In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex OPTIMIZATION problem that guarantees the global optimal solution. The convex OPTIMIZATION problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

There have been many productive methods developed so far for OPTIMIZATION of multiple RESPONSE surface (MRS) problems. This paper tends to review the most seminal approaches in MRS and discuss the strength and weakness of each of the approaches through existing aspects in MRS. A numerical example is included to compare results by different methods. Finally, some of the prominent areas for future research discussed by different researchers are presented.

The simultaneous OPTIMIZATION of multiple RESPONSEs is an important problem in the design of industrial processes in order to achieve improved quality. In this paper, we present a new metaheuristic approach including Simulated Annealing and Particle Swarm OPTIMIZATION to optimize all RESPONSEs simultaneously. For the purpose of illustration and comparison, the proposed approach is applied to two problems taken from the literature. The results of our study show that the proposed approach outperforms the other approaches and can find better solutions.Finally, in both cases, we present the results of a sensitivity analysis incorporating experimental design.

The performance of a product is often evaluated by several quality characteristics. Optimizing the manufacturing process with respect to only one quality characteristic will not always lead to the optimum values for other characteristics. Hence, it would be desirable to improve the overall quality of a product by improving quality characteristics, which are considered to be important. The problem consists of optimizing several RESPONSEs using multiple objective decision making (MODM) approach and design of experiments (DOE). A case study will be discussed to show the application of the proposed method

The automobile workshop queue system has been optimized using various approaches, such as queuing theory, simulation, and probability. The utilization of RESPONSE surface methodology (RSM) for optimizing automobile workshop queue systems is not yet established. The utilization of RSM with direct observation enables the detection of patterns of correlations between variables and RESPONSEs, which are then represented through mathematical equations. The OPTIMIZATION process involves numerous factors that impact queue performance, which can be categorized into two parts. The number of servers, number of phases, number of workers, worker experience, and layout are classified in inner design. This study examines the relationship between two components of the outer design, specifically the arrival rate and the interarrival time. The RESPONSEs analyzed are queue cost, service time, average customer waiting time, and number of customers. The findings indicate that queue costs are not reliable for establishing the optimum value due to the significant impact of the cost structure on the structure of the optimal location. This study discovered that the number of leaving customers is related to queue costs and is relevant in selecting the optimal point. This study also formulates mathematical equations for predicting the optimal point. This study emphasizes the necessity for further investigation to uncover alternative mathematical equations that can precisely predict the optimal conditions for various types of services.