Chemical plant optimization

Most aroma chemicals are relatively high boiling (80—160°C at 0.4 kPa = 3 mm Hg) Hquids and therefore are subject to purification by vacuum distillation. Because small amounts of decomposition may lead to unacceptable odor contamination, thermal stabiUty of products and by-products is an issue. Important advances have been made in distillation techniques and equipment to allow routine production of 5000 kg or larger batches of various products. In order to make optimal use of equipment and to standardize conditions for distillations and reactions, computer control has been instituted. This is particulady well suited to the multipurpose batch operations encountered in most aroma chemical plants. In some instances, on-line analytical capabihty is being developed to work in conjunction with computer controls. 

Process performance is affected by temperature. The reaction rate decreases with temperature over a range of 4—31°C. As the temperature decreases, dispersed effluent suspended sohds increase. In one chemical plant in West Virginia, the average effluent suspended sohds was 42 mg/L during the summer and 105 mg/L during the winter. Temperatures above 37°C may result in a dispersed floe and poor settling sludge. It is therefore necessary to maintain aeration basin temperature below 37°C to achieve optimal effluent quahty. 

The names or acronyms given to many applications are not easily recognized for the applications ability to meet a particular need. The list therefore includes several types of systems that have no direct applicability to SARA requirements (e.g., wastewater treatment plant optimization assistance with ordering chemicals). The creation of a comprehensive list of environmented applications provides a higher level of assurance that software that is relevant to Title III has not been overlooked. The list can also be used to eliminate systems from the review process and reduce the effort needed to identify a system that has the required capabilities. 

Standard shapes for composite stiffeners are not likely to occur for most aerospace applications. There, the value and function of the structure warrant optimizing the stiffener design. In contrast, for more everyday applications such as scaffolding, stairways, and walkways in chemical plants, competitive pressures lead to a situation where compromises in stiffener efficiency are readily accepted (overdesign) in order to achieve lower cost than would be associated with optimum design. 

Rippin, D.W.T. (1983) Simulation of single and multiproduct batch chemical plants for optimal design and operation. Comput. Chem. Eng., 7 (3), 137-156. 

The performance of a chemical plant depends upon an enormously high number of design and operating variables. This great number of process variables makes it impossible to find optimal conditions within the region of safe operation if no quantitative relationships (defined in terms of mathematics) between performance indices and process variables are known. In general, optima are complex functions of process variables, and therefore quantification of experimental ressults is needed. The methods for scale-up that were conventionally used at the time of Perkin chemistry resulted in successful commercialization of many laboratory recipes. This evolutionary, step-by-step method of scale-up is illustrated in Fig. 5.3-1 (after Moulijn et al. 2001). 

Much of the information presented in the first eight chapters of this book consisted of guidelines that would help the process engineer to save time and money. What has been presented is an optimization procedure for obtaining a preliminary chemical plant design. Like the wise small farmer, the efficient process engineer relies heavily upon information that has been obtained by others. We do not need to reinvent the wheel every time we want to construct a new vehicle. 

Pressure-relieving systems are unique compared with other systems within a chemical plant hopefully they will never need to operate, but when they do, they must do so flawlessly. Other systems, such as extraction and distillation systems, usually evolve to their optimum performance and reliability. This evolution requires creativity, practical knowledge, hard work, time, and the cooperative efforts of the plant, design, and process engineers. This same effort and creativity is essential when developing relief systems however, in this case the relief system development must be optimally designed and demonstrated within a research environment before the plant start-up. 

Optimization is the use of specific methods to determine the most cost-effective and efficient solution to a problem or design for a process. This technique is one of the major quantitative tools in industrial decision making. A wide variety of problems in the design, construction, operation, and analysis of chemical plants (as well as many other industrial processes) can be resolved by optimization. In this chapter we examine the basic characteristics of optimization problems and their solution techniques and describe some typical benefits and applications in the chemical and petroleum industries. 

Because of the complexity of chemical plants, complete optimization of a given plant can be an extensive undertaking. In the absence of complete optimization we often rely on incomplete optimization, a special variety of which is termed suboptimization. Suboptimization involves optimization for one phase of an operation or a problem while ignoring some factors that have an effect, either obvious or indirect, on other systems or processes in the plant. Suboptimization is often necessary because of economic and practical considerations, limitations on time or personnel, and the difficulty of obtaining answers in a hurry. Suboptimization is useful when neither the problem formulation nor the available techniques permits obtaining a reasonable solution to the full problem. In most practical cases, suboptimization at least provides a rational technique for approaching an optimum. 

Montagna, J. M. and O. A. Iribarren. Optimal Computation Sequence in the Simulation of Chemical Plants. Comput Chem Eng 12 12-14 (1988). 

To control, optimize, or evaluate the behavior of a chemical plant, it is important to know its current status. This is determined by the values of the process variables contained in the model chosen to represent the operation of the plant. This model is constituted, in general, by the equations of conservation of mass and energy. 

It is becoming common practice, in today s chemical plants, to incorporate some kind of technique to rectify or reconcile the plant data. These techniques allow adjustment of the measurement values so that the corrected measurements are consistent with the corresponding balance equations. In this way, the simulation, optimization, and control tasks are based on reliable information. Figure 3 shows schematically a typical interconnection between the previous mentioned activities (Simulation Sciences Inc., 1989). 

Reliable process data are the key to the efficient operation of chemical plants. With the increasing use of on-line digital computers, numerous data are acquired and used for on-line optimization and control. Frequently these activities are based on small improvements in process performance, but it must be noted that errors in process data, or inaccurate and unreliable methods of resolving these errors, can easily exceed or mask actual changes in process performance. 

Cronin G, Hay ME (1996b) Within plant variation in seaweed palatability and chemical defenses optimal defense theory versus the growth differentiation balance hypothesis. Oecologia... 

Chemical engineers use engineering principles to solve problems of a chemical nature. Nearly three-fourths of the approximately 33,000 chemical engineers in the United States work in chemical manufacturing. They design chemical plants, develop chemical processes, and optimize production methods. A primary concern of chemical engineers working in industry is to... 

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. 

II processes are subject to disturbances that tend to change operating conditions, compositions, and physical properties of the streams. In order to minimize the ill effects that could result from such disturbances, chemical plants are implemented with substantial amounts of instrumentation and automatic control equipment. In critical cases and in especially large plants, moreover, the instrumentation is computer monitored for convenience, safety, and optimization. 

In a chemical plant the capital investment in process piping is in the range of 25-40% of the total plant investment, and the power consumption for pumping, which depends on the line size, is a substantial fraction of the total cost of utilities. Accordingly, economic optimization of pipe size is a necessary aspect of plant design. As the diameter of a line increases, its cost goes up but is accompanied by decreases in consumption of utilities and costs of pumps and drivers because of reduced friction. Somewhere there is an optimum balance between operating cost and annual capital cost. 

I. E. Grossmann and R. W. H. Sargent. Optimal design of multipurpose chemical plants. 

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