Statistics & Machine Learning in Chemical Processes | AIChE

Statistics & Machine Learning in Chemical Processes


The desire and need for a team to rapidly develop and scale-up a new and novel chemical process can be an invigorating and rewarding experience if done well and comprehensively or be a source of grief and disappointment when key elements of the technology development are missed or fail to deliver at desired levels of product performance & consistency or production rate. This talk will summarize some of the most salient features of successful rapid process developments & scale-ups and major lessons-learned over three decades of personal experience. An over-arching theme of identifying early-on the major Critical To Quality (CTQ) specifications for end-product and product throughput rates is critical to success. The need to identify the top few technology-related critical issues and assembling cross-functional problem-solving teams to develop options and solutions using a variety of techniques and resources will be discussed.


This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.


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