ANN MODELLING OF SMALL HOLE DRILLING ON MONEL METAL BY USING ELECTRICAL DISCHARGE MACHINING

The selection of best combination of the process parameters in small hole drilling by Electrical Discharge Machining for an optimum material removal rate with a reduced tool wear rate can reduce machining time and yield better performances. Artificial Neural Network (ANN) has emerged as a powerful tool for modelling complex processes is used for achieving better performance parameter. Artificial Neural Network (ANN) with back propagation algorithm have been used for optimizing and modelling process. The experiments have been designed according to Taguchi L9 orthogonal array. The input parameters were considered for conducting experimentation are namely Discharge Current, Pulse off time and Pulse on time respectively. The performance measures were Material Removal Rate (MRR) and Tool Wear Rate (TWR). ANN models have been developed with varying number of neurons in the hidden layer from 5 to 10. It was found that one hidden layer with 9 neurons predicted the best results. The predicted values were compared with actual experimental results and the predicted values were almost equal to the expected with very less error.Â

MAINTENANCE STRATEGY EVALUATION BASED ON AHP – TOPSIS

This paper presents an application of Analytical Hierarchy Process (AHP) is combined with Technique for Order Preference by Similarly to Ideal Solution (TOPSIS) model for selection of the best maintenance strategy for pump in paper industry. AHP is used to compute the criteria weights whereas TOPSIS is used to ranking the maintenance strategy alternatives. This study focuses on four maintenance strategies such as Corrective Maintenance (CM), Predictive maintenance (PM), Time based preventive Maintenance (TM) & Condition Based Maintenance (CBM) and four main criteria such as safety, cost, added value and feasibility are used to evaluate the optimum maintenance strategy

Decentralised green power generation using methyl esters of non-edible oils

Istraživački radovi o sustavima obnovljivih izvora energije za elektrifikaciju sela vrlo su intenzivni posljednjih godina. U udaljenim područjima neka su sela još uvijek izvan dosega električne energije jer je nemoguće povezivanje mrežnog sustava. U svijetu oko dvadeset posto svjetske populacije živi bez struje. Za poboljšanje ruralnog življenja, uporaba zelenih izvora energije obuhvaća veću mogućnost zapošljavanja, energetsku sigurnost i smanjenje učinaka staklenika. Konvencionalna metoda lokalne proizvodnje koristi dizel generator koji nije prihvatljiv za okoliš. Biogoriva su optimistični izbor za ispunjavanje ovog zahtjeva. Biodizel je obnovljivi izvor koji ima gotovo jednaku učinkovitost kao i konvencionalni petrodizel. Ovaj rad pokusno istražuje mješavine biodizela (dizel + biodizel) dobivene od nejestivih ulja kao alternativni izvor energije za pogon dizelskog generatora. U ovoj studiji se uzima u obzir sedam metilnih estera ekstrahiranih iz nejestivih ulja pongamije (indijske breze), jatrobe (jatrophe), mahuae, mesua ferrae (nageškara), sjemenki lana, neema (nim drveta) i sjemenki pamuka. Performanse generatora kao što su regulacija napona, frekvencija, potrošnja goriva, učinkovitost i emisijske značajke nalaze se u različitim uvjetima opterećenja. Na temelju opažanja, nađeno je da je ulje pongamije dobro alternativno gorivo za proizvodnju električne energije.Research work on renewable energy systems for rural electrification have been quite intensive in recent years. In remote areas, some villages are still not reach of electricity because providing grid connection is impossible. Approximately twenty percent of global population are living without electricity in the world. For enhancement of rural livelihood, use of green energy sources encompasses greater employment opportunity, energy security and minimizes the greenhouse effects. The conventional method of local generation uses diesel generator that is not environment friendly. Bio-fuels have been the optimistic choice to meet this requirement. Biodiesel is a renewable source which has nearly the same efficiency as conventional petro-diesel. This paper experimentally investigates biodiesel blends (Diesel+Biodiesel) derived from non-edible oils as an alternative energy source for operating the diesel power generator. In this study, seven methyl esters extracted from non-edible oils of pongamia, jatroba, mahua, mesuaferra, linseed, neem and cotton seed are considered. The generator performances such as voltage regulation, frequency, fuel consumption, efficiency and emission characteristics are found in various load conditions. Based on the observations, pongamia oil was found to be a good alternative fuel for power generation

Selection of maintenance policy for textile industry using hybrid multi‐criteria decision making approach

PurposeThe purpose of this paper is to focus on the use of analytic hierarchy process (AHP) under fuzzy environment and technique for order preference by similarity to ideal solution (TOPSIS) to select an optimum maintenance strategy for a textile industry.Design/methodology/approachFirst by using improved AHP with fuzzy set theory, the weight of each criterion is calculated to overcome the criticism of unbalanced scale of judgments, uncertainty, and imprecision in the pair‐wise comparison process. Then this paper introduces a model that integrates improved fuzzy AHP with TOPSIS algorithm to support maintenance strategy selection decisions.FindingsAn efficient pair‐wise comparison process and ranking of alternatives can be achieved for maintenance strategy selection through the integration of AHP with fuzzy set theory and TOPSIS.Originality/valueThe paper points out a new insight of multi‐criteria decision making techniques to select optimum maintenance policy for a process industry with the use of a case study.</jats:sec

Integrated hazard and operability study using fuzzy linguistics approach in petrochemical industry

PurposeThis paper aims to investigate the failure modes present in the dangerous operations and modify processes. After the identification of potential failures, prioritization will be made to rank them for quick attention and immediate correction in the operation/modification.Design/methodology/approachThe methodology utilizes the strength of hazard and operability (HAZOP) study and failure mode and effect analysis (FMEA) to identify and prioritize the hidden potential failures present in the system. Fuzzy linguistics approach has been applied to enhance the performance of the study. This study correlates HAZOP study, FMEA and fuzzy system.FindingsThis proposed technique is used to find the better ranking of the failure modes. Risk priority number and fuzzy weighted geometric mean of the risk factors are used to improve the performance of the risk evaluation. This makes the assessment easier to be carried out effectively for critically operated systems.Practical implicationsThis proposed approach could be very useful for the systematic and rational risk assessment of passive systems.Originality/valueA new decision‐making approach is used to prioritize the failure modes present in the process industry with use of a case study.</jats:sec