Process trends, description

The extraction, though, of the so-called pivotal features from operating data, encounters the same impediments that we discussed earlier on the subject of process trends representation (1) localization in time of operating features and (2) the multiscale content of operating trends. It is clear, therefore, that any systematic and sound methodology for the identification of patterns between process data and operating conditions can be built only on formal and sound descriptions of process trends. 

None of the practiced compression techniques satisfies all of these requirements. In addition, it should be remembered that compression of process data is not a task in isolation, but it is intimately related to the other two subjects of this chapter (1) description of process trends and (2) recognition of temporal patterns in process trends. Consequently, we need to develop a common theoretical framework, which will provide a uniformly consistent basis for all three needs. This is the aim of the present chapter. 

Section II introduces the formal framework for the definition anc description of process trends at all levels of detail qualitative, order-of magnitude, and analytic. A detour through the basic concepts of scale-spact filtering is necessary in order to see the connection between the concept o process trends and the classical material on signal analysis. Within th( framework of scale-space filtering we can then elucidate the notions o episode, scale, local filtering, structure of scale, distinguishec features, and others. 

Once the stable reconstruction of a signal has been accomplished, its subsequent representation can be made at any level of detail, i.e. qualitative, semi-quantitative, or fully real-valued quantitative. The triangular episodes (described in Section I, A) can be constructed to offer an explicit, declarative description of process trends. 

Limestone Production. Because more than 99% of U.S. limestone is sold or used as cmshed and broken stone, rather than dimension-stone, most of the description of limestone s extraction and processing herein focuses on the former (Fig. 4). Most stone is obtained by open-pit quarrying methods. Underground mining is pursued by some important operations, but the toimage quarried exceeds that mined by nearly 20-fold. There is, however, a slight trend toward increased mining which should continue. 

Following the general trend of looldng for a molecular description of the properties of matter, self-diffusion in liquids has become a key quantity for interpretation and modeling of transport in liquids [5]. Self-diffusion coefficients can be combined with other data, such as viscosities, electrical conductivities, densities, etc., in order to evaluate and improve solvodynamic models such as the Stokes-Einstein type [6-9]. From temperature-dependent measurements, activation energies can be calculated by the Arrhenius or the Vogel-Tamman-Fulcher equation (VTF), in order to evaluate models that treat the diffusion process similarly to diffusion in the solid state with jump or hole models [1, 2, 7]. 

The pitfalls of a computer model are obvious in that it is only a conceptual representation of the reactor and includes only as many aspects of the real reactor as present knowledge permits. In addition, even the most perfectly conceived description will still depend upon the accuracy of the physically measured constants used in the model for the quality of the process representation. The goal of this report is, however, only to show conceptual trends and the technological base is developed to the extent that the conceptual trends will be correct. In some respects the computer model is a better process development tool than the pilot plant used for the LDPE process since the pilot reactor does not yield directly scaleable information. The reader should take care to direct his attention to the trend information and conceptual differences developed in this work very little attention should be paid to the absolute values of the parameters given. 

Process development with particular attention to process profitability and safety and minimization of the environmental impact is presented in Chapter 5. A brief description of the present practice in scale-up, development, and production planning is given and the most promising trends and achievements are presented. Recommendations are given how to achieve success in the scale-up of a process a successful scale-up can be defined as the procedure that allows the same yields and product distribution in a full-scale plant as on a small scale. 

Labels are distinguished based on whether they are context dependent or context-free. Context-dependent labels require simultaneous consideration of time records from more than one process variable context-free labels do not. Thus, generating context-free trend, landmark, and fault descriptions is considerably more simple than generating context-dependent descriptions. Context-free situations can take advantage of numerous methods for common, yet useful, interpretations. Context-dependent situations, however, require the application of considerable process knowledge to get a useful interpretation. In these situations, performance is dependent on the availability, coverage, and distribution of labeled process data from... 

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