A Decision Support Tool Utilizing Discrete Event Simulation to Select Advanced Manufacturing Technologies
Open AccessIn the global competitive landscape, large and small businesses must decrease cost, decrease lead-time, and increase factory throughput to remain competitive. These performance metrics increase when advanced manufacturing technologies (AMTs) are successfully implemented. However, the success of AMT implementation varies greatly, and predicting successful implementation is complex. As a result, significant growth and profitability on the investment of AMTs are not met. When companies decide to take the risk, unsuccessful investments are exceptionally hard-hitting for small to medium businesses that do not have the resources of a large company. Traditional evaluation methods struggle to evaluate AMTs accurately. This is because factory-wide metrics needed to assess the AMT fully are often difficult to capture or not considered entirely in the traditional evaluation methods. Discrete event simulation allows these metrics to be simulated accurately. With computational power becoming more available with time, simulation is a more approachable option for smaller companies. This research takes historical data of a confidential manufacturing firm and creates a decision support tool utilizing discrete event simulation to select AMTs based on growth and profitability factors. The simulation is created utilizing empirical distributions that capture the chaos of a real-world factory using labor reporting data which details the processes performed in the manufacturing environment. The simulation is validated, and experiments are performed to compare a known AMT effect on a real-world factory, in the case of this research, a robotic arm. The results show the tool/simulation is accurate within 5% of predicting the effect an AMT has on factory throughput, factory lead-time, and manufacturing costs. The practical application of this simulation is to be utilized by Engineering Managers as a support tool to help select and evaluate AMTs and ensure that the system-wide benefits of these technologies are accurately captured in the decision-making process. This tool/simulation can be tailored for various companies.
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