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Leveraging Model-Based Enterprise and MES for Superior Manufacturing Outcomes Maintaining quality is non-negotiable in high-complexity manufacturing, especially in sectors like aerospace and defense (A&D). Early identification of supplier-related issues further mitigates risks and enhances visibility across the supplychain.
In my last blog , I introduced the topic of artificial intelligence (AI) in the complex discretemanufacturing space, noting that companies need to take certain steps to prepare for AI adoption. Solving Aerospace & Defense Manufacturing Challenges with AI The production process takes too long.
Digital Continuity is Established Across As-Designed, As-Built, As-Maintained For a manufacturer to become a model-based enterprise (MBE), it must make digital continuity a priority. In discretemanufacturing, the underlying data model that defines a product is often centered around the bills of material (BOMs) that define the product.
Digital Continuity is Established Across As-Designed, As-Built, As-Maintained For a manufacturer to become a model-based enterprise (MBE), it must make digital continuity a priority. In discretemanufacturing, the underlying data model that defines a product is often centered around the bills of material (BOMs) that define the product.
It’s aimed at fixing the supplychain, and the beauty of this process is you can use reverse engineering to find the problems and also use it to reshore products they might not have access to,” Corder said. This is especially important because many of PPG clients are in the aerospace industry, which requires absolute precision.
Future-proofing manufacturing goes beyond acquiring data; manufacturers also need to evolve their business models and how they sell, acquire and distribute items to better serve their customers. Leading manufacturers are making the digital transition with help from trusted partners. That’s the future of manufacturing.
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