Optimisation Results

Points 1 and 2 on the gr h show the best downtime and cost achievable respectively for the system with an in.spection interval of 7. Should point 1 be selected, when downtime is minimised the operating cost per unit time is 911. This is almost 3.4% higher than the minimum possible operating cost. However, if point 2 is selected, when the cost is minimised, the downtime suffered will be 0.18 hours per unit time. This translates to a reduction in availability of 0.34% from the maximum availability attainable by the equipment. 

It is worth mentioning that in some cases, it could be relatively difficult to quantify cost factors with confidence. For example, for a fishing vessel, there are several elements that need to be considered when representing downtime as a loss value in monetary terms, such as wages, loss of consumption of perishables, etc. Therefore decisions on the inspection strategy may not be made solely based on C(T). In such cases, D(T) based decision on the inspection strategy may be more reasonable. If uncertainties in both D(T) and C(T) are considered, then decisions on the inspection strategy can be made based on a combination of D(T) and C(T). 

Inspections carried out during the operation phase of machinery will reveal any failures that have already been initiated at an earlier time. Upon identifying the abnormal condition, 

The final decision of the optimal inspection period will depend heavily on the needs and operating culture of the owner/operator of the vessel. The implementation of such a regime on fishing vessels will be influenced by the operating circumstances of the equipment and other factors such as availability of expertise, position of vessel and sea conditions. However, should the conditions for implementation be favourable, delay-time analysis can be used to optimise the system s inspection maintenance scheme. 

Almeida A.T. and Bohoris G.A., (1995) Decision Theory in Maintenance Decision Making , Journal of Quality in Maintenance Engineering, Vol. 1, No. 1, 1995, pp. 34-45. 

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The result of this work with the model clearly shows that there are worthwhile savings to be had from brine optimisation particularly as the cost of implementation will be small. The plant already has a system which optimises its production schedule and the brine optimisation results can be added to the associated program in the form of a simple look-up table. 

Figure 1.10 shows the optimisation of a separation of a mixture of aromatic hydrocarbons. In this case, optimisation of the liquid chromatography separation has been carried out by successive modifications of the composition of the mobile phase. It can be seen that this optimisation results in a significant increase in the cycle time for analysis. 

The optimisation results are summarized in Table 5.8. Figure 5.4 shows the reflux ratio profiles used in the simulation and those obtained by optimisation. Figure 5.5 shows the optimal accumulated and instant distillate composition profiles. The reflux ratio profile is increasing with time as expected. The results clearly show the benefit of optimising the reflux ratio. As can be seen from Table 5.8 the operation time is reduced by at least 50% compared to that in the simulation and experiment. The results also show that for the given separation task an initial total reflux operation is not at all required and the product can be collected from the very beginning of the process (see notes in section 3.3.1). 

Farhat et al. considered both optimal constant and optimal linear reflux ratio for this problem (Figure 6.15). Final time was fixed and 4 time intervals were considered. The length of each time interval was also optimised. Table 6.12 presents the summary of the optimisation results using both options of reflux ratio profiles. A significant gain of 10.7% in specified products can be observed between the optimal linear reflux policy and the optimal constant reflux policy. 

Case 1 of Table 9.3 is the base case. It shows the optimisation results using the cost parameters presented in Table 9.2. The maximum profit and optimal batch time obtained by optimisation shows very good agreement to those shown in Figure 9.8. The maximum profit shown in Figure 9.8 is between 3.99-4.13 ( /hr) with an optimum batch time between 12-14 hr. Each of the optimisation problems (i.e. solution of P2 with Equation 9.6) presented in Table 9.3 requires approximately 3- 4 iterations and about 3- 4 cpu sec using a SPARC-1 Workstation (Mujtaba and Macchietto, 1997). 

Finally, to check the reliability of the simulation results provided by the NN model, the optimal reflux and reboil ratios were implemented into the detailed (i.e., deterministic) MVC simulator (Barolo et al., 1998). The broken lines in Figure 12.12 represent the relevant time profiles obtained with the detailed MVC simulator for an operation carried out using the optimal values of the reflux and reboil ratios as calculated by the NN. Greaves et al. (2003) noted that the actual process is indeed represented quite accurately by the NN model, which confirmed that the optimisation results were reliable. 

The optimisation results revealed that the most economically favourable system configuration for Rauhelleren comprises a wind turbine with a capacity of 140 kW, a 30-kW PEM fuel cell, water electrolyser capable of producing 8 N m3/h of hydrogen and a 400-kg hydrogen storage tank. 

Following this study, we found that the optimum conditions for maximising the yield while retaining selectivity involved two successive 1 h autoclave reactions at 180 °C, using HM (4.0 g, Si/Al ratio 17.5), /er/-butanol (80 mmol) and cyclohexane (10 ml) for an initial 10 mmol of naphthalene. Under these conditions, a 2,6-di-tert-butylnaphthalene yield of 50 % and a 2,6/2,7 ratio of 58.5 were achieved after the first reaction, and a 60 % yield with a ratio of 50.6 after the second stage. The optimised result is compared with the most selective literature result in Table 4. 

We will now turn our attention towards the synthesis and application of phosphane functionalised carbenes. A very interesting class of ligands is based on the ferrocene [265-267] scaffold. Cp functionahsed carbenes will be discussed in Section 4.3 and we will find our ferrocene functionalised carbenes there as well. However, the synthesis of the ligands involves a strategy to introduce the phosphane and carbene moieties onto the ferrocene scaffold in a way that optimises results despite the fact that both groups are best introduced last. 

Table 1 lists the obtained optimisation results for the process schemes in Fig. 3. As expected, the conventional setup a) is a feasible option. It performs somewhat better for the strongly adsorbed component B. The reason is that for producing A, the recycle load is higher due to the strongly diluted stream of B at the extract port. 

Table 1 Optimisation results for the process options shown in Fig. 3. The first column marks the process scheme according for Fig. 3 and the target component. PR is scaleable by solid flux.

The model-based dynamic optimisation results that were obtained from a fixed feed composition, same initial condition as the batch culture, and a feeding interval of 6-12 h, suggested an optimal cell cycle-arrest time at 126 h and supplementation with feed from 48 h onwards. The results of three different fed-batch cultures with identical supplementation strategies but various cell cycle-arrest times are shown in Fig.3. The viable cell concentration, Xy, was closely predicted up to about 80 h. However, after lOOh, Xv decreased significantly in all three cultures. The predicted MAb concentration was in accordance with the experimental results with only a slight under-prediction around 80-100 h. Both model predictions and experimental results indicated a small difference in MAb yield when the cultures were arrested at different times. The optimised fed-batch experiments involved a total of 9 shake flask cultures so the... 

Table 4 presents the obtained results. In most cases, a relative benefit above 85% was obtained, with a rninimrun value of 77%. The observed relative computational effort remained below 50% for 9 of the 12 cases studied, showing that good accuracy on the optimisation results was obtained with significant reduction of the computahonal effort. 

The optimisation results in lower amounts of dust and residues and in higher energetic efficiency. 

Optimisation results show that a batch addition of the reactant constitutes the best feed profile. According to the reaction scheme (consecutive-competitive) these profiles could be a priori determined (Burghardt and Skrzypek, 1974). The configuration of the... 

It is observed from the optimisation results that for minimising burr size, the optimal cutting speed requirement is low, i.e. 8m/min irrespective of the drill diameter. On the other hand, as depicted in Figure 7.10, the requirement of optimal feed is in the low range (0.04-0.06mm/rev) and is in direct proportion to the drill diameter for the entire range specified. The reason might be that at lower feed thrust force reduces and hence forms thinner burrs. 

From the optimisation results, it is observed that the combination of optimal feed and point angle has played a key role in reducing the burr size for every drill diameter specified in the range 16-2 8mm. However, the different combinations of optimal feed and point angle are required for minimising the burr size. It is also revealed that, with the increase in drill diameter, simultaneous increase in feed and... 

The formulation of the s-constraint technique is performed as one of the objectives is assigned as the objective function while the others are constrained within specified upper limits. The selected process parameters are assigned as the decision variables of the optimisation problem. The optimiser searches over the process variables, within the feasibility and constraints regions and feeds these selected variables to the model in HYSYS. Then, it waits for the process in HYSYS to converge and then recalculate the objectives and evaluate the optimisation results. This search loop between the optimiser in Excel and the model in HYSYS continues until a global optimum point is found which represents a point on the Pareto curve. The above optimisation process is repeated for different bounds of the constrained objectives to develop the entire Pareto curve. 

Based on the generated optimisation result, the maximum for the scenario is identified to be US 24.07 million (per annum) with the annual production for Alkane, of 2643.42 tonnes. As the objective of this scenario is to synthesise an integrated biorefmery with maximum economic potential, alcohols are produced and sold as by-products together with the main product AlkanCj. The conversion pathways chosen for the scenario are presented in the synthesised integrated biorefmery as shown in Figure 11.9. 

The optimised results indicated a material blend of 60 % BB7755 and 40 % RPET, a preform cooling time of 4.5 s, a blow time of 7 s. with a mould temperature of 80 °C. Given that the nrould temperature indicates a non significant dqtendence at these low temperatures, subsequence experiments are conducted for mould temperatures between 120 - 150 "C for the optimised material blend utilising optimised process conditions as indicated above. 

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