Many chemical engineers in industrial settings spend their time designing processes that make the best use of time, money, and raw materials. Frequently this involves scaling up a process, whether that means taking a lab-scale process and making it work effectively on an industrial scale, or increasing current production volume at an existing facility by expanding the facility or building a larger facility.
There are, however, cases where scaling up might not be as suitable as numbering up. In other words, instead of simply relying on creating a single-unit, large-scale process to boost production, sometimes it is advantageous to adopt a modular approach where the number of times a process is carried out is increased in order to increase production.
But how do the economics of numbering up work? That’s what our researchers wanted to know, and it’s the topic they investigate in “The Scaling Economics of Small Unit Operations,” an open-access article in the Journal of Advanced Manufacturing and Processing (JAMP).
A rule of thumb for the economics of numbering up?
In situations where numbering up appears potentially advantageous, is it possible to provide a rough rule-of-thumb equation to describe the economics of numbering up? The authors of this article adapted the two-thirds-power rule to create a new functional form that applies to numbering up. The new form helps find economic advantages beyond manufacturing learning, which was the subject of a previous article (open access).
Could your work benefit from this research?
Chemical engineers looking to revamp a process could find this article useful. In particular, chemical engineers looking to design a process involving the conversion of geographically distributed sources of renewable or waste carbon into fuels or chemicals could find this especially beneficial.
What inspired this research?
While attending a workshop on modular manufacturing in Europe a couple years ago, one of the researchers was struck by the fact that multiple discussions focused on the advantages of numbering up even though a clear understanding of the cost of the modules was lacking.
Who’s behind the research?
In the writing of this blog post, we spoke to one of the authors of the JAMP article, Robert S. Weber, who is a scientist at the Pacific Northwest National Laboratory (PNNL). Prior to joining PNNL, Weber’s experience included working in academia (he taught at the University of Delaware and at Yale University) and also included working as a consultant and at a renewable fuels startup. In discussing his work at PNNL, Weber said the lab and its work appeal because of the broad mission, which includes research in both basic science and applied science as well as a focus on applying science in support of U.S. industry.
To learn more about this topic, see the open-access article featured in this post, and also check out the Journal of Advanced Manufacturing and Processing for articles on related topics. You may also want to learn more about RAPID, a group of industry-leading organizations working on more efficient processes and distributed industrial modularization.