Analysis demonstrates reduced investment costs by 30% and shorter timelines in industrial processes, suggesting improved risk assessment for investors.
Investors demand risk minimization references or at least demonstrator plant operations that are scaled down by a factor of about 25 times less than the manufacturing scale. This causes increased investments of about 30% and a time delay of about 3–5 years. Nevertheless, modern process simulation studies based on experimental model parameter determination at a reduced laboratory scale and process model validation by mini-plant operations with risk assessment studies based on a statistically sound quality by design (QbD) approach should be able to substitute existing methods with less effort in terms of time and cost. This approach is used for a risk assessment study based on an industrial-scale simulated moving bed chromatography separation of m- and p-isomers, including potential enrichment cycles of the simulated moving bed’s (SMB) internal desorbent and the corresponding raffinate and extract distillation columns, and well-documented experimental literature data. The results quantify potential risks within probability ranges for investor decisions quite sufficiently. The benefits of ROI across various annual capacity scales and product magnitudes are evident through reductions of about 30% regarding investment and 3–8 years in terms of time to market, which should motivate the desire to implement these innovative methods more strategically in industrial daily work instead of piloting demonstrator-scale construction and operation.
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Lütge et al. (2025) studied this question.
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