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Item Evaluate the performance and validation of coal fired boiler using ANN and GTM under various loading condition(UMT, Lahore, 2022) MUHAMMAD MUZZAMMIL YASINIndustries, district heating companies, and public institutions that use boilers for heating, process, or power production find it challenging to run at peak efficiencies due to rising fuel prices. Efficiency analysis is extremely important and brings attention to the boiler, which is at the center of energy generation because insufficient heat energy production and distribution efficiency contributes to overall energy expenditures. Boilers are widely used to produce steam which is used in mechanical components to transform fuel energy into kinetic energy of steam. The performance of a boiler is affected by various controlling parameters such as specific fuel consumption capacity, load, and heat losses. The current study was conducted to evaluate the performance of the coal-fired water tube boiler of D.G khan cement company limited and optimize the performance parameters using the Grey-Taguchi method. The experimental data were then validated through ANN-predicted results. The results indicated that the overall performance of the boiler was optimized at run number thirty where specific fuel consumption was 3.09 Kg/s at 66 % of the load, a steam temperature of 532 oC, and a steam pressure was 9.93 MPa. The specific steam flow rate was observed as 21.38 Kg/s at input conditions.Item Wind farm layout optimization by varying hub heights and inter-turbine spacing using genetic algorithm(UMT, Lahore, 2022) Muhammad Bin AliWind is an important renewable energy source. Majority of wind farms in Pakistan are installed in Jhimpir, Sindh Wind Corridor. At this location, downstream turbines encounter upstream turbines wakes decreasing power output. To maximize the power output, there is a need to minimize these wakes. In this research, a method is proposed to maximize the power output using Genetic Algorithm (GA). Hub heights and inter-turbine spacing are considered variables in this method. Two wind farms located at Jhimpir, Sindh namely; Second and Third Three Gorges Wind Farms (TGWFs) have been analyzed. Three different cases are considered to maximize the power output. In case I; same hub heights and inter-turbine spacing without wake effects are considered. In case II; same hub heights and inter-turbine spacing with wake effects are considered. In Case III; variable hub heights and inter-turbine spacing with wake effects are considered. The results reveal that TGWFs with variable hub heights and interturbine spacing produce more power output. It is also revealed that increase in power output in case of two different hub heights is greater in comparison to three different hub heights. Eventually, the proposed method can help in the layout optimization of any wind farm that is going to be installed.Item Fixture layout optimization of sheet metals by integrating topology optimization into genetic algorithm(UMT, Lahore, 2022) Shah Abdul HaseebManufacturing process accuracy is highly dependent on how well a workpiece is constrained in fixture. Workpiece is constrained by proper arrangement of fixture elements known as fixture layout. Fixture is comprised of locators and clamps. Fixtures restrain workpiece in such a way that the deformation is minimized during manufacturing process. Most of research is done considering rigid body. The research work on sheet metal is limited and many researchers are focusing on sheet metal due to many applications. A N-3-2-1 method is used for sheet metals which requires (N+3) fixture elements to constrain deformation normal to surface. Genetic Algorithm (GA) is used for fixture layout optimization but it requires high computational effort due to large number of population. A new method for fixture layout optimization is proposed by integrating topology optimization into GA. This method combines GA and topology optimization. In this method, topology optimization reduces population for GA. Objective function of this research is to reduce population for GA and minimize total deformation normal to plane of workpiece while restraining maximum deformation of individual nodes up to 2mm. Proposed approach comprised three stages. In first stage, initial number of clamps are determined. In second stage, population is reduced for GA and feasible area of clamps are identified by using topology optimization technique. In third stage, initial number and position of clamps earlier identified in stage one are optimized using GA. After stage one, two quadrants with highest maximum deformation is taken as design region while other two as non-design region for topology optimization. If clamp region is removed in topology optimization, then that clamp is excluded from workpiece because it indicates that clamp has least effect on deformation. Two case studies flat plate and spacer grid are solved to validate proposed method each case study consists of two subcases in which load applied position and magnitude is varied. Proposed method results 47.5% and 65 % decrease in population for subcase 1 and subcase 2 respectively. However, in subcase 3 and subcase 4 population reduced was 90% and 80% respectively. Convergence criteria is to solve GA for 25% of reduced population. Similarly, total deformation normal to the plane is reduced in each subcase with highest reduction of 86.31% in subcase 1 and lowest of 59.85% in subcase 4. In subcase 1 and subcase 2 optimum results were obtain in 64Th and 46th iteration respectively. Similarly in subcase 3 and subcase 4 optimal results were obtained on 4th and 14th iteration respectively. Results are also compared with previous thesis methods i-e GA and Response Surface Methodology (RSM). Experiment is also performed on case study 1- flat plate to validate results and experimental results are compared with simulation. Experimental results are close to simulation results. This concludes that proposed method is valid and optimal results are found by using less computational effort without compromising performanceItem OEE analysis for the manufacture of disc brake in local manufacturing industry(UMT, Lahore, 2022) Ahad HameedThe investigations for productivity improvement in the manufacturing industries is essential for the successful existence in the competitive global market and requires a rigorously defined performance measurement system for each manufacturing process in the production line for the manufacture of components. Overall Equipment Effectiveness, OEE, is a key indicator of Total Productive Maintenance (TPM) and provides performance and productivity measurement and the action plans for the improvement of machines in the manufacturing industries. The application of Total Productive Maintenance (TPM) tools and techniques identify the losses and reducing them on a priority basis and hence maximizes the Overall Equipment Effectiveness (OEE). TPM eliminates potential health and safety risks by making machines safe to use and at the same time increase overall equipment effectiveness (OEE). This results in an increased morale and job satisfaction for employees. TPM reduces product losses by improving process instability, equipment availability, and product quality. The current research work aims at the OEE improvement in the production line of disc brake. The production losses at each station of the initial setup are identified. Subsequently the waiting time due to the presence of conflicting requirements in the manufacturing processes is optimized for the productivity growth in the revised and improved setup. OEE improvement in the disc brake production line is suggested through the management of time losses by systematic planning of manufacturing processes and the implementation of Total Productive Maintenance (TPM). The investigations and subsequent corrective actions led to the improvement for low OEE in the auto part manufacturing line in the shortest possible time with very little investment.