Cycle time optimization

We have discussed individual analyses and the demands to achieve optimization of instrumentation. However, an analytical laboratory must deal with series of samples and we must consider another factor if we want to optimize complete workflows cycle time optimization. Cycle time is defined as the time from finishing the analysis of one sample to the time the next sample is finished. This can be easily determined on Microsoft Windows -based operating systems by examining the data file creation time stamps of two consecutive samples. A better way is calculating the average of a reasonable number of samples. 

FIGURE 3.11 Different cycle time optimization possibilities achieved by parallelizing individual steps of LCMS-analysis. 

Optimization of Cycle Times. In batch filters, one of the important decisions is how much time is allocated to the different operations such as filtration, displacement dewatering, cake washing, and cake discharge, which may involve opening of the pressure vessel. Ah. of this has to happen within a cycle time /. which itself is not fixed, though some of the times involved may be defined, such as the cake discharge time. 

Besides actual mixing time, however, the total cycle time shoiild be optimized. 

Productivity is directly related to cycle time. There usually is considerable common knowledge about a geometry and process conditions that will provide a minimum cycle time. Practices such as using thinner wall sections, cold or hot runners for TPs or hot or cold ones for TSs narrow sprues and runners, the optimal size and location of coolant (or heat) channels, and lower melt or mold heat, will decrease the solidification time reducing the cycle time. 

Minimizing the cycle time in filament wound composites can be critical to the economic success of the process. The process parameters that influence the cycle time are winding speed, molding temperature and polymer formulation. To optimize the process, a finite element analysis (FEA) was used to characterize the effect of each process parameter on the cycle time. The FEA simultaneously solved equations of mass and energy which were coupled through the temperature and conversion dependent reaction rate. The rate expression accounting for polymer cure rate was derived from a mechanistic kinetic model. 

At an A/E ratio of 1.05, wind time of 3.8 minutes and molding temperature of llO C, the curing profiles of the part were simulated varying the press temperature until the maximum exotherm temperature occurred at the center of the part. This condition was achieved at a press temperature of 135 C. The minimal cycle time at the optimal processing conditions was simulated to be eight minutes. 

An eight minute cycle time does not allow any tolerance for error. Fabricators require a part success rate of approximately 95% therefore, the actual operating conditions chosen were more conservative than the ones optimized here. The conditions used in the actual process were as follows an A/E ratio of 1.05, a wind time of 3.8 minutes and mold and press temperatures of 90 and 115 C, respectively. These conditions resulted in a cycle time of eleven minutes which is three minutes more than the optimized cycle time. Figures 6a-9b, which were previously... 

The optimal cycle time t pt evaluated as described above is not necessarily the best if more than one unit is considered. For instance, separation of a reaction mixture of relatively low conversion can be troublesome and expensive. Therefore, the usefulness of the above... 

The criterion for optimal design is the same as that for single-product campaigns. The horizon constraint (7.4-34) is reformulated in that the cycle times are defined differently. Assuming UIS policy, this constraint for mixed-product campaigns is given by ... 

The cycle time for the sequence, tc..K.uJS, should be minimized to find the optimal sequence of batches for the UIS policy. The form of the objective function implies that the optimization of a schedule for UIS with minimum cycle time simply reduces to selecting any sequence of batches with slack times of bottleneck stage(s) set to zero. 

A physical component of IT life cycle management is storage media management. Tapes, disks, and other electronic media degrade over time. Optimally, they are refreshed every 10 years. Ideally, this is part of the SOPs for the data centers and archive facilities. 

Early integration of material modification, product application, and process optimization. This integration reduces cycle time and up-front risk. Today s fast-moving markets cannot accommodate a 20-year development cycle and still ensure commercial success. Concurrent engineering with discovery and manufacturing is required to be a leader. 

C. The Rheodyne Model 7010 injection valve, equipped with a 20-pl loop, was switched to injection at the apex of the sample band, as observed on the refractive index detector. The complex kinetics of the production of mono-, di-, and tri-brominated glycols is shown in Figure 14. Optimization of parameters such as the flow rate of acid resulted in a 15% reduction in batch cycle time and eliminated the need for manual analysis and intervention to obtain a desired endpoint composition. 

The control variables can be constrained to fixed values (e.g. fixed initial temperature in a temperature profile) or constrained to be between certain limits. In addition to the six variables dictating the shape of the profile, ttotai can also be optimized if required. For example, this can be important in batch processes to optimize the batch cycle time in a batch process, in addition to the other variables. 

Operating conditions. Optimization variables such as batch cycle time and total amount of reactants have fixed values for a given batch reactor system. However, variables such as temperature, pressure, feed addition rates and product takeoff rates are dynamic variables that change through the batch cycle time. The values of these variables form a profile for each variable across the batch cycle time. 

The optimization is now constrained to be at a fixed (optimized) chlorine addition rate, but the temperature profile optimized. Profile optimization is used for the temperature, as discussed in Chapter 3. The batch cycle time required is 1.42 h. The resulting fractional yield of MBA from BA now reaches 92.7%. 

The final option is to allow both the chlorine addition profile and temperature profile to be varied through the batch. The optimization shows a further improvement of the objective to 99.8%. It requires 1.35 h of batch cycle time and 75.0 kmol of chlorine. The optimized profiles for reaction temperature and feed addition rate of chlorine are shown in Figure 14.5. 

The performance of a batch reactor may be optimized in various ways. Here, we consider the case of choosing the cycle time, tc, equation 12.3-5, to maximize the rate of production of a product. For simplicity, we assume constant density and temperature. 

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