A Control Algorithm Designed to Maximize the Long-Term Efficiency for any Value Adding Process – Medical or Otherwise￼
Tech ID: W-22-021
In many settings across many industries, process performance is often only considered in terms of maximizing throughput over a given period. The primary consideration in creation of the output product tends to be functional workpieces that meet short term quality expectations. This approach neglects the consideration of long-term product integrity. In other words, understanding how fresh and viable your process inputs are can directly relate to the freshness and viability of your process output, and more specifically, for how long a duration and to what level the final product retains these quality characteristics. The relationships that govern this decision-making are typically not trivial. Often-times processes can be presented with alternatives for immediate usage as inputs. Depending on the application, understanding the correct mix of process inputs (all of that / none of this, all of this / none of that, some of each, etc.) can dictate the optimized window of usefulness for the final product, the profitability of the organization, and even the safety of the consumer.
Description of Invention
In the course of researching non-pharmacological mitigation strategies for COVID-19, innovators at Western University have formulated a control algorithm designed to maximize the long-term efficiency for any value adding process – medical or otherwise. Characteristic inputs to the process are that of workpieces with varying remaining useful life. Characteristic outputs to the process are that of workpieces with desirably optimized remaining useful life in the aggregate. Typical processes might include a rapidly varying queue, operating near its useful maximum for the input, and on its output workpieces that have an attribute presenting itself as rapidly changing post process.
Benefits – Medical & non-Medical
- Consumer or societal safety
- Improved contact tracing (reductions in illness and death)
- Reduced spoilage
- Improved long-term Quality (performance, reliability, durability, conformance, aesthetic, safety)
- Competitive advantage (Improved product robustness in the aggregate)
- Inventory management optimization
- Reduction in overproduction
- Improved forecasting
- Reduced product returns
- Smaller more targeted recalls in the event of quality spills
(Please enquire regarding your application)
- Integration to PCR for improved contact tracing for COVID-19 and other SARS illnesses
- Integration to PCR robotics for improved contact tracing for COVID-19 and other SARS illnesses
- Integration to diagnostic tools for improved contact tracing for measles, tuberculosis, and HIV
- Integration to freezer equipment for medical cold chain optimization – last step
- Integration to freezer equipment for medical cold chain optimization – vaccine
- RFID Cold Chain management across all industries – better Distribution Centre decisions
- Food processing – Better shelf life in the aggregate
- Brewing and distilling – Better shelf life in the aggregate
- Chemical Engineering – innumerous useful life and non-toxic life applications
Python model for COVID-19 infection mitigation is copyright protected
- Commercial partner
- Development partner
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