Additive manufacturing represents the combination of physical production processes and digital data. It promotes manufacturing innovation and efficiency by making digital data a physical product.
However, like any manufacturing process, additive manufacturing involves the process from an ideal CAD file to a viable product that meets quality and repeatability requirements. Success depends on the use of design in additive manufacturing to optimize material topology and solve internal stress and other deviations from ideal problems under the guidance of simulation tools.
In order to take full advantage of the benefits of AM (greater design freedom, product personalization and shorter design cycles), users need to consider more available materials and processes to help them achieve their goals. For anyone who is not an expert, keeping track of what is available on the market is a challenge. Existing AM data limits the future success of this technology.
Scattered additive data makes it difficult for manufacturers to mix and match materials and machines to create novel workflows and products, thereby setting barriers to innovation. The choice of materials and processes are intertwined and determine the design space of the product, including its cost, weight, performance, and even its impact on the environment.
The lack of material and process data also prevents the design team from confidently applying modern computer-aided engineering (CAE) methods to parts that can be additively manufactured.
In large projects, sharing important data and process insights is especially important. Valuable experience can be learned from AM tests that have been conducted, failed prototypes, or material and quality tests not shared between departments.
When AM project teams perform tasks in silos, there is a greater risk of failure and the risk of wasting materials, time and money. It will extend the time required to bring the product to market and delay the adoption of AM across the enterprise.
As AM materials and technologies are relatively new, 3D printing brings new quality challenges. Designers’ unfamiliarity with additive manufacturing materials and processes often leads to defects in the final product. Predicting and preventing these defects during the design phase requires accurate material and machine data and process simulation.
Leading additive manufacturers are benefiting from Integrated Computational Materials Engineering (ICME), an emerging approach to a unified digital process, from material development to design engineering to manufacturing. ICME ensures the use of the best combination of materials and manufacturing processes to innovate and maximize performance, thereby reducing costs and delivery time.
ICME is a method aimed at understanding the behavior of materials at multiple scales. Boeing illustrates this point very well, he coined the phrase “atoms on airplanes.”
The goal is to design and make full use of materials from chemical composition to microstructure to samples and manufactured parts. In practice, integrating these scales means integrating historically isolated disciplines to obtain the best results. This integration means that designers can predict the impact of selected materials and manufacturing processes on product performance and design optimization.
Since the end of the 20th century, ICME has been the subject of cutting-edge research because of its ability to accelerate the discovery and application of new materials. What has changed is that we now have mature modeling capabilities, accessible computing power, and a technology ecosystem working towards this common goal.
E-Xstream Engineering, a part of Hexagon’s manufacturing intelligence division, recently launched 10xICME. The industrial solution portfolio aims to leverage the potential of ICME to enable design, materials, and manufacturing professionals to collaborate virtually, using detailed proprietary material models and process definitions from 3D printer suppliers, OEMs, R&D institutions, and end users to develop products.
10xICME has recently expanded to include the Senvol database, which is a comprehensive database of AM materials and machines. The new features allow teams with on-demand access to evaluate current 3D printing market capabilities based on their new product goals.
For example, materials engineers can work with the production department to compare historical data on 3D printers with materials, processes, and suppliers that have never been used before to develop a list of alternatives. Candidate materials can then be analyzed directly in CAE tools to explore design concepts and perform basic evaluations. Thereafter, the product development team can ask the supplier to access the shortlisted proprietary material system models and machine tool paths.
With such accurate data, materials professionals can virtually explore the performance limits of “manufactured” materials and enable designs that can make the best use of additive manufacturing processes to produce better products.
This integration enables manufacturers to instantly and on-demand access to insights from virtual testing and development and subsequent physical testing, thereby continuously transferring AM knowledge from one case to another in a virtuous circle.
Integrating additive manufacturing materials and process data into product development from concept to customer will help build confidence in new technologies and stimulate bold product design.
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Link to this article：ICME system makes 3D printing operations easier
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