International Journal of Mechatronics and Manufacturing Technology

Authors: Adarsh Kulkarni, Nagamadhu M, S K Sachin, Vishaldutt V Kohir

Abstract: A study has been made in identifying and isolating effects of cutting conditions on cutting forces. Machining tests were conducted using sharp tool and the effects of cutting parameters were studied. In the presented study experiments were conducted on EN8 steel at different cutting parameters. Here chatter starting point length is measured from the free edge of the work piece. Experiments were conducted on a precision center lathe and the influence of cutting parameters was studied using DOE. Based on the main effects plots obtained through full factorial design, optimum level for surface roughness and cutting force were chosen depth of cut, and the interaction of feed and depth of cut significantly influenced the variance. In case of surface roughness, from the three levels of cutting parameters considered Linear regression equation of cutting force has revealed that feed, the influencing factors were found to be feed and the interaction of speed and feed. As turning of EN8 steel using HSS is one among the major machining operations in manufacturing industry, the revelation made in this research would significantly contribute to the cutting parameters optimization.

Keywords: EN8, Surface Roughness, Design of Experiments (DOE)

Authors: Shalini Verma, Satish Kumar

Abstract: The global increasing demand for refrigeration in field of refrigeration airconditioning, food preservation, vaccine storages, medical services, and cooling of electronic devices, led to production of more electricity and consequently more release of CO2 all over the world which it is contributing factor of global warming on climate change. The prices of energy have been increasing exponentially worldwide. Industrial Refrigeration is one of the most energy consuming sector. What if a refrigeration system is designed which uses no energy or minimal amount of energy? The solution lies in absorption refrigeration system. By producing an absorption refrigeration system we are not only cutting down the energy costs but also preserving our environment. This refrigeration system doesn’t use any of the CFCs so our ozone layer is safe. This paper studies about LiBr/water based absorption refrigerator designed for rural application and applies solar rays based on reverse seebak effect.

Keywords: Advanced Refrigerator, LiBR/water, Seebak Effect

Authors: S.Ramanjaneyulu, R.Ramakrishna, V. Krishna Kanth

Abstract: This work made an attempt to summarize about contact stresses developed in a mating helical gear which has involute teeth. Face width and helix angle are important geometrical parameters in determining the state of stresses during the design of gears. The analysis of contact stresses has become popular as an area of research on gears to minimize and reduce the failures. The present investigation is carried out to make use of helical gear, by analyzing the contact stresses for different helix angles (0˚, 5˚, and 15˚) and (15 mm, 20 mm, and 25 mm) Face width. A Three-dimensional solid model is generated by Solid Works which is powerful and modern solid modeling software. The numerical solution is done by Ansys, which is a finite element analysis package. The analytical approach is based on contact stress equation, to determine the contact stresses between two mating gears. The results obtained from Ansys values are compared with Analytical results are in close agreement. Results advices that with increase in helix angle and face width, contact stresses decreases for a pair of helical gears. The present analysis is useful in quantifying the above said parameters that helps in safe and efficient design of the helical gear.

Keywords: Contact Stress, Helix Angle, Face Width, Friction Coefficient, ANSYS-14.5, VB Interface.

Authors: Ajeet Rathor , Piyush Chandra, Kamlesh Rajbhar

Abstract: The evolution of manufacturing paradigms has witnessed a shift from centralized production to flexible, distributed networks enabled by cloud technologies. Cloud Manufacturing (CM) integrates cloud computing, Internet of Things (IoT), and cyber-physical systems to provide scalable, on-demand manufacturing resources. Distributed Production Networks (DPNs) complement this by enabling geographically dispersed facilities to collaborate efficiently. This paper reviews the principles, architecture, communication models, and challenges of CM and DPNs. Emphasis is given to resource virtualization, real-time scheduling, quality control, and supply chain integration. The review also highlights recent trends in AI-driven decision making, predictive maintenance, and resilience in distributed manufacturing. The paper concludes with insights into the future of smart, connected manufacturing ecosystems.

Keywords: Cloud Manufacturing, Distributed Production Networks, CyberPhysical Systems, IoT, Resource Virtualization, Smart Manufacturing, Production Scheduling

Authors: R. K. Sharma, P. Tiwari, N. A. Khan, S. Verma

Abstract: Industrial robots are widely used in manufacturing environments to perform repetitive and precise operations. However, traditional robot control systems rely on fixed models and pre-programmed trajectories which are not suitable for dynamic and uncertain industrial conditions. Recently, artificial intelligence (AI) based adaptive control strategies have emerged as an effective approach to enhance flexibility, robustness, and autonomy in robotic systems. This paper presents a comprehensive review on AI-driven adaptive control for industrial robots, focusing on machine learning, reinforcement learning, neural networks, and hybrid intelligent control frameworks. The study explains how AI enables robots to adjust control parameters in real time based on environmental variations, payload changes, and task uncertainties. Different adaptive control architectures, learning methods, and industrial applications such as assembly, welding, and material handling are discussed. Advantages, limitations, and practical challenges in industrial deployment are also analysed. The paper concludes that AI-based adaptive control significantly improves accuracy, safety, and productivity of industrial robots, though issues like training data requirements and computational cost remain important considerations.

Keywords: Industrial robots, adaptive control, artificial intelligence, reinforcement learning, neural networks, intelligent robotics, automation.

Authors: Anil Kumar Deepati, Arun K. Kadian, Arpan K. Mondal, Pankaj Biswas

Abstract: The parametric analysis on friction stir welding of dissimilar aluminium alloys i.e. AA5083- AA1100 using different tool geometries were performed with experimentation. A multi response optimization problem was developed to perceive optimal process parameters to achieve better mechanical properties. Taguchi’s L16 orthogonal array design and the signal to-noise ratio (S/N ratio) concept were selected to optimize the objective functions with the experimental results. The objective functions were chosen with respect to process parameters i.e. tool rotational speed, welding speed, tool shoulder diameter, and tool pin type. The Taguchi’s approach followed by the Grey relational analysis was successfully applied to solve this multiresponse optimization problem. The ANOVA method was used to evaluate the overall output of various factors considered and optimal results were confirmed with additional experiments. The current study obtained the application viability of the Grey Taguchi method for the continuous enhancement of the weld quality in the manufacturing sector.

Keywords: FSW, AA5083, AA1100, Orthogonal array, Signal-to-noise ratio, Taguchi approach.

Authors: D.D. Mondal, Ajit Bhandare, Shubham Bele, Prasanna Abhang

Abstract: This project presents a alternative system for remote monitoring system based on the SCADA model (Supervisory Control And Data Acquisition), specifically developed for automated production processes in a various automated company or various companies. Our proposed system also include other typical SCADA functionalities, namely alarms management, process trending, data logging and remote monitoring of various functionalities or parameter. In this proposed system we are using PIC microcontroller for processing of data and other parameters. We are going to use ESP8266 wireless fidelity module, for sending data wirelessly to server. Whole system architecture will communicate wirelessly with PC or controlling device. Hence, processes at hazardous areas can be controlled with more accuracy and better safety using this system.

Keywords: Sensor, Industrial automation, Scada, Microcontroller

Authors: A. Sreenivasa Rao, K Venkata Rao

Abstract: Finite element simulations have been utilized in analyses of machining process for several decades. This paper presents the development of a cutting force model for end milling process under various cutting conditions and the tool wear is measured by Scanning Electron Microscope (SEM).This novel approach combines the concept of experimental design and finite element modeling of the cutting process which allows for a fairly accurate prediction of cutting forces with a significantly lower computational cost. The simulated results are compared against the experimental observations. The results have shown that the material AISI 316 Stainless steel has affects on cutting forces and tool wear. In cutting approach, Deform 3Dv6.1 software is used to simulate the milling process. The simulation and experimentation is performed based on Taguchi design of experiments. In this research, three dimensional finite element modeling and simulation issues for vibration assisted milling are explored in detail. Machine dynamic effects are taken into account to predict the outcomes such as tool wear and cutting forces. The model can be implemented in an online tool wear monitoring system which predicts the actual state of tool wear in real time by correlating cutting force variations during machining. The comparisons of simulations with experimental results demonstrate their predictive capability. From the results, useful conclusions may be drawn, and it can be stated that the proposed models can be used for industrial application.

Keywords: End milling, Cutting force, Tool Wear, Machining, Metal cutting, Modeling.

Authors: Anirban Mukherjee, K. Ramesh Babu

Abstract: Lean manufacturing is a systematic approach aimed at minimizing waste while maximizing productivity and quality in industrial operations. Originating from the Japanese manufacturing philosophy, lean principles have been widely adopted across global industries to improve efficiency, reduce costs and enhance customer satisfaction. This paper presents a comprehensive study on lean manufacturing principles, tools, implementation strategies, industrial applications and future trends. The integration of lean practices with modern technologies such as Industry 4.0 and digital manufacturing is also discussed.

Keywords: Lean Manufacturing, Waste Reduction, Continuous Improvement, Industrial Engineering, Productivity

Authors: Soumen Chakraborty, K. Rajasekar

Abstract: Computer-Aided Manufacturing (CAM) has revolutionized industrial production by integrating computer technologies with manufacturing processes to achieve precision, efficiency and automation. CAM systems enable the conversion of digital product designs into machine-readable instructions for automated production. This paper presents a comprehensive analysis of CAM principles, system architecture, applications, advantages, challenges and future trends. The role of CAM in smart manufacturing and Industry 4.0 environments is also discussed.

Keywords: Computer-Aided Manufacturing, CNC Machines, Automation, Smart Manufacturing, Industry 4.0

Authors: S. Harishankar, Subhajit Dey

Abstract:Computer Numerical Control (CNC) machining has revolutionized modern manufacturing by enabling precise, automated and repeatable production processes. CNC systems use programmed instructions to control machine tools such as lathes, milling machines, routers and grinders. This paper presents a comprehensive study of CNC machining technology, including its evolution, working principles, machine components, programming techniques and industrial applications. The integration of CNC with Industry 4.0 technologies such as IoT, artificial intelligence and cloud manufacturing is also explored. The study highlights performance advantages, operational challenges and future developments in CNC-based manufacturing systems.

Keywords: CNC Machining, Automation, Manufacturing Technology, G-Code Programming, Smart Manufacturing

Author: Prasanta Kumar Samal

Abstract: This work has been done to realize a piezoelectric ultrasonic transducer, almost from scrap materials. The shape and size of the device were determined by considering practical limitations and for the ease of fabrication. The device was realized by conventional manufacturing processes. An aluminum plate was clamped in between two massive acrylic plates. These two massive plates having central holes were clamped together with nuts and bolts. This makes the aluminum plate as a diaphragm with fixed boundary condition at the circumference of the central hole. Two Lead (Pb)-Zirconium (Zr)-Titanate(Ti) (PZT) patches were glued unto the aluminium plate on its two faces concentric with the central holes of the two massive plates. The transducer can act both as an actuator and a sensor. Two PZT patches are meant for actuation and sensing of the vibration of the aluminum plate. The finite element analyses were performed using the commercial package ANSYS and plotted in MATLAB. The frequency response of the device was obtained from harmonic analysis in ANSYS. The actual natural frequency was determined experimentally using Laser Doppler Vibro-meter (LDV) and compared.

Keywords: Design, Fabrication; Characterization; Piezoelectric; Ultrasonic Transducer.

Author: Anjana Joshi

Abstract: Structural testing of aircraft components involves extensive use of electro hydraulic actuators. Electro hydraulic actuators can be operated in either load or position control modes. For precise control of load and position, feedback elements such as a load cell and potentiometer are used respectively. Structural testing of aircraft structural components mainly involves the simulation of aerodynamic loads. Aerodynamic loads are applied using Electro-hydraulic servo actuators.

Keywords: Data Acquisition; SCADA, remote monitoring

Authors: R. S. Umamaheshwar Rao,  Dr. G. Chandra Mohan Reddy

Abstract:

Polymer based composite materials are being used extensively for the development of a wide spectrum of products. The demands for many applications need a set of properties that cannot be full fill by single polymer. One of the methods to satisfy these demands is to mix two or more polymers. The compounds so formed are generally known as polymer blends. Polymer blending has by now emerged as a well-established route to synthesize specialized polymer systems. Well known examples of blends include impact modified and toughened polymers, where polymers with different glass transition temperatures are combined. Many blends are used in the industries, where specific polar or non-polar polymers are mixed in order to increase the resistance against the transport of water vapour and gases. In the present paper mechanical properties of the nano particle reinforced phenol formaldehyde (PF) composites are studied, for which water soluble phenol formaldehyde composites (PFC) are prepared by solvent casting technique, with varying chitin loading percentage. To optimize the chitin loading, on the bases of its mechanical properties, chitin whisker loaded samples were studied. Nano Chitin particle loaded Phenol Formaldehyde (PF) composites were prepared, varying from 0 to 1.5 % nano chitin by weight, in a variation of 0.5% chitin in the composite. The study showed that the nano chitin loaded PF with 0.5% chitin nano particles have the highest tensile strength and the percentage elongation for the same sample were high. Hence the optimum percentage loading for the composites were decided to be for those having 0.5% chitin loading.

Keywords: Chitin, Nano composites, Tensile Strength, Maximum force, Elongation at Break.

Authors: G. Gopala Krishna, P. Ram Reddy, M. Manzoor Hussain

Abstract: Aluminium alloy applications are increasing day by day because of many attractive features. The combination of reduction of weight and cost is one of the attractive features of these alloys. Aluminium alloys are the best choice for the reduction of weight and as well as the cost and readily replicable steals in many applications. Friction Stir Welding (FSW) process is an efficient and cost-effective process for welding aluminium and aluminium alloys. This process gaining more importance due to a better quality of the joint as it has no effect on the parent metal. This process utilises a non-consumable rotating tool to generate frictional heat between the tool and the abutting surface of the workpiece to accomplish the process. Being a is solid state welding process it offers various advantages like low distortion, absent of melt-related defects, high joint strength etc., as compared to conventional fusion welding processes. The present butt jointed FSW experimental work initially compared tensile properties of similar (AA6351 with AA6351) and dissimilar (AA6351 with AA5083). Later the effect of impurities (copper and brass) in thin sheet form (0.1 mm thick), inserted in between two similar aluminium alloy (AA6351 with AA6351) combinations during FSW. Tensile test results of similar aluminium alloy combinations using strip (copper and brass) material and without strip material were also compared.

Keywords: Friction Stir Welding, Tensile behaviour, Aluminium AA6351 alloy, Copper and Brass.

Authors: Sailesh Banrjee , Ansul Chandra , Dinesh Tiwari

Abstract: In modern manufacturing, achieving high-quality products while maintaining efficiency is a critical challenge. Traditional quality control methods rely heavily on human inspection and periodic sampling, which are often timeconsuming and prone to errors. The emergence of smart manufacturing, characterized by interconnected systems, Industrial Internet of Things (IIoT), and advanced analytics, has enabled a shift towards data-driven quality control (DDQC). By leveraging real-time sensor data, machine learning algorithms, and predictive analytics, manufacturers can detect defects early, optimize production processes, and reduce waste. This paper reviews recent developments in data-driven quality control, discussing sensor integration, data analytics techniques, predictive modeling, and case studies in smart manufacturing. Challenges and future research directions are also highlighted to guide the next generation of quality assurance strategies.

Keywords: Data-driven quality control, smart manufacturing, Industrial IoT, predictive analytics, process optimization, machine learning.