Additive Manufacturing Feasibility Assessment Framework
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Solution Overview
Problem
Current additive manufacturing processes face limitations in materials, size, surface finish, accuracy, production speed, and high costs, making it challenging to universally apply them across all engineering designs, necessitating a framework to assess the technical feasibility of additive manufacturing for complex shapes.
Innovation Solution
A system and method that includes a processor, memory, and modules for receiving user inputs, preliminary assessment, weightage assignment, detailed assessment using a decision matrix, and recommending suitable additive manufacturing processes based on predefined design rules, allowing for customizable attributes and reduced subjectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional additive manufacturing processes are used for production of finished parts, then complex shapes can be produced with minimum material, but limitations exist in terms of materials, size, surface finish, accuracy, production speed and high costs
Solution Approach 1:
The patent segments the assessment process into multiple distinct modules: preliminary assessment module, weightage assigning module, detailed assessment module, and recommendation module. Each module handles specific aspects of feasibility evaluation, allowing comprehensive analysis of complex manufacturing decisions while addressing multiple constraints simultaneously
Solution Approach 2:
The system evaluates and compares multiple additive manufacturing processes by changing parameters such as material type, build size, surface finish requirements, and production speed. The framework allows users to adjust these parameters to find the optimal process that balances complex shape capability with manufacturing precision requirements
2Ease of manufacture
If traditional additive manufacturing processes are used, then complex shapes can be produced, but production speed is limited
Solution Approach 1:
The assessment framework is designed to be dynamic and adaptable, allowing users to adjust weights and parameters based on specific production requirements. The system can dynamically evaluate different scenarios to identify processes that optimize both complex shape production and production speed according to user priorities
3Ease of manufacture
If traditional additive manufacturing processes are used, then complex shapes can be produced, but high machine and material costs are incurred
Solution Approach 1:
The system enables users to independently assess and determine the feasibility of additive manufacturing for their specific designs by providing a comprehensive evaluation framework. Users can input their own design parameters and receive tailored recommendations, allowing them to make informed decisions about cost-effectiveness without requiring external consulting services
4Reliability
If a comprehensive assessment framework is implemented, then suitable additive manufacturing processes can be selected, but assessment time and complexity increase
Solution Approach 1:
The framework begins with a preliminary assessment module that quickly evaluates basic feasibility before proceeding to detailed analysis. This preliminary action filters out clearly unsuitable cases early, saving time while maintaining reliability by only conducting comprehensive assessments when initially promising
Solution Approach 2:
The system allows users to perform partial assessments by selecting only the most relevant attributes for their specific needs, rather than requiring complete evaluation of all possible parameters. This reduces assessment time while maintaining sufficient reliability for the particular application
Data Source
AI summary
A framework for assessing technical feasibility of additive manufacturing of an engineering design. This framework needs to be based on preliminary identification of key parameters that influence the decision making process. The parameters may also be customized for a particular application. Each of these parameters can be assigned weightage either relative or arrived at by paired comparison using a pre-determined minimum point method. Each of the attributes are then assigned scores which are then multiplied by the weightages assigned. The summation of all such scores on a weighted average basis indicates the potential for 3D printing of that part or assembly. It offers to select the right part to leverage the benefit of additive manufacturing. It narrows down on the ideal manufacturing process for the qualified parts and proposes to reduce subjectivity by using paired comparison of attributes. It also provides a faster assessment of technical aspects of the design.


