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Manufacturing Technology Insights | Tuesday, January 02, 2024
Mastery of the data preparation process enables individuals to optimize job preparation, reducing the likelihood of failed builds. Proficiency in selecting appropriate materials and determining optimal parameters for each part, including the design of support structures, is vital.
Fremont, CA: Industrial 3D printing demands a diverse set of skills spanning design, simulation, data preparation, application engineering, and machine operation. The intricate process involves navigating through various stages, from selecting production components to scaling and validating production. Key competencies include:
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Design and Simulation: A pivotal role in the additive manufacturing process chain, where a profound understanding of methodologies, guidelines, and the possibilities and limitations of 3D printing is essential. Designers significantly impact powder consumption, build time, and overall cost-per-part, making their expertise crucial.
Data Preparation: Mastery of the data preparation process enables individuals to optimize job preparation, reducing the likelihood of failed builds. Proficiency in selecting appropriate materials and determining optimal parameters for each part, including the design of support structures, is vital.
Materials and Processes: Recognizing the unique properties of each material is crucial, influencing their behavior in the 3D printing process. Material-specific parameter editor training is necessary to comprehend values and implications for data preparation. Understanding attributes of various materials aids in selecting the best fit for each job.
Machine Operation: Intensive training is required for safe and efficient machine operation, encompassing handling processing software, job setup, monitoring the process, and machine maintenance. Competence in these tasks is integral to successful 3D printing operations.
Distributed Production: Leveraging digital twin technology, employees can simulate production processes before embarking on serial production. This allows forecasting throughput and output based on machine park equipment, operator shifts, and maintenance procedures. Digitizing the entire process chain and connecting machines to IIoT platforms facilitates aligning production with local demands, minimizing transportation and storage costs.
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