http://localhost:8080/xmlui/handle/123456789/307 2026-06-23T06:19:27Z http://localhost:8080/xmlui/handle/123456789/2945 Title: Improving the quality characteristics of abrasive water jet machining of marble material using multi-objective artificial bee colony algorithm Authors: Pawar, P. J.; Vidhate, U. S.; Khalkar, M. P. Abstract: Although abrasive water jet machining has proved its capabilities for cutting marble material in a most economic and environment friendly manner, is facing serious issues related to dimensional inaccuracy and striation marks. This has put limit on its applications. Also, due to complex nature of abrasive water jet machining pocess, it is very difficult to control all three quality factors i.e. kerf taper, kerf width, striation marks simultaneously to achieve desired quality. This work therefore deals with multi-objective optimization consideringthree objectives as: minimization of kerf width, minimization of kerf taper, and maximization of depth of striation free surface in abrasive water jet machining process. The response surface modeling is used to establishthe relation between various input parameters such as stand of distance, traverse speed, water pressure, and abrasive flow rate, with objectives mentioned above. Application of well-known meta-heuristics named artificial bee colony algorithm is extended to multi-objective optimization with posteriori approach by incorporating the concept of non-dominated sorting. Set of Pareto optimal solutions obtained by this proposed approach provides a ready reference for selecting most appropriate parameter setting on the machine with respect to objectives considered in this work. 2017-12-11T00:00:00Z http://localhost:8080/xmlui/handle/123456789/2920 Title: Material flow optimisation of production planning and scheduling problem in flexible manufacturing system by real coded genetic algorithm (RCGA) Authors: Pawar, P. J.; Bhosale, K. C. Abstract: In a loading problem of flexible manufacturing system (FMS), part type selection and operations allocation are two critical problems. The total completion time of a product for the selected process plan in the system can be minimum for the loading problem. But, in a real time scheduling system, this process plan may not be optimum because of consideration of waiting time of product and machine. So, the total completion time and thereby the material flow of the selected process plan in the FMS may be high. Due to this problem an integrated approach of part type selection and an operation allocation problem i.e. production planning problem and scheduling problem is considered to optimise material flow in FMS. Loading and scheduling problems are NP-hard in nature. So, to solve complex problems like this, real coded genetic algorithm (RCGA) is used which overcomes some limitations of genetic algorithm. It is observed that, the results of optimisation using RCGA outperforms those obtained by earlier researchers. 2018-03-17T00:00:00Z http://localhost:8080/xmlui/handle/123456789/1990 Title: Parametric optimisation of abrasive water jet machining of glass fibre reinforced plastic composite using non-dominated sorting genetic algorithm-II Authors: Mali, Anil Abstract: Machining of glass fibre reinforced plastic (GFRP) possesses several challenges; it is completely different from metal machining. Abrasive water jet machining has proved to be an interesting manufacturing process to machine GFRP in environment friendly manner. In this paper, experimentation is conducted and mathematical model has been developed to establish the correlation between process variables: water jet pressure, traverse rate, abrasive mass flow rate and standoff distance with performance measures: surface roughness, kerf width and kerf taper angle using response surface methodology. A well-known multi-objective optimisation method, non-dominated sorting genetic algorithm-II, is applied to obtain the set of Pareto-optimal solutions, which can be used as a ready reference by the process engineers. Rarely if ever, multiple responses are considered but that too are attempted with priori approach considering finite solutions. Whereas in practice, the problem has to be dealt with infinite solutions with posteriori approach, which is attempted in the proposed method 2017-02-09T00:00:00Z http://localhost:8080/xmlui/handle/123456789/1646 Title: Shielded Metal Arc Welding Electrode Selection Using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method Authors: gangurde, bansode Abstract: An important factor in welding process is selection of appropriate welding electrode. If a wrong welding electrode is selected then it may give rise to various welding defects and ultimately lead to failure of weld.In this paper, best welding electrode is selected from available alternatives of general purpose electrodes for mild steel for Shielded Metal Arc Welding process (SMAW). The selection is done by using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The results are then compared with other Multi Attribute Decision Making (MADM) methods; Simple Additive Weighing (SAW), Weighted Product Method (WPM), Modified TOPSIS. The best ranked electrode by all the methods is then selected as the best welding electrode from available alternatives 2017-04-11T00:00:00Z