Production plant optimization

As a new product is taken from the laboratory, through the pilot, and into the production plant, a lot of information will accumulate that helps to better understand the product and the associated production process. In general, the major characteristics are soon evident and will be exploited to optimize the production. Fine-tuning the process can only be done, however, if hitherto hidden aspects are revealed. 

The book starts with general information on fine chemicals and characteristic features of their manufacture. Tools that are used in working out new industrial processes and optimization of existing plants and processes are presented in subsequent chapters. Finally, the target of all laboratory, pilot and design activities, namely a modern production plant, is described. 

Chellemi DO, Mirusso J (2006) Optimizing soil disinfestation procedures for fresh market tomato and pepper production. Plant Dis 90 668-674. doi 10.1094/PD-90-0668... 

The production of PET is a well-known industrial process. Early patents on PET synthesis refer to the 1940s. Esterification and transesterification reactions have been investigated since the end of the 19th century. PET production plants have been optimized over the last few decades based on well-established production know-how . PET is now a commodity product with unusually rapid growth and further nearly unlimited future growth perspectives. 

The investments are estimated on the basis of long-term experience in building hydrogen production plants and on the assumption of budding 10 identical units in order to optimize the construction costs. Table 9.4 gives the plant cost estimate as a percentage of the delivered equipment costs [99]. Such an estimate does not... 

Optimizing production plants through knowledge transfer if both companies have comparable production plants and/or production processes, benchmarking on the basis of a virtual plant is suitable. This comes from combining the cost leaders in the individual process steps ... 

Production Controls The nature of the production control logic differs greatly between continuous and batch plants. A good example of production control in a continuous process is refinery optimization. From the assay of the incoming crude oil, the values of the various possible refined products, the contractual commitments to deliver certain products, the performance measures of the various units within a refinery, and the like, it is possible to determine the mix of products that optimizes the economic return from processing this crude. The solution of this problem involves many relationships and constraints and is solved with techniques such as linear programming. 

The CEA process, as it is, would be compatible with GA s secondary helium, but an analysis with a helium inlet temperature near the GA value indicates that this coupling is probably not optimal. Indeed, whereas the helium flow rate would be increased by a factor of (900-400)/(900-565) 1.50 (i.e. +50%), the overall production of the HTR production plant would not increase, since the total heat demand of the process would not change. In other terms, CEA s process efficiency would not increase. 

McKellar, M.G., et al. (2007), Optimized Flow-sheet for a Reference Commercial-scale Nuclear-driven High Temperature Electrolysis Hydrogen Production Plant, DOE Milestone Report, 14 November. 

The compressor loading in Figure 4.1 (gatefold) is determined by the central plant optimizer, which determines the percentage of the H2 production... 

Before carrying out a scale-up it is necessary to clarify which influences are likely to constrain the process. Only then is it possible to base the calculation on the correct process parameters. The objective of a scale-up (or scale-down) should be to narrow down the margin of error to +/-5 %. When carrying out optimization tests for existing systems, it is always reasonable to define the zero line in a scale-down test as a baseline for the optimization tests. The required Delta is then transferred to the production plant as an optimization potential (Fig. 11.16). 

Production plants for supercritical fluid extraction of natural substances have now been in operation for several years. Production costs are significantly influenced by the energy requirement. Energy optimization may improve production economy for existing and future extraction plants. Results of optimization calculations were first published by Eggers 1. These calculations are extended here. 

These extrapolation methods allow to determine what will be the best operating conditions, and the optimal system configuration of the production plant from a technical and economical point view. If the extrapolation and optimization methods describe above concerns only the "extraction step" of the process, it is also very important to optimize the other parts of the process the optimization of the extract recovering and fractionation, the energetic process optimization, or the improvement of the extractor emptying and loading procedure are also some very important points that must be considered in the industrial process design. 

Packings and Flooding As pointed out above, optimized mass and heat balances have been derived from a combination of experimental results with a con uter simulation of the process. The optimized balances can be used for the layout of a production plant A multi-purpose plant should be able not only to produce samples, but also to determine scaleup parameters. The scaleup parameters depend on the type of packing and its specific flooding point The ability to measure flooding points or to test different packings is restricted mainly by the range of flow rates. 

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