Selection of Machining Parameters of Face Milling operation for Aluminium with HSS cutter using Response Surface Methodology and Genetic Algorithm

Components used in chemical equipments are produced from forging, extrusion and casting processes with classic dimension tolerances due to its producing ability. So machining processes were introduced for close tolerance assembly and improve the product working efficiencies. At present,  lot of machining processes are available for producing chemical equipments such as turning, milling, drilling and grinding etc.,. Milling operation is playing critical role on making the chemical equipment’s components with high accuracy and higher productivity. Face milling operation is one of the milling processes which is used for achieving higher flatness and surface finish of chemical equipment’s parts. Thiswork concentrates the parameters influence on Material Removal Rate (MRR) and Surface Roughness (SR) by using aluminium as work piece material. Actually, aluminium alloy has the  most significant in chemical industries because of its inherent properties such as, corrosive resistance , low weight to strength ratio. The milling parameters such as feed rate, spindle speed  and depth of cut are selected as parameters for improving the quality and productivity. This work put together the link between input and response variables for developing the face milling performances. The Response Surface Methodology (RSM) is employ for making the link between dependent and independent variables. Building the empirical model by conducting regression analysis The performance of developed regression models are verified with experimental results. Verification results show the developed models have best agreement with experimental results. The developed models are used for achieving the best input parameters by using Genetic Algorithm (GA). Finally, the optimal parameters are evaluated by GA

Rule based heuristic approach for minimizing total flow time in permutation flow shop scheduling

Programiranje radova u proizvodnji je od bitne važnosti u planiranju i funkcioniranju proizvodnog sustava. Unaprijeđeni sustav programiranja značajno utječe na smanjenje troškova i minimalni broj radnih postupaka. U ovom se radu razmatra problem programiranja n/m/F/ΣCi primjenom Decision Tree (DT) algoritma. Budući da je ovaj problem poznat kao veoma NP-hard, u radu se za njegovo rješenje predlaže metodologija temeljena na heuristici. Prednosti DT-a su u tome što je pravilo otpreme u obliku If-then else pravila koja radnici u radionici lako razumiju. Predloženi je pristup testiran na repernim problemima dostupnim u literaturi i uspoređen. Predloženi rad je dodatak tradicionalnim metodama.Production scheduling plays a vital role in the planning and operation of a manufacturing system. Better scheduling system has a significant impact on cost reduction and minimum work-in-process inventory. This work considers the problem of scheduling n/m/F/ΣCi using Decision Tree (DT) algorithm. Since this problem is known to be strongly NP-hard, this work proposes heuristic based methodology to solve it. The advantages of DT’s are that the dispatching rule is in the form of If-then else rules which are easily understandable by the shop floor people. The proposed approach is tested on benchmark problems available in the literature and compared. The proposed work is a complement to the traditional methods

The Eye: A Light Weight Mobile Application for Visually Challenged People Using Improved YOLOv5l Algorithm

The eye is an essential sensory organ that allows us to perceive our surroundings at a glance. Losing this sense can result in numerous challenges in daily life. However, society is designed for the majority, which can create even more difficulties for visually impaired individuals. Therefore, empowering them and promoting self-reliance are crucial. To address this need, we propose a new Android application called “The Eye” that utilizes Machine Learning (ML)-based object detection techniques to recognize objects in real-time using a smartphone camera or a camera attached to a stick. The article proposed an improved YOLOv5l algorithm to improve object detection in visual applications. YOLOv5l has a larger model size and captures more complex features and details, leading to enhanced object detection accuracy compared to smaller variants like YOLOv5s and YOLOv5m. The primary enhancement in the improved YOLOv5l algorithm is integrating L1 and L2 regularization techniques. These techniques prevent overfitting and improve generalization by adding a regularization term to the loss function during training. Our approach combines image processing and text-to-speech conversion modules to produce reliable results. The Android text-to-speech module is then used to convert the object recognition results into an audio output. According to the experimental results, the improved YOLOv5l has higher detection accuracy than the original YOLOv5 and can detect small, multiple, and overlapped targets with higher accuracy. This study contributes to the advancement of technology to help visually impaired individuals become more self-sufficient and confident. Doi: 10.28991/ESJ-2023-07-05-011 Full Text: PD

Spondyloenchondrodysplasia Due to Mutations in ACP5: A Comprehensive Survey

Purpose: Spondyloenchondrodysplasia is a rare immuno-osseous dysplasia caused by biallelic mutations in ACP5. We aimed to provide a survey of the skeletal, neurological and immune manifestations of this disease in a cohort of molecularly confirmed cases. Methods: We compiled clinical, genetic and serological data from a total of 26 patients from 18 pedigrees, all with biallelic ACP5 mutations. Results: We observed a variability in skeletal, neurological and immune phenotypes, which was sometimes marked even between affected siblings. In total, 22 of 26 patients manifested autoimmune disease, most frequently autoimmune thrombocytopenia and systemic lupus erythematosus. Four patients were considered to demonstrate no clinical autoimmune disease, although two were positive for autoantibodies. In the majority of patients tested we detected upregulated expression of interferon-stimulated genes (ISGs), in keeping with the autoimmune phenotype and the likely immune-regulatory function of the deficient protein tartrate resistant acid phosphatase (TRAP). Two mutation positive patients did not demonstrate an upregulation of ISGs, including one patient with significant autoimmune disease controlled by immunosuppressive therapy. Conclusions: Our data expand the known phenotype of SPENCD. We propose that the OMIM differentiation between spondyloenchondrodysplasia and spondyloenchondrodysplasia with immune dysregulation is no longer appropriate, since the molecular evidence that we provide suggests that these phenotypes represent a continuum of the same disorder. In addition, the absence of an interferon signature following immunomodulatory treatments in a patient with significant autoimmune disease may indicate a therapeutic response important for the immune manifestations of spondyloenchondrodysplasia

Development and evaluation of a search-and-rescue robot Paripreksya 2.0 for WRS 2020

In recent years, the influence of robotics in search-and-rescue missions has become relevant. Robots can provide human rescue teams with valuable information about the disaster area, track victims and speed up the rescue operation. The disaster robot category challenge at the World Robot Summit (WRS) is a platform where emerging technologies in search-and-rescue robot developments are evaluated. This paper describes the design, development and implementation of a teleoperated all-terrain search-and-rescue robot, Paripreksya 2.0, for participation in the Standard Disaster Challenge. The robot was integrated with a 4-DoF robotic manipulator for performing dexterity tasks along with tracks and four assistive flippers for locomotion. The design of the robot was done in SolidWorks and the stability constraints of the robot while climbing stairs and slopes are also calculated. The software of the robot was built on the ROS framework. The robot was designed to perform various tasks including staircase climbing, negotiation of obstacles, opening and closing of valves, manoeuvring, plant inspection, etc. Our team has secured the best-in-class dexterity award at the WRS 2020 challenge. The performance of the robot was evaluated using the scores from different challenges held at the WRS competition.</p