78 resultados para batch fermentation

em Indian Institute of Science - Bangalore - Índia


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This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

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The work reported herein is part of an on-going programme to develop a computer code which, given the geometrical, process and material parameters of the forging operation, is able to predict the die and the billet cooling/heating characteristics in forging production. The code has been experimentally validated earlier for a single forging cycle and is now validated for a small batch production. To facilitate a step-by-step development of the code, the billet deformation has so far been limited to its surface layers, a situation akin to coining. The code has been used here to study the effects of die preheat-temperature, machine speed and rate of deformation the cooling/heating of the billet and the dies over a small batch of 150 forgings. The study shows: that there is a pre-heat temperature at which the billet temperature changes little from one forging to the next; that beyond a particular number of forgings, the machine speed ceases to have any pronounced influence on the temperature characteristics of the billet; and that increasing the rate of deformation reduces the heat loss from the billet and gives the billet a stable temperature profile with respect to the number of forgings. The code, which is simple to use, is being extended to bulk-deformation problems. Given a practical range of possible machine, billet and process specifics, the code should be able to arrive at a combination of these parameters which will give the best thermal characteristics of the die-billet system. The code is also envisaged as being useful in the design of isothermal dies and processes.

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The activity of glutamine synthetase fromAspergillus niger was significantly lowered under conditions of citric acid fermentation. The intracellular pH of the organism as determined by bromophenol blue dye distribution and fluorescein diacetate uptake methods was relatively constant between 6•0–6•5, when the pH of the external medium was varied between 2•3–7•0.Aspergillus niger glutamine synthetase was rapidly inactivated under acidic pH conditions and Mn2+ ions partially protected the enzyme against this inactivation. Mn2+-dependent glutamine synthetase activity was higher at acidic pH (6•0) compared to Mg2+-supported activity. While the concentration of Mg2+ required to optimally activate glutamine synthetase at pH 6•0 was very high (≥ 50 mM), Mn2+ was effective at 4 mM. Higher concentrations of Mn2+ were inhibitory. The inhibition of both Mn2+ and Mg2+-dependent reactions by citrate, 2-oxoglutarate and ATP were probably due to their ability to chelate divalent ions rather than as regulatory molecules. This suggestion was supported by the observation that a metal ion chelator, EDTA also produced similar effects. Of the end-products of the pathway, only histidine, carbamyl phosphate, AMP and ADP inhibitedAspergillus niger glutamine synthetase. The inhibitions were more pronounced when Mn2+ was the metal ion activator and greater inhibition was observed at lower pH values. These results permit us to postulate that glutamine synthesis may be markedly inhibited when the fungus is grown under conditions suitable for citric acid production and this block may result in delinking carbon and nitrogen metabolism leading to acidogenesis.

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This paper describes a simple technique for the fermentation of untreated or partly-treated leafy biomass in a digester of novel design without incurring the normal problems of feeding, floating and scum formation of feed, etc. The solid phase fermentation studied consists of a bed of biomass frequently sprinkled with an aqueous bacterial inoculum and recycling the leachate to conserve moisture and improve the bacterial dispersion in the bed. The decomposition of the leaf biomass and water hyacinth substrates used in this study was rapid, taking 45 and 30 days for the production of 250 and 235 l biogas per kg total solids (TS) respectively, for the above mentioned substrates at a daily sprinkled volume of 26 ml cm−2 of bed per day sprinkled at 12 h intervals. Very little volatile fatty acid (VFA) intermediates accumulated in the liquid sprinkled, suggesting acidogenesis to be rate-limiting in this process. From the pattern of VFA and gas produced it is concluded that most of the biogas produced is from the biomass bed, thus making the operation of a separate methanogenic reactor unnecessary.

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Wear of dies is a serious problem in the forging industry. The materials used for the dies are generally expensive steel alloys and the dies require costly heat treatment and surface finishing operations. Degeneration of the die profile implies rejection of forged components and necessitates resinking or replacement of the die. Measures which reduce wear of the die can therefore aid in the reduction of production costs. The work reported here is the first phase of a study of the causes of die wear in forging production where the batch size is small and the machine employed is a light hammer. This is a problem characteristic of the medium and small scale area of the forging industry where the cost of dies is a significant proportion of the total capital investment. For the same energy input and under unlubricated conditions, die wear has been found to be sensitive to forging temperature; in cold forging the yield strength of the die material is the prime factor governing the degeneration of the die profile, whilst in hot forging the wear resistance of the die material is the main factor which determines the rate of die wear. At an intermediate temperature, such as that characteristic of warm forging, the die wear is found to be less than that in both cold and hot forging. This preliminary study therefore points to the fact that the forging temperature must be taken into account in the selection of die material. Further, the forging industry must take serious note of the warm forging process, as it not only provides good surface finish, as claimed by many authors, but also has an inherent tendency to minimize die wear.

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In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

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A mathematical model is developed to simulate oxygen consumption, heat generation and cell growth in solid state fermentation (SSF). The fungal growth on the solid substrate particles results in the increase of the cell film thickness around the particles. The model incorporates this increase in the biofilm size which leads to decrease in the porosity of the substrate bed and diffusivity of oxygen in the bed. The model also takes into account the effect of steric hindrance limitations in SSF. The growth of cells around single particle and resulting expansion of biofilm around the particle is analyzed for simplified zero and first order oxygen consumption kinetics. Under conditions of zero order kinetics, the model predicts upper limit on cell density. The model simulations for packed bed of solid particles in tray bioreactor show distinct limitations on growth due to simultaneous heat and mass transport phenomena accompanying solid state fermentation process. The extent of limitation due to heat and/or mass transport phenomena is analyzed during different stages of fermentation. It is expected that the model will lead to better understanding of the transport processes in SSF, and therefore, will assist in optimal design of bioreactors for SSF.

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Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

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This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

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The study of the nutritional requirements of Arthrobacter strain C19d which accumulates alanine in large amounts in the culture medium. 1evealed that the organism needs thiamine for its growth. A Iso the alanine accumulation by this strain was found to be related to thiamine concentration in the medium. The optimum concentration of thiamine for alanine accumulation (20 tJ.g/mJ) Was also optimum for the growth of the organism indicating thereby that alanine accumulation by this strain is a growth associated process rather than far removed from it. Among the various growth promoters tried yeast extract was found to be superior from the point of view of alanine yield and it wa5 also superior to giving thiamine alone in the medium. A concentration of 0.02% yeast extract was found to be optimum for alanine occumulation.

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The optimal design of a multiproduct batch chemical plant is formulated as a multiobjective optimization problem, and the resulting constrained mixed-integer nonlinear program (MINLP) is solved by the nondominated sorting genetic algorithm approach (NSGA-II). By putting bounds on the objective function values, the constrained MINLP problem can be solved efficiently by NSGA-II to generate a set of feasible nondominated solutions in the range desired by the decision-maker in a single run of the algorithm. The evolution of the entire set of nondominated solutions helps the decision-maker to make a better choice of the appropriate design from among several alternatives. The large set of solutions also provides a rich source of excellent initial guesses for solution of the same problem by alternative approaches to achieve any specific target for the objective functions

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The present work concerns with the static scheduling of jobs to parallel identical batch processors with incompatible job families for minimizing the total weighted tardiness. This scheduling problem is applicable in burn-in operations and wafer fabrication in semiconductor manufacturing. We decompose the problem into two stages: batch formation and batch scheduling, as in the literature. The Ant Colony Optimization (ACO) based algorithm called ATC-BACO algorithm is developed in which ACO is used to solve the batch scheduling problems. Our computational experimentation shows that the proposed ATC-BACO algorithm performs better than the available best traditional dispatching rule called ATC-BATC rule.

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The oxygen transfer rate and the corresponding power requirement to operate the rotor are vital for design and scale-up of surface aerators. The aeration process can be analyzed in two ways such as batch and continuous systems. The process behaviors of batch and continuous flow systems are different from each other. The experimental and numerical results obtained through the batch systems cannot be relied on and applied for the designing of the continuous aeration tank. Based on the experimentation on batch and continuous type systems, the present work compares the performance of both the batch and continuous surface aeration systems in terms of their oxygen transfer capacity and power consumption. A simulation equation developed through experimentation has shown that continuous flow surface aeration systems are taking more energy than the batch systems. It has been found that batch systems are economical and better for the field application but not feasible where large quantity of wastewater is produced.

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We consider the problem of minimizing the total completion time on a single batch processing machine. The set of jobs to be scheduled can be partitioned into a number of families, where all jobs in the same family have the same processing time. The machine can process at most B jobs simultaneously as a batch, and the processing time of a batch is equal to the processing time of the longest job in the batch. We analyze that properties of an optimal schedule and develop a dynamic programming algorithm of polynomial time complexity when the number of job families is fixed. The research is motivated by the problem of scheduling burn-in ovens in the semiconductor industry