Effect of cutting conditions on surface roughness of machined parts in CO2 laser cutting of pure titanium

Titanium (Ti) and its alloys machining has been a long standing issue in the manufacturing industry. The extraordinary Ti machining costs restrict its used in the specialised applications. To achieve improved surface quality, researchers are working tirelessly to optimize various cutting parameters. In this study, high-power C

Multi-Objective Flexible Job Shop Scheduling Using Genetic Algorithms

Flexible Job Shop Scheduling is an important problem in the fields of combinatorial optimization and production management. This research addresses multi-objective flexible job shop scheduling problem with the objective of simultaneous minimization of: (1) makespan, (2) workload of the most loaded machine, and (3) total workload. A general-purpose, domain independent genetic algorithm implemented in a spreadsheet environment is proposed for the flexible job shop. Spreadsheet functions are used to develop the shop model. Performance of the proposed algorithm is compared with heuristic algorithms already reported in the literature. Simulation experiments demonstrated that the proposed methodology can achieve solutions that are comparable to previous approaches in terms of solution quality and computational time. Flexible job shop models presented herein are easily customizable to cater for different objective functions without changing the basic genetic algorithm routine or the spreadsheet model. Experimental analysis demonstrates the robustness, simplicity, and general-purpose nature of the proposed approach

Analysis of flow and heat transport between converging channel

Heat transport analysis for non-Newtonian fluid flows between non-parallel wall channels has sustainable significance in high-performance thermal engineering processes. In recent years, this analysis is extensively used in numerous natural flows and industrial processes, for instance, blood flow through human veins, lubrication systems, automobile radiators, thermal pumps, and water purification processes, etc. Therefore, this research, it is targeted to enhance thermal performance with the addition of ultrafine metallic nanoparticles into working fluids. With this goal in mind, this research work presents a numerical investigation for buoyancy-driven flow of Carreau nanofluids confined in a vertical converging enclosure. In addition, heat and mass transport analysis with non-linear thermal radiation and activation energy are mathematically formulated via Buongiorno’s model. A new formulation is developed for purely radial flow inside this converging channel and appropriate non-dimensional variables are utilized for problem simplification. These transformed equations are then numerically tackled with the help of a versatile numerical method, bvp4c function in MATLAB. The simulated results are portrayed by virtue of nanofluid velocity, temperature, and concentration distributions with variation in governing dimensionless parameters. The results indicate that the velocity was significantly reduced with higher activation energy parameter. Moreover, the higher values of the Grashof number yields increasing conduct in velocity distributions

Robust Asynchronous H∞ Observer-Based Control Design for Discrete-Time Switched Singular Systems with Time-Varying Delay and Sensor Saturation: An Average Dwell Time Approach

This work discuss the robust stabilization problem for discrete-time switched singular systems with simultaneous presence of time-varying delay and sensor nonlinearity. To this end, an observer-based controller was synthesized that works under asynchronous switching signals. Investigating the average dwell time approach and using a Lyapunov–Krasovskii functional with triple sum terms, sufficient conditions were derived for achieving the existence of such asynchronous controller and guaranteeing the resulting closed-loop system to be exponentially admissible with H∞ performance level. Subsequently, the effectiveness of the proposed control scheme was verified through two numerical examples

Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia)

Fuzzy methods using linguistic expressions and fuzzy numbers can provide a more accurate examination of manufacturing systems where data is not clear. Researchers expanded fuzzy control charts (CCs) using fuzzy linguistic statements and investigated the current process efficiency index to evaluate the performance, precision, and accuracy of the production process in a fuzzy state. Compared to nonfuzzy data mode, fuzzy linguistic statements provided decision makers with more options and a more accurate assessment of the quality of products. The fuzzy index of the actual process efficiency analyzed the process by considering mean, target value, and variance of the process simultaneously. Inspection of household water meters in Ha'il, Saudi Arabia showed the actual process index values were less than 1, indicating unfavorable production conditions. Fuzzy methods enhance the accuracy and effectiveness of statistical quality control in real-world systems where precise information may not be readily available. In addition, to provide a new perspective on the comparison of urban water and sewage systems, the results obtained from fuzzy-CC were compared with various machine learning methods such as artificial neural network and M5 model tree, in order to identify and understand their respective advantages and limitations. HIGHLIGHTS This research shows that fuzzy methods, which use appropriate linguistic expressions and fuzzy numbers, can provide a more accurate examination of the state of the production process.; This article evaluates the performance of the fuzzy-CC, which was developed by benefiting the fuzzy linguistic statements, the current procedure, and the actual process efficiency index (Cpm) in the production process.

Minimization of completion time variance in flowshops using genetic algorithms

The majority of the flowshop scheduling literature focuses on regular performance measures like makespan, flowtime etc. In this paper a flowshop scheduling problem is addressed where the objective is to minimize completion time variance (CTV). CTV is a non-regular performance measure that is closely related to just-in-time philosophy. A Microsoft Excel spreadsheet-based genetic algorithm (GA) is proposed to solve the problem. The proposed GA methodology is domain-independent and general purpose. The flowshop model is developed in the spreadsheet environment using the built-in formulae and function. Addition of jobs and machines can be catered for without the change in the basic GA routine and minimal change to the spreadsheet model. The proposed methodology offers an easy to handle framework whereby the practitioners can implement a heuristic-based optimization tool with the need for advanced programming tools. The performance of the proposed methodology is compared to previous studies for benchmark problems taken from the literature. Simulation experiments demonstrate that the proposed methodology solves the benchmark problems efficiently and effectively with a reasonable accuracy. The solutions are comparable to previous studies both in terms of computational time and solution quality

Design of a Fuzzy Optimization Control Structure for Nonlinear Systems: A Disturbance-Rejection Method

This paper tackles the control problem of nonlinear disturbed polynomial systems using the formalism of output feedback linearization and a subsequent sliding mode control design. This aims to ensure the asymptotic stability of an unstable equilibrium point. The class of systems under investigation has an equivalent Byrnes–Isidori normal form, which reveals stable zero dynamics. For the case of modeling uncertainties and/or process dynamic disturbances, conventional feedback linearizing control strategies may fail to be efficient. To design a robust control strategy, meta-heuristic techniques are synthesized with feedback linearization and sliding mode control. The resulting control design guarantees the decoupling of the system output from disturbances and achieves the desired output trajectory tracking with asymptotically stable dynamic behavior. The effectiveness and efficiency of the designed technique were assessed based on a benchmark model of a continuous stirred tank reactor (CSTR) through numerical simulation analysis