Problem Definition Phase

While the cause leading to the initiation of a project can be ascribed either to the situation at a single site or that of an entire value chain, the resulting project can usually not be limited to one of these perspectives. For 

If a capacity expansion is the primary objective, the two most common cases are 

If the primary objective is the restructuring of a value chain, the solution space is wider as several plants can be affected simultaneously. Restructurings are usually initiated because of inefficiencies within the existing network or in the context of site closures and can take on one of three basic forms (cf. Bankhofer 2001, p. 95)  

It should be noted though, that in practice the restructuring of a value chain s production network often combines different basic restructuring types and includes capacity changes. Also, the relative importance of decision criteria depends on the type of project. For example, in plant closures factors such as public opinion towards the decision (sometimes causing a company to favor closures in countries other than their home country) and possible obligations to repay subsidies received become important (cf. Richbell and Watts 2000). 

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This phase is intended as a final check of the model as a whole. Testing of individual model elements should be conducted during earlier phases. Evaluation of the model is carried out according to the evaluation criteria and test plan established in the problem definition phase. Next, carry out sensitivity testing of the model inputs... 

The second part of the problem definition phase shows clearly that PCDD should be a potential concern to humans and animals in the environment. The degree of concern that we as a society should have can be estimated by a formalized risk assessment process. 

For convenience of presentation, model building can be divided into four phases (1) problem definition and formulation, (2) preliminary and detailed analysis, (3) evaluation, and (4) interpretation application. Keep in mind that model building is an iterative procedure. Figure 2.2 summarizes the activities to be carried out,... 

The following sections discuss each of these steps in detail and present a process that can be used to help insure successful problem definition. The two steps in the Solving the Problem phase of the project are not discussed in this chapter. Experimentation is dependent on the method that is used to probe the system and relies on the expertise of the person(s) collecting the data. Analysis of Experimental Results is the application of the chemomctric tools and is the topic of Chapters 3-5. 

In the environmental policy life cycle, four phases can be discerned 1, calling attention to the problem 2, definition phase 3, formulation of the solution and taking measures and 4, control phase. The development of concentration techniques with an interface and control function is indispensable in phases 1, 2, and 4. This situation is illustrated in Figure 2. 

There is a wide range of tools in the Six-Sigma toolbox, used during the define phase of a Six-Sigma project, which can be applied effectively for problem definition. Such tools... 

Table 8.1 describes the steps of the methodology in more detail. The procedure starts with the Problem definition production rate, chemistry, product specifications, safety, health and environmental constraints, physical properties, available technologies. Then, a first evaluation of feasibility is performed by an equilibrium design. This is based on a thermodynamic analysis that includes simultaneous chemical and physical equilibrium (CPE). The investigation can be done directly by computer simulation, or in a more systematic way by building a residue curve map (RCM), as explained in the Appendix A. This step will identify additional thermodynamic experiments necessary to consolidate the design decisions, mainly phase-equilibrium measurements. Limitations set by chemical equilibrium or by thermodynamic boundaries should be analyzed here. 

To complete the model specification, boundary conditions have to be specified. These describe the flow conditions at the domain boundaries. At flow inlets one can usually specify the fluid velocity, a mass flow rate, or an inlet pressure. Depending on the problem definition, the inlet temperature, species concentrations, turbulence properties, and volume fractions of any secondary phase must also be supplied. At flow exits, one usually specifies an outlet pressure, and if entrainment through a flow exit is anticipated, the exit... 

Quantitative study of kinetics of radicals accumulation has required solution of auxiliary problem - definition of the rate of photoinitiation Win. In the case of solid-phase reactions there are experimental difficulties in solution of this problem. Measurement of Win according to consumption of inhibitor is complicated by possible photochemical reactions of inhibitor itself and specific solid-phase effects of kinetic stop type and so on [10]. Measurement of Win according to initial rate of radicals accumulation is also tactless in solid polymer, as the latter may be much lower than Wm [164]. 

The Initiation Phase for an expert system covers the tasks involved in problem definition and in determining the need for an automated solution. It explores characteristics of a problem that suggest an expert system solution. However, the conclusions drawn from this phase are usually written independent of any particular technology. 

The objectives for the Concept Phase include problem definition, requirements and feasibility. These objectives define the approach to solve the information processing problem. The first objective of the Concept Phase is to confirm the existence of the information processing or knowledge-intensive problem. The second objective is to identify high level requirements for a solution to the problem. These requirements should focus on the nature of the problem and the user s needs. The third objective is to determine the feasibility of an expert system solution to the problem. This requires a study of the applicability of expert systems to the project and the capabilities of other information technologies in comparison to the choice of an expert system. 

Following the previous steps, a good problem definition should now be available. In some cases (e.g., the debutanizer), the cause may be identified. If not, there will be sufficient information to narrow down the possible causes and to form a theory. In general, when problems emerge, everyone will have a theory. In the next phase of the investigation, these theories are tested by experimentation or by trial and error. The following guidelines apply to this phase ... 

Problems with phase equUibrium experiments in reactive systems arise mainly if the reaction time constant is of the same order magnitude as the time constants of phase equilibrium experiments (intermediate Damkbhler number Da). For typical fluid phase equilibrium experiments, time constants are of the order of 10-1000 s, depending on the choice of the apparatus (and the definition of the time constant). These are however also typical time constants for many reactions, which are of interest for RD. It is therefore worthwhUe to discuss measurements of reactive phase equilibria in more detail. 

The formulation of engineering problems in phase equilibria begins with a set of abstract equations relating the component fugacities ft of each component i in a multiphase syslon. Tianslation of these equations into useM working relatiotiships is done by definition (throu tiie fiigacity coefficieiit and/or the activiqr coefficient y,) and by thermodynamic manipulation. Different problems require diffincnt translations we have illustrated many of the standard procedures by examples in Sections 1.3, 1.6, and 1.7. 

Agrawal, A. K., Tan, P.,Nagarajaiah, S., Zhang, J. (2009). Benchmark structural control problem for a seismically excited highway bridge—Part I Phase I problem definition. Structural Control and Health Monitoring, Special Issue, 16(5), 509-529. doi 10.1002/stc.301... 

The first phase in modeling is a description of the goal. This determines the boundaries of the system (which part of the system and the environment should be considered) and the level of detail (to which extent of detail should the system be modeled). The goal should be reasonably clear. A well-known rule of thumb is that the problem is already solved for 50% when the problem definition is clearly stated. 

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