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Metal AM Utilization

Manufacturing

Developed a Python-based buffer size simulation to optimize throughput and utilization of a Nikon SLM printer. Improved projected utilization from ~20% to ~50%.

PythonSimulationManufacturingOptimizationMetal 3D Printing
Metal AM Utilization

Project Overview

Working with Physical Sciences Inc., I developed a comprehensive simulation system to optimize the utilization of their high-value Nikon SLM metal 3D printer. The printer was experiencing significant downtime between jobs due to inefficient workflow management and buffer sizing issues.

Approach & Solution

I modeled the entire post-processing machine line (SLM, band saw, mill) as unreliable with buffers and simulated various workflows to determine ideal buffer sizes. This Python-based simulation accounted for machine reliability, processing time variations, and job scheduling constraints.

Outcome & Results

Through careful analysis and optimization, the simulation recommended buffer configurations and job scheduling strategies that improved projected utilization from approximately 20% to 50%. I also delivered standard operating procedures (SOPs), live spreadsheets, and simulation tools for PSI implementation.

Project Report

This comprehensive report details the optimization of a Nikon SLM metal 3D printer's utilization through simulation and workflow improvements. The project achieved a significant increase in operational efficiency.

Project Details

Timeline

Fall 2024

Role

Mechanical Engineer

Client/Organization

Physical Sciences Inc.

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