Enhance blow-molding quality with a digital twin using sensor fusion to predict defects in real-time, improving process control and reducing waste. Ideal for high-throughput environments, this solution leverages polarized light and IR cameras for data-driven insights.
This innovative solution uses digital twins and sensor fusion to enhance the quality of blow-molded plastic products by predicting defects in real-time. By integrating data from polarized light cameras and infrared (IR) cameras, this technology provides a comprehensive view of the manufacturing process, allowing operators to make informed adjustments to prevent defects and reduce waste. This approach is particularly beneficial in high-throughput environments, such as those producing 6000 bottles per hour.
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The technology is currently at TRL 4, indicating it has been validated in a laboratory environment. The next steps involve further development of the vision system and integration into real-world manufacturing settings to enhance the accuracy and applicability of the defect prediction models.
The Ohio State University is a comprehensive public land‑grant research university in Columbus, serving one of the nation’s largest student populations and a broad research enterprise. Industry partners engage through an integrated academic medical center for clinical translation, a campus‑adjacent innovation district for co‑located projects, and a statewide extension network that pilots solutions across Ohio. Corporate engagement provides a single front door for sponsored research, talent pipelines, and streamlined agreements. Research is supported by competitive federal funding from agencies such as NIH, NSF, DOE, USDA, DoD, and NASA. A dedicated technology transfer office and venture support help protect IP, license technologies, and launch startups.