Mechanical Engineering

The benefits of risk management in projects are huge. You can gain a lot of money if you deal with uncertain project events in a proactive manner. The result will be that you minimize the impact of project threats and seize the opportunities that occur. This allows you to deliver your project on time, on budget and with the quality results your project sponsor demands. Also your team members will be much happier if they do not enter a "firefighting" mode needed to repair the failures that could have been prevented. In this paper we identified six common risk factors that could impact a project. Some factors are obvious, but some are not and it is important to identify them all. You are encouraged to review them all when planning for project risks. Also In this paper we describe common schedule risk factors. We give you some tools to identify risk and lower its impact, thereby saving your projects from schedule slips.

Crude oil price directly influence the economic conditions of world. This will impact on the airlines operating of aero engines that lead to turbo machinery to future fuel conservation requirements. The continuing effort to improve performance has created in improving the efficiency of current and future gas turbine engines. The fuel efficiency of an aircraft is dependent upon factors: the drag contributed by the air frame, the drag contributed by the engine and the efficiency of the engine itself. In this paper we discuss the latest advancement in gas turbine engines that improves efficiency of the engine from a unit mass of fuel that is burnt. Turbofan engine coupled with planetary gear increases speed of low pressure compressor by three to four folds of fan takes place inside the core of the engine, which includes the compressor, the combustion chamber, and the turbines that extract mechanical energy from the hot, expanding gases. By increasing the fan diameter & by improving the overall bypass ratios up to 12, the fuel efficiency of engine increases to double digit ~15% which is revolutionary in aero engine development history.

Flow Shop Scheduling is the combinational optimization & NP-hard (i.e. Non-deterministic Polynomial-time hard) problems. In Permutation Flow Shops, the sequence of the jobs is same on all machines. In a Flow Shop Scheduling problem with ‘n’ jobs that should be processed on ‘m’ machines. The job can be processed on at most one machine; meanwhile one machine can be processed at most one job. A significant research effort has been committed for sequencing jobs in flow shop to minimizing the make span. Optimization algorithms such as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO) & Neighborhood Search have played a significant role in solving small scale flow shop scheduling problems. In this paper a recently developed Teaching Learning Based Optimization (TLBO) is proposed method to solve the flow shop scheduling problems to minimize the make span. The proposed algorithm is tested on Taillard Benchmark problems and results are compared with Palmer’s & CDS Heuristic methods. The results show that the proposed algorithm is efficient in producing optimal solution and simple, easy to understand.

The use of nanofluids as the operating fluid in the TPCT (two phase closed thermosyphon) significantly improves the heat transfer. In the present study, the performance enhancement of 6063 AA TPCT container material with cerium IV oxide nanofluid is investigated by RSM using Box-Behnken Design (BBD). According to BBD design, the process parameters are heat input (A), inclination angle of TPCT (B), and the flow rate of pure water in the condenser section (C). This work resulted in identifying the optimized set of input parameters and output response of the 6063 AA TPCT.

Press tool manufacturing is one of the widely emerging trends in production area. Basically sheet metal components are produced using press tools. In this work, Design and analysis procedure to develop bending press tool is discussed. The components manufactured using this process exhibits high dimensional accuracy therefore automobile and aircraft firm depend largely on press tools. The purpose of carrying out analysis is to prevent the costly tryouts and thus optimize the quality and rate of production.

As an engineer we need to solve the problems facing the present society. One among them is pollution it is very serious problem. One of the major cause for the pollution releasing of methane gas to the environment from the vehicle. To reduce this folding electrical cycle is a small effort which helps to reduce the pollution and provide more comforts to the rider. In this cycle we are arranging lithium battery to reduce the mechanical work done by the rider & folding experiences the rider more reliable,comfortable & portable to the rider

The objective of this paper is to predict the failure load of the composite laminates during tensile loading using an online Acoustic Emission (AE) monitoring and Artificial Neural Network. Bidirectional glass/epoxy laminates were subjected to tensile loading. The laminates were made for 12 layers of bi-directional glass mat in an epoxy matrix. The AE data recorded during the tensile testing was used to predict the failure load. The parameters such as amplitude, count, duration, energy, peak to count and rise-time were used for the analysis. Feed forward back propagation neural network model was generated from acoustic emission cumulative counts data taken during loading of bi-directional glass/epoxy tensile specimens. Cumulative counts recorded up to 50% and 75% of the failure load were used as the input data for simulation. The results show that the developed non-destructive method is capable of predicting the failure of composites subjected to tensile loading with an error of 3.5% and 7.6% for cumulative counts of 50% and 75% of loads respectively.

Damping is the material's ability to dissipate elastic strain energy during cyclic loading. Materials with high damping capacity are significant in the present day scenario for transportation and other industrial applications. The development of materials with high damping capacity is one of the efficient measures to reduce vibrations, thereby noise. Low weight materials like aluminum and magnesium have excellent mechanical properties, but poor in damping.

The study has been done on the basis of questionnaire survey in the twenty-degree engineering colleges from West Bengal and foreign countries by random selection, ten colleges from each to measure the current or baseline performance level. The feedback for this questionnaire survey has been considered independently for service providers such as administrators, faculties, other supporting staff as well as students who receive these services and are direct customers. A total of 2168 persons have been surveyed from the 20 colleges. The baseline or current performance level of the colleges has been assessed based on the sigma level through quantification of the survey questionnaire consisting of eight enablers. Each enabler contains several questions or drivers. A seven-point scale has been designed for each driver ranging from “Unsatisfactory” to “Outstanding”.

Sand inclusion is an important defect in Cast Iron castings. On an average this defect is almost thirty to forty per cent of the total defects occurring in a foundry. Sand inclusion is undesirable since it results in reduction in the strength of the casting and bad finish of the casting surface. More than hundred parameters are responsible for sand inclusion and hence it is difficult to control defect during casting. A detailed Literature review of the previous work mostly on sand inclusion for almost last fifty years is done in this paper to find appropriate parameters for defect formation of sand inclusion. From the literature review it is found that the exact remedy for sand inclusion is not easy. The papers describing different techniques like Quality Function Deployment, cause and effect diagram, Design of Experiments etc. are also referred for finding the appropriate parameters responsible for sand inclusion. Corrective action should be taken on responsible parameters to eliminate the defect and improve quality of ferrous castings.