Final Design

Description:

The final design of this project takes into consideration the strength-to-weight ratio, cost, manufacturability, and ease of installation of this component. The flange attaches to the T250 engine while the base mounts on sliding rails. In combination with another tool, this component slides on the rails, supporting the weight of the engine and splitting it apart.

The final design weighs 552.17 lbs and has a minimum factor of safety of 5.22 with the applied load of 4500N. This results in a normalized strength-to-weight ratio difference of 4.35

Optimization Design Procession

Evaluation of the current tool

The tool must be at a weight lower than the current, there is no specific target value given by the sponsor, but the team aims for a design much less than the current design weight of 725 pounds. It must be able to support 4500N (1011.64 lbs) which is located 16.5 inches vertically and 72 inches horizontally from the center of the flange with a safety factor between 2 to 3 from yield failure.

Based on the given loading conditions, the static structural simulation of the current tool shows that the maximum stress of the tool is 145.038 kpsi, which nets a safety factor of 0.249. However as the current tool has been used frequently to support the expected load, it is expected that the actual safety factor is higher than predicted, possibly due to oversimplification of the given loading conditions.

In order to move forward, we have chosen to normalize the safety factors of the optimized designs to the safety factor of the current tool. This allows us to compare the performance of future designs with the current design without concern of the exact accuracy of the current tool’s safety factor. For normalization purposes, the load used for static simulations for this point onward is 4500 N which nets a safety factor of 2.5 for the current tool.

Design Optimization Workflow

This flowchart serves as a visual representation of the design optimization process. It must ensure that the component has an acceptable factor of safety while optimizing the strength-to-weight ratio by making alterations to geometry and material. This acts as a guideline for making changes to geometry and material selections. In this process, topology optimization is heavily used as it indicates excess material on a component given the goal of attaining performance, in our case it would be supporting the given load. This method aids with design changes for geometry. A visual representation of how the flowchart works can be seen below.

Selection Criteria

To aid in a comprehensive way in which to explain selection criteria to our sponsors, we decided to implement a Pugh Matrix. We created a spreadsheet that has each design depicted and numbered, then apply each considered material to each design as a letter, creating a pool of number letter pairings. Each pairing has unique mechanical properties: weight, factor of safety for max Von Mises Stress, normalized strength to weight ratio difference versus the current design, etc. These values were computed from FEA analysis and software modeling. Also, each pairing has unique business-related properties: manufacturability, ease of install, and cost. These were assigned a score versus the baseline business-related properties of the current tool design, where a positive number demonstrates an improvement in a property, a zero demonstrates no deviation from the current design, and a negative number demonstrates a regression in that category. These concerns are scaled by a multiplier which indicates magnitude of concern form the sponsor. Manufacturability receives an x1, cost receives an x3, and ease of install receives an x5. These scaled values are summed into a total Pugh Sum, which can be used to determine the overall feasibility of each design from a business/use-case stand point.

The Pugh scores and normalized S-W ratios were them compiled and visualized to show the distribution of performance of the pool of designs compared to the current tool located on the origin.

By processing the data, we found a group of potential designs that seem to be superior to the original design. The designs shown in this figure have normalized strength-to-weight ratio exceeds that of the current design, and offers a positive Pugh Sum, indicating that these designs offer a better use case and more beneficial economic costs. From this figure, we conclude that the three most optimal designs in terms of strength-to-weight ratio and Pugh sum are 5b, 5c, 5d. Indicating that the geometry of design 5 is the most optimal out of the collection and the materials A36 steel, 316 stainless steel, and 6061 aluminum should be used for this geometry.

Below is the completed Pugh matrix with all of the proposed optimized designs