3D PRINTING AND AI-GUIDED SCULPTURE FABRICATION Prerak Sudan, B Reddy, Anand S. Relkar, Vaibhaw R Doifode, Surendra Babu K, Vikas Sagar Shodhkosh Journal of Visual and Performing Arts, 2025 This study looks at how 3D printing and artificial intelligence (AI) are coming together in the field of sculpture manufacturing, focussing on how they are changing the way art is made, how quickly it can be made, and how it looks in general. The research examines how AI-powered design models and computer creativity can aid people in thinking of new ideas by creating complex sculptures with human assistance. In this research the relationship between human intention and computer activity is being reconceptualized in contemporary art practice within a framework of digital aesthetics, machine learning and material science. The theoretical background focuses on how additive manufacturing has evolved in the creative areas, the use of AI-assisted generative design, and the social issues that arise when machine-generated art is produced. The project takes an experimental approach to the generation of led AI models by using a mix of neural networks, computer-aided design (CAD) systems and 3D printer tools to create and test the models. The suggested system design consists of training models, integrating process between artificial intelligence and printers and optimising materials for accurate manufacturing. Comparing sculptures that were made by humans and those that were made by AI can help us understand how to make better statues and come up with new designs. The sample building results show that it is possible to build complex structures that weren't possible before, thanks to the AI-guided 3D printing technology, which also reduces waste and the need for human assistance.
Application of Monte Carlo and regression analysis technique in maintenance management Anand S. Relkar, Prasad R. Baviskar, Milind M. Patil Aip Conference Proceedings, 2018 A major role of any production system is to produce expected product or components at the desired rate, but practically there are many factors that really affect ideal expectations of production rate at shop. To reach this ideal expectations one must analyze the practical factors affecting the process of production. In this paper attempt has been done to identify and analyze the significant factors affecting the production quantity. A regression model of five significant factors affecting production quantity is considered in this paper. The developed regression model is further used to predict the production quantity. Monte Carlo Simulation is used to randomly generate different scenarios of considered factors. After development, Model is able to determine exact production quantity with any input values of significant factors. These randomly generated scenarios are more near to reality. Hence developed methodology can help to bridge the gap between theory and practice. This developed model is very case specific and more generic model can be developed in future. The attempt to integrate regression model of Time between failures, Time to repair, Cycle time, Non availability of manpower and material, Tool change and Setting with Production quantity. Monte Carlo Simulation is scare in nature of the referred literature.
Optimizing & analysing overall equipment effectiveness (OEE) through design of experiments (DOE) Anand S. Relkar, K.N. Nandurkar Procedia Engineering, 2012 Continuous availability of reliable sophisticated equipment with precision is need of the competitive market. Overall equipment effectiveness (OEE) is important performance measure metric for equipment effectiveness. An attempt has been done to measure and analyze existing overall equipment effectiveness of critical machinery producing important automobile components like serration cap, Dowel rod and sequence rod. Which are used by leading automobile company. By measuring the performance of existing system, reference values are obtained for design of experiments. By using MiniTab15 software an experimentation has been done on three factors and two level of OEE. Main effect plots and regression analysis provides information about which is most influencing factor and classic relationship between availability, performance rate and quality rate. Significance of each factor is indicated by P-value in the given analysis. Finally counter plots and response surface method results in to optimized values of three factors of OEE. Simulated values of the output will be useful information to industry.
Correlating failure mode effect analysis (FMEA) & overall equipment effectiveness (OEE) Chandrajit P. Ahire, Anand S. Relkar Procedia Engineering, 2012 To compete in global market, no organization will tolerate losses. Overall Equipment Effectiveness (OEE) is such a performance measure metric which will indicate performance rate with very simple calculations. It considers all important measures of productivity. Implicitly it indicates amount of losses each parameter contributes to reduce productivity. By applying quality improvement tool such as failure Mode and Effect Analysis (FMEA) root cause of any OEE measure can be found out. It will help to improve OEE and correspondingly productivity.In this paper an attempt has been made to establish a relationship between OEE and FMEA. All the parameters of OEE (i.e. Availability, Performance Rate and Quality Rate) are evaluated with respective to FMEA (i.e. severity, occurrence and Detection). Total 32 hypothesis are considered to establish relation between OEE and FMEA. A case study conducted in one of reputed process industry gives very significant insight for OEE improvement. Power of Excel tool is explored in this paper.
RECENT SCHOLAR PUBLICATIONS
Experimental Study on the effect of cleaning agent pressure on the cleaning process DAL Yogesh Keshav More , Dr. Anand Relkar International Journal for Research Trends & Innovation-IJRTI 7 (7), 1566-1571 , 2022 2022.0
Design and Fabrication of Arduino Based Flexible Manufacturing Process on the Desk: 3D Printing NB Khona, BU Chaudhari, PB Ambekar, AS Relkar, AD Lokhande International Journal for Research in Applied Science & Engineering … , 2022 2022.0 Citations: 2
STUDY OF CENTER GUIDING SYSTEM FOR 4 ROLL CALENDERING AS Relkar, VR Pawase, SH Sagar, YD Umare, SH Sagar Advance and Innovative Research, 197 , 2021 2021.0
MATERIAL OPTIMIZATION OF WHEEL RIM USING FINITE ELEMENT ANALYSIS AS Relkar, AD Lokhande, MD Newadekar Advance and Innovative Research, 107 , 2021 2021.0
Risk analysis of equipment failure through failure mode and effect analysis and fault tree analysis AS Relkar Journal of Failure Analysis and Prevention 21 (3), 793-805 , 2021 2021.0 Citations: 47
Application of Monte Carlo and regression analysis technique in maintenance management AS Relkar, PR Baviskar, MM Patil AIP Conference Proceedings 2018 (1), 020015 , 2018 2018.0
Predicting Production Quantity by integrating Monte Carlo Simulation and Regression Analysis AS Relkar International Conference on Manufacturing Excellence (ICMAX-17) , 2017 2017.0
A Survey of factors affectinfg OEE in Engineering Industries AS Relkar International Conference on Manufacturing Excellence, (ICMAX-17) , 2017 2017.0
Reduction of Equipment downtime through FMEA & Root Cause Analysis” ASRKN Nandurkar International conference on science & Technology for sustanable developement , 2016 2016.0
Model Development for Preventive Maintenance and Replacement Policy ASRKN Nandurkar Joint Global Conference on “Democratizing Communications , 2015 2015.0
Optimizing Overall equipment effectiveness through simulation analysis AS Relkar, KN Nandurkar International Conference on Operations Research and Statistics (ORS … , 2012 2012.0 Citations: 2
Risk analysis of equipment failure through failure mode and effect analysis and fault tree analysis AS Relkar Journal of Failure Analysis and Prevention 21 (3), 793-805 , 2021 2021.0 Citations: 47
Design and Fabrication of Arduino Based Flexible Manufacturing Process on the Desk: 3D Printing NB Khona, BU Chaudhari, PB Ambekar, AS Relkar, AD Lokhande International Journal for Research in Applied Science & Engineering … , 2022 2022.0 Citations: 2
Optimizing Overall equipment effectiveness through simulation analysis AS Relkar, KN Nandurkar International Conference on Operations Research and Statistics (ORS … , 2012 2012.0 Citations: 2
Experimental Study on the effect of cleaning agent pressure on the cleaning process DAL Yogesh Keshav More , Dr. Anand Relkar International Journal for Research Trends & Innovation-IJRTI 7 (7), 1566-1571 , 2022 2022.0
STUDY OF CENTER GUIDING SYSTEM FOR 4 ROLL CALENDERING AS Relkar, VR Pawase, SH Sagar, YD Umare, SH Sagar Advance and Innovative Research, 197 , 2021 2021.0
MATERIAL OPTIMIZATION OF WHEEL RIM USING FINITE ELEMENT ANALYSIS AS Relkar, AD Lokhande, MD Newadekar Advance and Innovative Research, 107 , 2021 2021.0
Application of Monte Carlo and regression analysis technique in maintenance management AS Relkar, PR Baviskar, MM Patil AIP Conference Proceedings 2018 (1), 020015 , 2018 2018.0
Predicting Production Quantity by integrating Monte Carlo Simulation and Regression Analysis AS Relkar International Conference on Manufacturing Excellence (ICMAX-17) , 2017 2017.0
A Survey of factors affectinfg OEE in Engineering Industries AS Relkar International Conference on Manufacturing Excellence, (ICMAX-17) , 2017 2017.0
Reduction of Equipment downtime through FMEA & Root Cause Analysis” ASRKN Nandurkar International conference on science & Technology for sustanable developement , 2016 2016.0
Model Development for Preventive Maintenance and Replacement Policy ASRKN Nandurkar Joint Global Conference on “Democratizing Communications , 2015 2015.0
REDUCTION OF TOTAL SUPPLY CHAIN CYCLE TIME IN INTERNAL BUSINESS PROCESS OF REAMER USING DOE AND TAGUCHI METHODOLOGY MPP Kulkarni, AS Relkar
REDUCTION IN TOTAL CYCLE TIME BY VALUE STREAM MAPPING MPP Kulkarni, AS Relkar