimization to understand the manufacturing process and identify bottlenecks. In this example, the heat treatment process was identified as a high bottleneck especially for forging Super Duplex F55. Then a parametric and randomised study was conducted to optimize the heat treatment process where the inputs were initial temperature of the workpiece, heat treatment temperature, heating rate and soaking time at the heat treatment temperature; outputs were residual stress build-up in a specific location in the workpiece as well as the energy input to the workpiece through heating. The aim of the study is to minimise the energy input while maintaining other material and mechanical properties the same hence reducing energy and/or time consumed during the heat treatment process as well as reducing carbon emissions. The finite element model was validated by conducting controlled experiments and empirical analysis. The results showed good correlation between controlled experiments and simulated results. Also, significant gains on heat treatment time were achieved by optimizing the soaking time using the energy input of the simulation. It was observed that initial and final temperatures were the main drivers for the energy consumed whereas for residual stress build-up in the part, the most influential parameter was the exit temperature. It must be noted that the workpieces were forged before heat treatment which is ignored in the simulations due to other constraints. The effects of forging parameters on residual stress will be taken into consideration in the future work.