Optimization of hole-making operations in manufacturing industry plays a vital role. Tool travel and tool switch planning are the two major issues in hole-making operations. Many industrial applications such as moulds, dies, engine block, automotive parts etc. requires machining of large number of holes. Large number of machining operations like drilling, enlargement or tapping/reaming are required to achieve the final size of individual hole, which gives rise to number of possible sequences to complete hole-making operations on the part depending upon the location of hole and tool sequence to be followed. It is necessary to find the optimal sequence of operations which minimizes the total processing cost of hole-making operations. In this work, therefore an attempt is made to reduce the total processing cost of hole-making operations by applying relatively new optimization algorithms known as shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm for the determination of optimal sequence of hole-making operations. An industrial application example of ejector plate of injection mould is considered in this work to demonstrate the proposed approach. The obtained results by the shuffled frog leaping algorithm and proposed modified shuffled frog leaping algorithm are compared with each other. It is seen from the obtained results that the results of proposed modified shuffled frog leaping algorithm are superior to those obtained using shuffled frog leaping algorithm.
Highlights Tool travel and tool switch scheduling are major issues in optimization of hole-making operations. Many industrial applications such as moulds, engine block, automotive parts etc. requires machining of number of holes. It is necessary to achieve a correct sequence of hole-making operations to minimize tool travel and tool switch and finally to minimize total processing cost. In the present work, we have attempted an industrial application example of ejector plate of injection mould using shuffled frog leaping algorithm and modified shuffled frog leaping algorithm.
Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO) algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.
Applications like boilerplates, food-industry processing separator, printed circuit boards, drum and trammel screens, etc. consists of a matrix of a large number of holes. The primary issue involved in hole-making operations is a tool travel time. It is often necessary to find the optimal sequence of operations so that the total processing cost of hole-making operations can be minimized. In this work, therefore an attempt is made to reduce the total tool travel of holemaking operations by applying a relatively new optimization algorithm known as modified shuffled frog leaping for determining the optimal sequence of operations. Modification is made in the existing shuffled frog-leaping algorithm by introducing three parameters with their positive values to widen the search capability of existing algorithms. A case study of the printed circuit board is considered in this work to demonstrate the proposed approach. Obtained results of optimization using modified shuffled frog leaping algorithm are compared with those obtained using particle swarm optimization, firefly algorithm and shortest path search algorithm.
An electric vehicle battery pack which is a gathering of battery modules which subsequently comprised of the battery cell is a primary source of control transmission for an Electric Vehicle (EV). The inappropriate design of the battery enclosure will cause many genuine issues, such as cracking, causing noise, or battery harm. At the same time, the weight of the battery enclosure is huge; in order to get better the driving range of the electric vehicle and diminish the influence of the battery on the vehicle dynamic performance and acceleration performance, it is essential to carry out the lightweight design of the battery enclosure. This paper reviews the multi-material battery enclosure design optimization, the multi- technologies, and a proficient Battery Management System (BMS) for compact battery pack design used to lightweight battery pack enclosure design; the multi-objective optimization approach for distinctive parameters of battery pack enclosure design optimization by diverse manufacturing techniques.
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