Sandhyamayee Sahu

Dissolution kinetics of nickel laterite ore using different secondary metabolic acids

The dissolution kinetics of nickel laterite ore in aqueous acid solutions of three metabolic acids, i.e., citric acid, oxalic acid and acetic acid were investigated in a batch reactor individually. It was determined that experimental data comply with a shrinking core model. The diffusion coefficients for citric acid, oxalic acid and acetic acid were found to be 1.99×10 -9 cm 2 /s, 2.59×10 -8 cm 2 /s and 1.92×10 -10 cm 2 /s respectively. The

A novel swarm optimization technique for partner selection in virtual enterprise

Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared to its continuous counterpart. The method substantially reduces the number of tuning parameters in the algorithm. The algorithm presented include main crucial factors for partner selection such as the running cost, reaction time and running risk and select the partners for various processes that minimizes total cost. The working of the algorithm is demonstrated with the help of a typical example. Exhaustive simulation illustrates the effectiveness of algorithm.

ART based cell formation using combined operation sequence and time

The cell formation (CF) problem mainly deals with clustering of parts into part families and the machines into machine cells. The parts are grouped into part families based on similarities in their manufacturing and design attributes and the machines are allocated into machine cells to produce the identified part families. The zero-one part-machine incidence matrix is commonly used as input to any clustering algorithm. The output is generated in the form of block diagonal structure. Production data such as operation time, sequence of operations, batch size etc. that have significant bearing on smooth flow of materials are not considered in such methods. In this paper, an attempt has been made to develop an algorithm based on adaptive resonance theory (ART) neural network to addresses this issue by considering combination of operation sequence and operation time of the parts to enhance the quality of the solution obtained for the CF problem. A new performance measure is proposed to assess the goodness of the solution quality obtained through proposed algorithm. The performance of the proposed algorithm is tested with example problems and the results are compared with the existing methods found in the literature. The results presented clearly shows that the performance of the proposed algorithm is comparable with other methods for small size problems and better for large size problems.