Determining optimal laser-beam cutting equipment investment through a robust optimization modeling approach

Area of Science:

• Operations Research
• Manufacturing Engineering
• Industrial Engineering

Background:

• Acquiring advanced manufacturing technologies (AMT) involves significant investment and risk.
• Optimizing equipment investment and production planning is crucial for profitability.

Purpose of the Study:

• To develop a robust model for optimizing equipment investment decisions in advanced manufacturing.
• To determine an optimal production plan considering technical constraints and demand uncertainty.

Main Methods:

• A linear investment model was developed using historical demand and laser cutting process parameters.
• The model was transformed into a robust optimization model to account for demand uncertainty.
• An optimal production plan was determined assuming normal distribution of demand.

Main Results:

• The robust optimization model effectively addresses demand uncertainty in investment decisions.
• A case study on Laser-Beam Cutting (LBC) services validated the model's effectiveness and solution robustness.
• The optimal robust solution demonstrated a potential increase in company profits by 6.4%.

Conclusions:

• The proposed robust model provides a reliable framework for investment and production planning in advanced manufacturing.
• Integrating demand uncertainty significantly improves the decision-making process for AMT acquisition.
• The model offers a practical approach to enhance profitability in laser cutting services.