Data Validation : SQL Meets Tableau
Data Validation : SQL Meets Tableau
Embedded Files
This project involved using one of my interactive Tableau dashboards - 'Workforce Dynamics Dashboard' - to perform data validation. Using SQL, I performed data integrity checks, validated attrition rates, employee counts, and demographic trends, and ensured accurate alignment between raw datasets and visualization outputs.
Project Name: Optimizing energy consumption in directed energy deposition-based hybrid additive manufacturing: an integrated modeling and experimental approach.
NSF Project
Summary: This project explores ways to reduce energy consumption in Directed Energy Deposition (DED)-based Hybrid Additive Manufacturing (HAM), a process combining additive manufacturing with CNC machining. Using Inconel 718, a high-performance nickel-based superalloy, I developed and validated an energy consumption model to analyze the effects of process parameters such as laser power, scanning speed, and feed rate.
Key Highlights:
Process Optimization: By analyzing the influence of scanning speed, laser power, and feed rate on specific energy consumption (SEC), I identified optimal parameter settings that can reduce energy usage in DED-based HAM processes.
Statistical Methods: The study employed Lenth’s method and regression analysis to quantify the impact of each parameter, revealing that laser power is the most significant factor influencing energy consumption, followed by scanning speed and feed rate.
Practical Impact: The findings emphasize that higher scanning speeds combined with lower laser power and feed rates lead to energy-efficient operations. This insight contributes to sustainable manufacturing by minimizing energy requirements, aligning with the goals of Industry 4.0 and Industry 5.0 for eco-friendly production.
This research advances our understanding of energy-efficient strategies in hybrid additive manufacturing, providing a foundation for future studies in sustainable manufacturing practices.
Our Setup
Electricity Consumption during Subtractive Manufacturing VS Additive Manufacturing
Project Name: Innovative Product Design with Fused Deposition Modeling (FDM).
Summary: This project explored the potential of Fused Deposition Modeling (FDM) to create optimized, lightweight, and structurally sound components for engineering applications. Using advanced design software, including Fusion 360 and Autodesk Netfabb, I developed two innovative products—a bionic aircraft bracket and a load-bearing bridge—that balance material efficiency with durability.
Bionic Aircraft Bracket
Inspiration: Modeled after a butterfly wing to achieve a lightweight, structurally efficient design for aerospace use.
Process:
Created a bio-inspired design in Fusion 360 to reduce material use while maintaining strength.
Used Autodesk Netfabb for STL file repair, ensuring precision for FDM printing.
Key Insight: Demonstrates the potential of bio-inspired design in aerospace, allowing significant weight reduction without compromising performance.
Bionic Aircraft Bracket. Material: CFRP
Multi-view of the Bionic Aircraft Bracket. Created in Fusion 360
STL file repair. Created in Netfabb
Multi-view of the Load Bearing Bridge. Created in Fusion 360
Load Bearing Bridge
Inspiration: Designed with an arc-based honeycomb structure, inspired by Roman arch bridges, to maximize load-bearing capacity.
Process:
Developed and optimized in Fusion 360; refined file in Netfabb to prepare for FDM printing.
Conducted simulation tests in Fusion 360, followed by lab testing, confirming a high load-bearing-to-weight ratio.
Key Insight: Highlights how additive manufacturing can create efficient, high-strength structural designs, applicable to civil engineering and research.
Load Bearing Bridge. Material: ABS
STL file repair. Created in Netfabb
Project Name: Efficient Manufacturing Design with Digital and Generative Tools.
Summary: This project aimed to optimize the design and manufacturing process of a mechanical hinge by integrating digital tools and generative design within Computer Integrated Manufacturing (CIM). The goal was to investigate methods to enhance the material stiffness, tool life, and machining efficiency while reducing overall manufacturing costs.
Objective: The project focused on maximizing stiffness with minimal material usage, generating efficient tool paths, and evaluating costs and manufacturing efficiency.
Process and Tools:
CAD and CAM Modeling: Using Fusion 360 for CAD modeling and Computer-Aided Process Planning (CAPP), I designed a 3D model of a mechanical hinge, optimized for production in both 3-axis and 5-axis CNC setups.
Generative Design: Leveraged generative design to explore alternative geometries and configurations, guided by AI-driven algorithms to achieve the optimal structural layout for stiffness and load-bearing capacity.
Material and Process Analysis: Investigated multiple materials, including Aluminum ALSi10Mg and Inconel 718, and compared machining approaches (3-axis vs. 5-axis milling and die casting) to determine the best method for cost efficiency and structural integrity.
Outcome: The project identified a cost-effective design and machining plan, demonstrating how digital manufacturing and generative tools can lead to efficient and sustainable production processes. By analyzing tool life, machining time, and material removal rate (MRR), the study provided actionable insights for reducing waste and enhancing productivity in mechanical manufacturing.
This project showcases the potential of digital manufacturing techniques to improve production quality and cost-efficiency, aligning with the goals of sustainable and integrated manufacturing practices.
3 Axis Milling Process
Page updated
Google Sites
Report abuse