Scale factors have been important not just at the level of the individual plant and its optimal output, compared to the size of the available market. As the industry shifted to petroleum feedstocks in the interwar years and mastered the problems of large-scale, continuous process operations, the optimal size of plant often grew to exceed the market requirements of even the largest of western European countries.
But it should now be apparent that it is a serious mistake to visualize the competitive process as if it were entirely a matter of squeezing out, as rapidly as possible, the cost reductions offered by such existing learning curves.
In fact, larger plants typically incorporate a number of technological improvements, based upon the wealth of experience and insight into better plant design, that could be accumulated only through prolonged exposure to the problems involved in the operation of somewhat smaller plants.
Such production is not a matter of simply scaling up the tubes and retorts in which a new product was originally developed.
August 2, MIT researchers use a new machine learning technique to rapidly evaluate new transition metal compounds to identify those that can perform specialized functions.
The overwhelming emphasis that has been placed, in recent years, on moving down the learning curve of an existing, unchanging plant [category 2 ], fails to take account of the steady flow of incremental improvements in plant design [category 3 ] that, at some point, makes it economically attractive to introduce new facilities incorporating these later improvements.
August 8, A giant in the field of food science and engineering, Karel developed important innovations in food packaging as well as food systems for long-term space travel.