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Integrated design of emulsified cosmetic products: A review
Chemical Engineering Research and Design ( IF 3.7 ) Pub Date : 2020-07-24 , DOI: 10.1016/j.cherd.2020.07.014
Fernando Calvo , Jorge M. Gómez , Luis Ricardez-Sandoval , Oscar Alvarez

Chemical product design has progressively become a more critical issue since the chemical industry is rapidly moving toward the production of consumer-oriented products at low cost. This new paradigm has boosted research and developments in this emerging field. However, designing a new chemical product through an integrated approach is still challenging. In particular, the design of emulsified cosmetic products commonly involves the implementation of heuristics during the formulation of the product, highlighting the need of implementing integrated strategies in this field. This study reviews the current status of the integrated design of emulsified cosmetic products, including but not limited to, property modeling, manufacturing methods, the key variables affecting final product quality, and the current challenges in this field. This review highlights the need to perform close integration between market parameters, engineering variables, and business models, on the one hand, and systematic and standardized approaches to translate consumer needs into technical specifications on the other. Also, this study presents the requirement for better accuracy of predictive models for emulsified product's physical properties for the successful integrated design of cosmetic emulsions, considering different modeling frameworks such as population balance models that have the potential to improve the models’ prediction capabilities.



中文翻译:

乳化化妆品的整体设计:综述

由于化学工业正迅速转向以低成本生产面向消费者的产品,因此化学产品设计已逐渐成为一个更为关键的问题。这种新的范例促进了这一新兴领域的研究与开发。但是,通过集成方法设计新的化学产品仍然具有挑战性。尤其是,乳化化妆品的设计通常涉及在产品配制过程中实施试探法,这凸显了在该领域实施整合策略的必要性。这项研究回顾了乳化化妆品产品集成设计的现状,包括但不限于性能模型,制造方法,影响最终产品质量的关键变量以及该领域的当前挑战。这篇评论强调一方面需要在市场参数,工程变量和商业模型之间进行紧密集成,另一方面需要系统化和标准化的方法将消费者需求转化为技术规范。此外,本研究还提出了对化妆品乳液成功集成设计的乳化产品物理特性预测模型要有更高准确性的要求,同时考虑了诸如人口平衡模型等可能具有提高模型预测能力的潜力的不同建模框架。

更新日期:2020-07-24
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