Common Bottlenecks

Wort separation and beer filtration are two common bottlenecks ia the brewiag process. Poor lauteriag aot only causes a loss ia productioa capacity, but can also lead to losses ia extract yield. Furthermore, a slow lauteriag aegatively affects the quaHty of the wort, which may give beer filtratioa problems and problems with the flavor and stabiHty of the beer. 

Applications that would benefit from the described achievements are commonly bottlenecked by a lack of general procedures to interpret intensity data. Recently, it was suggested to interpret STEM data by extraction of single atom scattering cross sections For HRTEM, Figure 8 highlights a suitable method for intensity quantification from reconstructed electron exit waves. 

A common bottleneck in these processes remains the undesired enzymatic hydrolysis of the activated side-chain molecule to the usually poorly soluble amino acid [57]. In combination with unfavourable equilibrium conditions in the coupling reaction, this still leads to a tedious and costly purification technology. 

The most common bottleneck in achieving convergence in methods that rely on particle transfers is the prohibitively low acceptance of transfer attempts. 

Approximately 25% of the energy used in wet processing is consumed in drying [3]. In addition to energy cost, drying is a common bottleneck in the wet processes. Thus, improvement of the drying rate and... 

The types of facilities bottleneck which appear late in field life depend upon the reservoir, development scheme and facilities in place. Two of the most common capacity constraints affecting production include ... 

For catalyst testing, conventional small tubular reactors are commonly employed today [2]. However, although the reactors are small, this is not the case for their environment. Large panels of complex fluidic handling manifolds, containment vessels, and extended analytical equipment encompass the tube reactors. Detection is often the bottleneck, since it is still performed in a serial fashion. To overcome this situation, there is the vision, ultimately, to develop PC-card-sized chip systems with integrated microfluidic, sensor, control, and reaction components [2]. The advantages are less space, reduced waste, and fewer utilities. 

Nowadays, MS is often no longer the analytical bottleneck, but rather what precedes it (sample preparation) and follows it (data handling, searching). Direct mass-spectrometric methods have to compete with the separation techniques such as GC, HPLC and SFC that are commonly used for quantitative analysis of polymer additives. Extract analysis has the general advantage that higher-molecular-weight (less-volatile) additives can be detected more readily than by direct analysis of the polymer compound. 

Copper production is quite a complex process to plan and to schedule due to the many process interdependencies (shared continuous casters and cranes, emission level restrictions, limited material availability, to name a few). This makes it very difficult to foresee the overall consequences of a local decision. The variability of the raw material has alone a significant impact on the process, various disturbances and equipment breakdowns are common, daily maintenance operations are needed and material bottlenecks occur from time to time. The solution that is presented here considers simultaneously, and in a rigorous and optimal way, the above mentioned aspects that affect the copper production process. As a consequence, this scheduling solution supports reducing the impact of various disturbance factors. It enables a more efficient production, better overall coordination and visualization of the process, faster recovery from disturbances and supports optimal... 

As shown in Figure 7.2, most assays involve a common series of steps that must be completed in order to report results. These steps include sample receipt, method development, sample preparation, analysis, data processing, and data reporting. While most researchers focus on speeding the analysis step, any of these steps can become bottlenecks. Thus it is important to optimize the whole process. 

Just as it is common to feel that if a little training is good then more must be better, some researchers have worked on the assumption that if a few neurons are good, many neurons must be better. This working assumption is often incorrect. Two hidden layers are all that is needed for an ANN to deal with discontinuous or nonlinear functions. More layers may be used, but they are not normally necessary except for specialized applications such as bottleneck networks,53 which are not covered in this chapter. The inclusion of extra... 

Rarely in the pharmaceutical industry is a new plant built to accommodate a new process or product It may happen in the petrochemical industry, where economies of scale mean that product-specific plants are designed from scratch and then continuously de-bottlenecked over a number of years to increase and optimize productivity, but it is not the case in the pharmaceutical industry, where the number of types of unit operations in use is generally fairly small and fixed. Within a multi-purpose chemical plant commonly found in the batch chemical industry, it is common practice for process designers to make do with what is available on a given site to avoid capital expenditure and plant shut-down for modifications. 

The approach pursued in this and the next chapter is focused on the common mathematical characteristics of boundary processes. Most of the necessary mathematics has been developed in Chapter 18. Yet, from a physical point of view, many different driving forces are responsible for the transfer of mass. For instance, air-water exchange (Chapter 20), described as either bottleneck or diffusive boundary, is controlled by the turbulent energy flux produced by wind and water currents. The nature of these and other phenomena will be discussed once the mathematical structure of the models has been developed. 

---