Hard turning: Parametric optimization using genetic algorithm for rough/finish machining and study of surface morphology

The machining of hardened surfaces can be done even fulfilling the ever stricter accuracy and quality prescriptions, besides the economic efficiency. Decisively, hard machining is highlightedly important in finish processes because the components must meet increased functional demands. Therefore the number and/or the hardness of the hard surfaces on the components is continuously increasing. In practice the demand for such components is high since they are more wear resistant and their tool life may be higher. Today there are several possibilities for finish machining of components having hard surfaces. We have done experiments for hard machining of inner cylindrical surfaces. The examined procedures were as follows: grinding, hard turning, combined machining. The first two procedures (hard turning, grinding) have got different procedure-specific advantages and disadvantages. Combining these two procedures, using-up the advantages of them, the efficiency of the production can be increased. This paper outlines these procedures of hard machining, their applicability, the increase of their efficiency, and the possibilities provided by the combination of the procedures.

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Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study

Decision Science Letters ◽

10.5267/j.dsl.2016.3.001 ◽

2016 ◽

pp. 581-592 ◽

Cited By ~ 22

Author(s):

Amlana Panda ◽

Ashok Kumar Sahoo ◽

Arun Kumar Rout

Keyword(s):

Decision Making ◽

Grey Relational Analysis ◽

Hard Turning ◽

Parametric Optimization ◽

Relational Analysis ◽

Multi Attribute Decision Making ◽

Grey Relational ◽

Ceramic Insert

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Parametric Optimization of Nd:YAG Laser Beam Machining Process Using Artificial Bee Colony Algorithm

Journal of Industrial Engineering ◽

10.1155/2013/570250 ◽

2013 ◽

Vol 2013 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Rajarshi Mukherjee ◽

Debkalpa Goswami ◽

Shankar Chakraborty

Keyword(s):

Genetic Algorithm ◽

Laser Beam ◽

Process Parameters ◽

Nd:Yag Laser ◽

Artificial Bee Colony ◽

Parametric Optimization ◽

Machining Process ◽

Laser Beam Machining ◽

Abc Algorithm ◽

Bee Colony

Nd:YAG laser beam machining (LBM) process has a great potential to manufacture intricate shaped microproducts with its unique characteristics. In practical applications, such as drilling, grooving, cutting, or scribing, the optimal combination of Nd:YAG LBM process parameters needs to be sought out to provide the desired machining performance. Several mathematical techniques, like Taguchi method, desirability function, grey relational analysis, and genetic algorithm, have already been applied for parametric optimization of Nd:YAG LBM processes, but in most of the cases, suboptimal or near optimal solutions have been reached. This paper focuses on the application of artificial bee colony (ABC) algorithm to determine the optimal Nd:YAG LBM process parameters while considering both single and multiobjective optimization of the responses. A comparative study with other population-based algorithms, like genetic algorithm, particle swarm optimization, and ant colony optimization algorithm, proves the global applicability and acceptability of ABC algorithm for parametric optimization. In this algorithm, exchange of information amongst the onlooker bees minimizes the search iteration for the global optimal and avoids generation of suboptimal solutions. The results of two sample paired t-tests also demonstrate its superiority over the other optimization algorithms.

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