International Journal of Mechatronics and Manufacturing Technology

Authors:- Chitra Khandelwal, Namitha Shivanna, Dr. N. P. Shivashankar

Abstract:- Drinking water has recently emerged as the most pressing issue confronting practically the whole planet. It is a chronic issue of paramount importance, especially in a country like India that has gotten little attention. Although individuals can handle water, the quality of drinking water appears to be an issue, which eventually impacts the body's general health. While everyone around the world recognises the significance of Himalayan water and its attributes as "drinking water," the research looks into how water accessible in households may be transformed into the greatest possible drinking water with the necessary qualities. One method for achieving health is to consume alkaline water. There has been very little study done on it. As a result, working on the technology to obtain the needed alkalinity of the output water was viewed as a problem. This technique may supply the user with not just alkalinity but also any pH value within the given range. Water ionisers used to produce varied pH levels are relatively costly in foreign nations due to the use of platinum sheets as electrodes. This research focuses on replacing platinum electrodes with SS316 plates as electrodes to get water with varying pH levels.

Keywords:- Ph Values, Low cost water ionizer, SS316L plates, Drinking water.

Authors:- Gopiraja Parimi, Nazeer Shaik, Ravi Teja Appikonda

Abstract:- The majority of machine components may be produced using any of the many manufacturing processes, such as forging, machining, casting, or welding. The manufacturing technique chosen is determined by the production costs of the options for specific parts. Turning, grinding, lapping, and other surface machining operations are widely used in all production units to produce high-quality components. The primary goal of this project is to design and build a suitable cylindrical grinding machine attachment for turning cylindrical rods. It shortens the machining time required to grind cylindrical rods in a cylindrical grinding machine. This attachment is particularly cost-effective when compared to all the other attachments that revolve and grind at the same time.

Keywords:- Manufacturing Technique, Tool Attachment, Turning, Grinding.

Author:- Rasel Hossain

Abstract:- This article talks about drones and their uses, first discussing the construction of the drone, the most important components of which are the frame, propeller, engine, power system, electronic control, and communication system. A drone is a type of aircraft. A drone is also known as an unmanned aerial vehicle (UAV). A drone is "unmanned" because it doesn't need a pilot on board to fly it. Due to the popularity of drones and the fact that many of them are easy and cheap to buy, it is generally expected that the ubiquity of drones will increase significantly in the next few years. The main danger of using a drone is the fall of a drone from a great height, which can be caused by battery discharge, damage due to weather conditions (low air temperature, rain), or hitting an obstacle (trees, buildings, high-voltage lines). The US military has used drones since the mid-1990s. Since the beginning of 2013, many people have started flying drones for fun.

Keywords:- Drone Technology, GPS, Unmanned Aerial Vehicle, Aircraft

Authors:- Dr. Santoshi Sakharani, Rajkailsh Kothari, Promila, Tejas Bhosale 

Abstract:- The requirement for consistent quality, standardization, safety, and low-cost medical components has become a significant challenge for industries' survival in the global medical component market. Companies' applications are heavily reliant on the success of design, manufacturing, and marketing strategies; this is the only way to achieve market success, and research and development teams should be considered as well. Different companies have been established to meet these requirements in order to remain competitive in the market. Frequently, the design and manufacturing operations used to produce medical plastics for the health care market must be adjusted on a daily basis in order to meet increasingly stringent, government-regulated, bio-medical requirements, in addition to all other market pressures. As a result, medical plastics are constantly looking for more systematic ways to improve product quality and produce more at a lower cost, as it has now become an important factor to consider in accordance with customers. Plastic is now used to replace MS, aluminium, glass, and other materials in all manufacturing industries. Because of its ease of manufacture and low cost, aluminium protective caps have largely replaced plastic protective caps in pharmaceutical industries.

Keywords:- Protective caps, intravenous fluid protective caps, intravenous fluids, Medical caps

Authors:- Hemant Shinde , Neha Dhiman, Swati Patil

 

Abstract:- The experimental and FE modal analysis of an intermediate shaft utilised in an automotive gear box are presented in this work. The natural frequencies are calculated using an FFT analyzer throughout the experiment. PRO-E is used to create the three-dimensional finite element model. ANSYS workbench is used to mesh the model. The three fundamental bending modes are recovered throughout the study. The findings indicate that the intermediate shaft is not running at critical speed. The finite element model correlates well with the FFT results and may be used as the intermediate shaft's baseline model.

Keywords:- Finite Element Analysis, FFT analyzer, ANSYS workbench 

Authors:- Pallavi Maharu, Sunita Yamgar, Sanket Dhariya

Abstract:- Glass Fiber Reinforced Polymeric (GFRP) Composite materials have demonstrated key advantages in many fields from Aerospace to Sporting Goods. An efficient design of FRP Composites requires detailed understanding of material and the way of testing. This paper discusses the concepts of Overview, Characterization, Fabrication, Fatigue Testing using Digital Image Correlation (DIC) Technique, Microscopic study using Scanning Electron Microscopy (SEM) and composite repair of continuous GFRP well known as Refractory Ceramic Fiber (RCF) Composites at different fiber orientations (00,+450,-450,900) etc. which tends to complete definition of a Research Problem. This paper provides a scope to young researchers to know the usage of DIC technique in their work so that efficient design can be done which fulfills all the criteria’s.

keywords:- Glass Fiber Reinforced Polymeric (GFRP) Composites; Fatigue, Digital Image Correlation (DIC) Technique; Composite repair; Scanning Electron Microscopy (SEM); Continuous Fiber; Refractory Ceramic Fiber (RCF).

 

Authors:- M. Muthukumar, K. Vijaylakshmi

Abstract:- A coating is a layer of material deposited on a substrate that improves surface properties such as corrosion and wears resistance. There are numerous coating methods available for depositing many different material types at thicknesses ranging from a few microns to several millimetres. The literature on why the PVD process is appropriate, types of PVD methods, their processes, applications, and challenges have been reviewed in this paper. Many coating processes are available, but they are limited to coating only a few materials. PVD coating technology, also known as green coating technology, is highly focused on environmental protection and covers a wide range of coating materials. Many parameters influence PVD (sputtering process) experimental work, such as coating thickness, sputtering gas, gas flow rate, sputtering power, and so on. Carbon nanotubes (CNTs) are a type of carbon that exists between fullerene and flat graphene sheets. It has a structure made up of carbon atoms arranged in one or more cylindrical layers and joined by covalent bonds in a hexagonal pattern to form a hollow tube. CNTs have a very high tensile strength, wear resistance, and thermal conductivity due to their structure.

Keywords:- Green coating technique, Carbon nanotubes (CNT), HSS cutting tool, Coating cutting tool, PVD Sputtering process

Authors:- Kavita Soni, Kritika Gupta

Abstract:- The dispersion of jute nanofibres inside an epoxy polymer matrix has been used to investigate polymer-based nanocomposites. Thermal properties of a composite are critical in assessing product performance and forecasting processibility features of polymers in certain applications. The thermal behaviour of the interface between nanofiber reinforcement was investigated using thermogravimetric analysis and differential scanning calorimetry. The inclusion of nanofibres with varying weight percentages (1wt. percent to 5wt. percent) has been examined and compared to base composites. The addition of jute nanofibres considerably improves the thermal stability of nanocomposite. The nanofibre reinforcement between the matrix resin molecules provided some thermal degradation resistance. DMA measurements are performed with a single frequency and constant deformation amplitude while the temperature is varied. Measurements that vary the amplitude of deformation or use several frequencies give additional information. The dynamic characteristics are represented in terms of storage modulus, loss modulus, and damping factors, all of which are temperature, time, and frequency dependent. The dispersion of nanosized fibres inside polymer matrices has a substantial impact on their physical characteristics. The interface macromolecular chains-nanofibre interface and the large area of the nanofibres are the primary sources of alteration.

Keywords:- Nano-Fibres, Jute Plant, Polymer, Epoxy polymer, Nan composites 

Authors: Avinash Sharma, Ankit Verma, Deepak Kulkarni, Rameshwar Singh

Abstract: Modern manufacturing industries are facing continuous changes in product design, customer demand and production volume. Traditional manufacturing systems are usually designed for mass production and are not capable of adapting quickly to these changes. As a result, industries are shifting toward reconfigurable and flexible manufacturing platforms that can quickly adapt to new production requirements. Reconfigurable Manufacturing Systems (RMS) and Flexible Manufacturing Systems (FMS) provide the ability to adjust production capacity, modify machine structure and integrate new technologies with minimal downtime. These systems allow manufacturers to improve productivity, reduce cost and respond rapidly to market variations. Reconfigurable and flexible manufacturing platforms are built using modular machines, programmable automation, digital control systems and intelligent software. They support quick system reconfiguration, allowing manufacturing lines to switch between different products or production volumes. In recent years, technologies such as industrial robotics, Internet of Things, cloud computing and digital twins have further improved the efficiency of these platforms. This paper discusses the concept of reconfigurable and flexible manufacturing platforms, their key components, system architecture and enabling technologies. The advantages, industrial applications and implementation challenges are also analyzed. A comparison between traditional manufacturing systems, flexible manufacturing systems and reconfigurable manufacturing systems is presented. The study highlights the importance of these advanced platforms in supporting smart manufacturing and Industry 4.0 initiatives.

Keywords: Reconfigurable manufacturing system, Flexible manufacturing system, smart manufacturing, modular production, Industry 4.0, digital manufacturing

Auhtors: Varun S. Pandey , Sobhit Agrawal , Sanju Negi , Shivam Pathak

Abstract: Human-Robot Interaction (HRI) and collaborative robots (Cobots) are becoming central in modern manufacturing, healthcare, and service industries. HRI focuses on understanding, designing, and evaluating interactions between humans and robots to ensure safety, efficiency, and intuitiveness. Cobots, as a subcategory of robots, are designed specifically to work alongside humans without compromising safety. This review paper provides an overview of the evolution, methodologies, and applications of HRI and Cobots. It further discusses the integration of artificial intelligence (AI), machine learning, and sensor technologies to enhance interaction capabilities. Challenges such as safety, ethical concerns, and acceptance are highlighted, along with future research directions. Case studies and comparative analyses from recent literature are presented to show practical implementations in manufacturing, healthcare, and service domains.

Keywords: Human-Robot Interaction, Collaborative Robots, Cobots, AI in Robotics, Safety, Industrial Automation

Authors: Subodh Jain , Sakshi Agrawal , Sailender Bhatia

Abstract: Force-controlled robotic manipulation has become a vital research area in industrial automation, healthcare, and service robotics. Traditional positioncontrolled robots often struggle with tasks that require delicate interaction with objects or uncertain environments. The integration of Artificial Intelligence (AI) in force control enables adaptive, precise, and intelligent manipulation by allowing robots to perceive, learn, and respond to environmental changes. This review paper explores the state-of-the-art in force-controlled robotic manipulation using AI, including model-based and data-driven approaches, sensor technologies, control strategies, and applications. Challenges in realtime implementation and future research directions are also discussed. The study aims to provide a comprehensive understanding for researchers and engineers working in intelligent robotics.

Keywords: Force Control, Robotic Manipulation, Artificial Intelligence, Adaptive Control, Sensor Fusion, Machine Learning.

Authors: Sukanya Tiwari , Ramesh Chaudhary , Amrapali Deshmukh

Abstract: Fault detection, diagnostics, and prognostics (FDD&P) are crucial for the reliability, safety, and performance of mechatronic systems. Modern mechatronic systems, which integrate mechanical, electrical, and computational components, are inherently complex, making traditional monitoring techniques insufficient. This paper reviews the latest methods and technologies for FDD&P in mechatronic systems, emphasizing sensor integration, data-driven models, and hybrid approaches. A comparative study of different algorithms is presented along with practical applications in robotics, CNC machines, and automated manufacturing. Challenges such as sensor noise, data scarcity, and model uncertainty are discussed, and future research directions are proposed to improve predictive maintenance strategies.

Keywords: Mechatronic systems, Fault detection, Diagnostics, Prognostics, Predictive maintenance, Sensor fusion, Data-driven modeling

Authors: Sudharshan S Agrawal

Abstract: Digital Twin technology is becoming very important in modern manufacturing systems. A digital twin is basically a virtual model which represents a physical machine, process or system. With help of sensors, IoT and data analytics the digital model continuously receives data from real environment and behaves almost same as the physical system. Because of this, industries can monitor, simulate and optimize production process without disturbing the actual machines. In recent years, the use of digital twins has grown in smart factories, predictive maintenance and process optimization. This paper presents a review on development of digital twins for manufacturing processes. The study discusses the concept, architecture, enabling technologies, and applications of digital twin in manufacturing sector. Some challenges such as data integration, modeling complexity and cyber security are also discussed. The paper also highlights future research directions in digital twin based manufacturing systems. Overall, digital twin technology is expected to play a significant role in Industry 4.0 and intelligent production systems.

Keywords: Digital Twin, Smart Manufacturing, Industry 4.0, Process Simulation, Predictive Maintenance

Authors: Ravi Kumar , Nirmal Sachdeva

Abstract: Recent advances in artificial intelligence (AI) have significantly impacted control strategies in mechatronic devices. Traditional control systems, though effective, often struggle to manage the complexity and uncertainty in modern devices. AI-based control systems, including machine learning (ML) and deep learning (DL) techniques, provide adaptive, robust, and predictive capabilities that enhance system performance. This paper presents a comprehensive review of AI-enhanced control strategies for mechatronic devices, including neural network-based controllers, fuzzy logic systems, reinforcement learning, and hybrid approaches. Benefits, challenges, and applications across robotics, precision manufacturing, and autonomous systems are discussed. The study concludes with a perspective on future trends and research directions in AIdriven mechatronic control.

Keywords: AI control, Mechatronic systems, Neural networks, Fuzzy logic, Reinforcement learning, Adaptive control, Robotics

Authors: Rekha Dhanghi, Kavita Bansal

Abstract: Manufacturing industries are undergoing a significant transformation due to the integration of Artificial Intelligence (AI) technologies. Modern factories produce massive volumes of operational data through sensors, machines, enterprise systems, and supply chains. AI driven manufacturing optimization focuses on analyzing this data to improve productivity, quality, and operational efficiency. Machine learning algorithms, predictive analytics, and intelligent decision support systems allow manufacturers to detect patterns, forecast failures, and optimize production schedules in real time. The integration of AI also enables adaptive manufacturing processes where systems automatically adjust parameters to achieve desired outcomes. This paper reviews the role of AI in manufacturing optimization and decision support. It discusses core technologies such as machine learning, digital twins, predictive maintenance, and data driven scheduling. The study also highlights benefits including cost reduction, improved production planning, and enhanced product quality. However, challenges like data integration, computational complexity, and workforce adaptation remain significant. The paper concludes that AI driven optimization will play a central role in the development of smart manufacturing and Industry 4.0 systems.

Keywords: Artificial Intelligence, Smart Manufacturing, Predictive Maintenance, Decision Support Systems, Production Optimization, Industry 4.0

Authors: Shyam Diwaker, Manisha Kulkarni, Deepak Bansal

Abstract: Additive Manufacturing (AM) has emerged as an important manufacturing technology in recent decades. Unlike traditional subtractive manufacturing where material is removed from a solid block, additive manufacturing builds components layer by layer using digital models. This approach enables the fabrication of complex geometries, lightweight structures and customized products which are difficult to produce using conventional machining methods. However, AM processes often suffer from limitations such as poor surface finish, dimensional inaccuracies, and lower mechanical properties in some materials. To overcome these issues, hybrid additive–subtractive manufacturing systems have been developed. These systems integrate additive manufacturing processes with traditional subtractive machining operations such as milling or turning within a single machine platform. Hybrid systems combine the advantages of both techniques, allowing near-net shape production using additive methods followed by precision finishing using machining operations. This paper reviews the principles of additive manufacturing, major AM technologies, and the concept of hybrid additive–subtractive systems. The advantages, challenges, industrial applications and future research directions are also discussed. The study shows that hybrid manufacturing systems are gaining increasing attention in aerospace, medical and tooling industries due to their ability to produce high precision complex components with reduced manufacturing time. Even though the technology is still developing, hybrid manufacturing is expected to play a significant role in the future smart manufacturing environment.

Keywords: Additive Manufacturing, Hybrid Manufacturing, Subtractive Machining, 3D Printing, Smart Manufacturing

Author: Ravi Shukla

Abstract: Adaptive motion planning has emerged as a critical aspect of robotics, particularly for humanoid and industrial robots operating in dynamic and uncertain environments. Unlike conventional motion planning algorithms, adaptive methods enable robots to modify their paths and trajectories in realtime, responding to changing obstacles, human interactions, or task requirements. This paper reviews recent developments in adaptive motion planning, highlighting algorithms, sensors, control strategies, and practical applications. The discussion includes humanoid robots’ gait and balance adaptation, industrial manipulators’ path optimization, and learning-based methods. Challenges such as computational complexity, real-time constraints, and robustness in unstructured environments are also explored. Finally, future research directions emphasize hybrid approaches combining model-based planning, machine learning, and human-in-the-loop systems.

Keywords: Adaptive motion planning, humanoid robots, industrial robots, realtime trajectory optimization, machine learning, dynamic environments.

Authors: Sangita Chattarje, Sarvesh Rana, Deepak S Baitha, Kuldeep Setty

Abstract: The evolution of Industry 4.0 has transformed traditional manufacturing systems into highly interconnected, data-driven smart factories. The integration of the Industrial Internet of Things (IIoT) and edge computing has enabled realtime decision-making, predictive maintenance, and resource optimization, providing significant gains in efficiency, flexibility, and productivity. This paper presents a comprehensive review of smart factory architectures that leverage IIoT and edge computing. We explore the layered architectural models, communication technologies, data management frameworks, and computational strategies. Moreover, challenges such as security, interoperability, and latency are discussed. Several case studies and frameworks are examined to illustrate practical implementations of IIoTenabled smart factories with edge intelligence. The paper concludes with potential research directions for developing resilient, scalable, and adaptive manufacturing ecosystems.

Keywords: Smart factory, IIoT, edge computing, Industry 4.0, industrial automation, real-time analytics, predictive maintenance.

Authors: Rohan Agrawal , Dhirendra Sharma

Abstract: In today’s rapidly evolving industrial landscape, manufacturing systems must adapt to fluctuating market demands, mass customization, and short product lifecycles. Traditional manufacturing systems often lack flexibility, leading to inefficiencies and increased downtime. Self-reconfigurable manufacturing systems (SRMS) are an emerging paradigm that allows production systems to autonomously adapt their hardware and software configurations to changing production requirements. This paper reviews the concept, architecture, enabling technologies, challenges, and future prospects of SRMS. It highlights the role of modular design, cyber-physical integration, intelligent control, and multi-robot coordination in realizing self-reconfigurable systems. The review also examines recent research trends, applications, and potential pathways for Industry 5.0 adaptation.

Keywords: Self-reconfigurable manufacturing, modular production, Industry 4.0, cyber-physical systems, adaptive manufacturing, flexible robotics

Authors: Anjana S. Patil, Hemant Verma, Shreya Kulkarni, Ravinder Yadav

Abstract: Micro-assembly has become an essential manufacturing process in fields such as micro-electronics, biomedical devices, MEMS packaging, and precision optics. Traditional mechanical assembly approaches face major limitations when handling micro-scale components due to issues like adhesion forces, positioning accuracy, and limited visual feedback. Opto-mechatronic systems combine precision mechanics, optical sensing, imaging, and intelligent control to enable accurate and reliable manipulation of micro-parts. This paper reviews the architecture, sensing principles, actuation mechanisms, and control strategies of opto-mechatronic micro-assembly systems. It also discuss key challenges such as calibration, illumination design, and real-time feedback integration. Recent advances including vision-guided assembly, laser-assisted bonding, and micro-robotic manipulation are also presented. Tables and figures illustrate typical system configurations and performance comparisons. The review shows that opto-mechatronics provides significant improvements in alignment accuracy, automation level, and assembly quality for micro-scale manufacturing. However, further research is needed in adaptive control and integrated optical-mechanical design to achieve fully autonomous microassembly lines.

Keywords: Opto-mechatronics, Micro-assembly, Precision robotics, Optical sensing, Vision-guided manipulation, Micro-manufacturing

Authors: R. K. Verma, S. Mahajan, P. Dutta

Abstract: Modern manufacturing is shifting from fixed mass production toward flexible and customized production systems. Reconfigurable production lines allow rapid change in product type, volume and workflow. In such systems, multiple robots must work together in coordinated manner to perform tasks like assembly, material handling, inspection and packaging. Multi-robot coordination improves productivity and adaptability but also introduces challenges such as task allocation, collision avoidance, communication and real-time control. This paper presents a review of multi-robot coordination approaches in reconfigurable production lines. Different coordination architectures, planning algorithms, communication strategies and control techniques are discussed. Applications in smart factories and Industry 4.0 environments are analyzed. The study also highlights advantages, limitations and future research directions. Results show that cooperative robot systems can significantly increase flexibility and throughput of production lines when proper coordination strategies are applied.

Keywords: Multi-robot systems, Reconfigurable manufacturing, Production lines, Robot coordination, Smart factories, Task allocation, Industrial automation

Authors: Raj Pal Setty , Sneha Chaudhary , Rupesh Mehta, Gyanendea Pathak

Abstract: Micro-Electro-Mechanical Systems (MEMS) have emerged as a key enabling technology in precision manufacturing, allowing enhanced measurement accuracy, process control, and automation. This paper reviews recent advancements in MEMS-based sensing technologies applied to precision manufacturing environments. Various MEMS sensor types, including accelerometers, gyroscopes, pressure sensors, and force sensors, are discussed with respect to their integration into manufacturing systems. The paper also highlights the role of MEMS in monitoring tool wear, vibration, and environmental parameters, contributing to improved quality control and reduced downtime. Challenges, such as sensor drift, packaging, and signal integration, are analyzed. The paper concludes with future trends in MEMSenabled manufacturing, including AI-assisted sensor networks and smart factories.

Keywords: MEMS, precision manufacturing, micro-sensors, tool monitoring, process control, industrial automation, sensor fusion

Authors: Rajiv Sharma , Sneha Reddy , Deepak Singh , Sanju Arya

Abstract: Smart sensor fusion plays a major role in the advancement of industrial automation systems by combining data from multiple sensors to produce reliable and accurate information. As industries migrate towards Industry 4.0 and beyond, the quality and speed of sensor data interpretation have become crucial to maintaining efficiency and safety. This review paper explores the principles, algorithms, practical applications, challenges, and trends in smart sensor fusion within industrial automation, focusing on the benefits and potential limitations of this technology. The paper also discusses real-world use cases, integration issues, and future directions for research.

Keywords: Industrial automation, smart sensor fusion, data integration, multi-sensor systems, predictive maintenance, Industry 4.0.

Authors: Raman Tiwari , Sohel Pathak

Abstract: Additive manufacturing (AM), commonly known as 3D printing, has evolved from a rapid prototyping tool into a viable manufacturing technology for functional parts across aerospace, biomedical, automotive, and consumer industries. The advancement of AM is strongly dependent on mechatronics integration, which combines mechanical systems, electronics, sensors, control algorithms, and software to achieve precise and automated fabrication processes. This paper presents a comprehensive review of mechatronics integration in additive manufacturing systems, focusing on hardware architecture, motion control, sensor feedback, intelligent process monitoring, and cyber-physical connectivity. It discusses the role of actuators, embedded controllers, and sensor fusion in improving print accuracy, reliability, and productivity. Emerging trends such as AI-assisted control, adaptive slicing, and digital twin-based AM are also analyzed. The study highlights benefits, technical challenges, and future research directions in achieving fully autonomous additive manufacturing platforms.

Keywords: Additive manufacturing, 3D printing, mechatronics integration, motion control, sensor feedback, cyber-physical systems, smart manufacturing