Effects of Contact Pressure, Plastic Strain and Sliding Velocity on Sticking in Cold Forging of Aluminium Billet

AbstractHot rolling of stainless steel is one of the most important steps in manufacturing process regarding surface quality of the product. Stabilised ferritic stainless steels are widely used in automotive and cosmetic appliances but are also concerned by sticking phenomenon. These grades, having high dry corrosion and creep resistance, are enriched in specific chemical elements such as Cr, Nb or Ti, limiting also slab oxidation during hot rolling. Nevertheless, the mastered oxidation of slab surface is a way to protect metal surface from direct contact with rolls. In order to better understand initiation of sticking, a first campaign was based on topography and rolls surface state wear analysis. This study revealed that sticking initiation is not due to the presence of roll scratches which depth is higher than oxide layer thickness. Indeed, the probability that roll scratches are deeper than oxide layer thickness is very low. In a second time, a pilot was designed, reproducing tribological conditions of a roll bite, to better understand mechanisms that initiate sticking. Keeping in mind the importance of rolls and slab surface state, this pilot is able to use specimen taking from industrial products, having the original oxide layer surface. This second study highlighted the major role of silicon oxides on scale adherence and the high heterogeneity of this scale layer in thickness and in chemical composition

Prediction of welding responses using AI approach : adaptive neuro-fuzzy inference system and genetic programming

Laser welding of thin sheets has widespread application in various fields such as battery manufacturing, automobiles, aviation, electronics circuits and medical sciences. Hence, it is very essential to develop a predictive model using artificial intelligence in order to achieve high-quality weldments in an economical manner. In the present study, two advanced artificial intelligence techniques, namely adaptive neuro-fuzzy inference system (ANFIS) and multi-gene genetic programming (MGGP), were implemented to predict the welding responses such as heat-affected zone, surface roughness and welding strength during joining of thin sheets using Nd:YAG laser. The study attempts to develop an appropriate predictive model for the welding process. In the proposed methodology, 70% of the experimental data constitutes the training set whereas remaining 30% data is used as testing set. The results of this study indicated that the root-mean-square error (RMSE) of tested data set ranges between 7 and 16% for MGGP model, while RMSE for testing data set lies 18–35% for ANFIS model. The study indicates that the MGGP predicts the welding responses in a superior manner in laser welding process and can be applied for accurate prediction of performance measures

Multi-objective optimization of kerf-taper and surface-roughness quality characteristics for cutting-operation on coir and carbon fibre reinforced epoxy hybrid polymeric composites during CO2-pulsed laser-cutting using RSM

Current research focuses on optimizing various quality characteristics for kerf geometry generated through laser cutting of Coir fibre/carbon fibre/epoxy resin hybrid composite adjacent to straight cut profile employing pulsed CO2 laser system. The Kerf taper (KT) and the Surface roughness (SR) are the main quality parameters discussed. Dependent on significant process parameters, namely gas pressure, cutting speed, pulse frequency and pulse width predictive models were developed. In accordance with Taguchi's L9 orthogonal array (OA), the cutting trials are designed. Process-parametric optimization was performed using Response Surface Methodology (RSM). Furthermore, experiments were performed to obtain experimental data for the analysis of cut quality features. The impact of the input variables on the response characteristics is also explored. The morphological characterizations have been performed to analysis the effect of machining-variables and cut-quality for the top and bottom kerf widths with various laser cutting variables in the pulse laser-cutting of Coir-fibre/carbon-fibre/epoxy-resin hybrid composite. For SR and KT, the developed second order surface response model was found very successful. The optimal levels of cutting variables for KT are established at Gas pressure-6N/mm2, pulse width-2.04ms, cutting speed-8.01mm/s, pulse frequency-15 Hz, for sample A1, Gas pressure-5.47N/mm2, pulse width-2.5ms, cutting speed-8.81mm/s, pulse frequency-8.43 Hz, for sample A2, Gas pressure-3.85N/mm2, pulse width-1.5ms, cutting speed-9.06 mm/s, pulse frequency-5 Hz, for sample A3 additionally for SR Gas pressure-2N/mm2, pulse width-1.5ms, cutting speed-7mm/s, pulse frequency-5 Hz, for sample A1, Gaspressure-2.36 N/mm2, pulse width-1.5ms, cutting speed-7mm/s, pulse frequency-15 Hz, for sample A2, Gaspressure-6N/mm2, pulse width-1.5ms, cutting speed-11 mm/s, pulse frequency-8.73 Hz, for sample A3. Regression results and linear and square impact of laser cutting variables have been revealed to be important to validate the model

On the replacement of steel by NITINOL as coupling agent in automobile shaft

Automobile couplings generally fail due to excessive misalignment in shafts and torque overload which ultimately generates vibration in the assembly. These vibrations weaken the coupling structure and ultimately get transmitted to the shaft leading to fatigue failure. Additionally, the complexity in the design of standard coupling is related to lower durability. In this system, when the radial space is larger it trigger a bulkier transmission. Shape memory alloy such as NITINOL is a special class of smart material that possesses super-elasticity which means it can retain deformation of about 8%. This material has a high degree of strength, greater elastic and shear modulus than existing coupling materials such as steel, and have unique vibration damping features. Coupling made of NITINOL is simple in design and requires lesser space with minimal maintenance. They provide higher durability and are much reliable in operation over a wide range of temperatures. This paper aims to review the NITINOL material used in coupling technology industries and the parameters governing its shape memory effect. The knowledge gathered from this work enable to further extend the technological contribution of NiTi coupling at large scale production in the automobile sector with direct effect on longer life for the transmission system

Optimization of the cycle time of robotics resistance spot welding for automotive applications

In the automobile manufacturing industry, resistance spot welding (RSW) is widely used, especially to build the car's body. The RSW is a standard and wide‐ranging joining technique in several assembling ventures, showing a wide range of possibilities for a competent procedure. Robots are commonly used for spot welding in various industrial applications. After completing assembling design, interest increases to improve the designed processes, cost‐reduction, environmental impact, and increase time productivity when all is said to be done. In this paper, the robot movement between two welding points, a path followed while spotting, gripping and payload‐carrying activities, numbers of holds, moves, and a possibility to enhance interaction between four Robots were analyzed using an offline Robot simulation software 'DELMIA‐V5'. The body shop assembly line of the SML ISUZU plant has four robots that perform about 209 welding spots in 532 sec. The optimal model reduced the whole welding cycle time by 68 sec, and after modification and proper sequencing, a12.7% reduction in cycle time was achieved. The offline Robot simulation software 'DELMIA‐V5' has good potential to produce optimal algorithms while saving precious time. It enables an organization to promote higher quality and to encourage meaningful creativity by reducing design flaws

Towards better performances for a novel rooftop solar PV system

Solar photovoltaic (PV) systems are used worldwide for clean production of electricity. Photovoltaic simulation tool serve to predict the amount of energy generated by the PV solar array structure. This paper presents the photovoltaic system installed on the rooftop of the G.D. Naidu Block at Vellore Institute of Technology (Vellore, India). A novel PV plant design is developed here in order to improve the energetic efficiency of an existing PV system. The effectiveness of proposed design is evaluated over an entire year using the PVsyst v6.70 software, which works on accurate plant specifications. For this purpose, Metronome 7.1 weather data sets of ambient temperature and radiation from PVsyst database are used for the investigation. The cost of the proposed PV system and the required payback period are analyzed as well. Simulation results demonstrate the superiority of the proposed PV system design over the existing one in terms of the amount of electric energy injected in the grid, energy conversion efficiency, and reductions in CO2/SO2/NO emissions. Performance ratio of proposed design (Design 2) is 0.791 whereas the existing design (Design 1) is only 0.704. Design 2 provides 40 MWh more energy to grid than Design 1 due to reducing shading losses. The daily system energy generated for Design 2 is maximum (in particular, 26-29% higher than for Design 1) between March and May, when the sun is brightest and directly above our head. Shading analysis carried out for both designs revealed that the existing Design 1 has more shading loss while the proposed Design 2 may reduce this loss by about 11-13%, which results in a better efficiency of energy production. The article also documents significant emission reduction and cost analysis calculation for the proposed Design 2

Current global scenario of sputtered deposited NiTi smart systems

This review provides details of the global scenario on the recent development and application of NiTi smart metal shape memory alloys (SMA). It mainly focuses on the dc/rf magnetron sputtering fabrication technology of nitinol thin film, which is a prominent structural material for many miniaturised systems. The sputtering parameters and their influence on the smart mechanism of the NiTi thin film has highlighted. The application of NiTi SMA at industrial scale from aviation industries to medical industries was discussed. The raised challenges within various applications were addressed, discussed and we have proposed possible way to overcome these limitations

COVID-19 challenges : can industry 4.0 technologies help with business continuity?

The COVID-19 pandemic has halted economic activities and made business dynamics much more challenging by introducing several additional operational, structural, and managerial constraints. The problem has affected global supply chains in many ways, and has questioned their long-term continuity. On the other hand, Industry 4.0 is an emerging phenomenon. However, there is a need to investigate how Industry 4.0 technologies may play a potential role in sustaining business operations to ease unprecedented causalities. The current research aims to investigate the potentiality of Industry 4.0 technologies to solve the COVID-19 challenges for long term sustainability. From an exploratory literature analysis coupled with the Delphi method, keeping in view the situation of the pandemic, ten challenge groups that have affected global business dynamics were identified. A questionnaire was developed with the aim of accumulating industrial and academic experts to evaluate the degree of influence and interrelationship among the identified challenges. The Decision Making, Trial and Evaluation Laboratory (DEMATEL) approach was deployed to further analyze the challenges for the categorization of these into causes and effects, further prioritizing them for better decision making. The prioritized challenges from the list of causes were governmental policies and support, followed by real access to customers and a lack of infrastructure. Additionally, these challenges were further evaluated through the expert opinion of Industry 4.0 systems experts and strategic-level supply chain experts to potentially gauge the potency of Industry 4.0 technologies to solve COVID-19-induced challenges. The outcomes of this research (which used Delphi integrated with a DEMATEL approach) are expected to support businesses in formulating strategies with the aim of business continuity in combating future disruptions caused by COVID-19-like pandemics

Comprehensive survey on nanobiomaterials for bone tissue engineering applications

One of the most important ideas ever produced by the application of materials science to the medical field is the notion of biomaterials. The nanostructured biomaterials play a crucial role in the development of new treatment strategies including not only the replacement of tissues and organs, but also repair and regeneration. They are designed to interact with damaged or injured tissues to induce regeneration, or as a forest for the production of laboratory tissues, so they must be micro-environmentally sensitive. The existing materials have many limitations, including impaired cell attachment, proliferation, and toxicity. Nanotechnology may open new avenues to bone tissue engineering by forming new assemblies similar in size and shape to the existing hierarchical bone structure. Organic and inorganic nanobiomaterials are increasingly used for bone tissue engineering applications because they may allow to overcome some of the current restrictions entailed by bone regeneration methods. This review covers the applications of different organic and inorganic nanobiomaterials in the field of hard tissue engineering

Project managers' personality and project success : moderating role of external environmental factors

Successful project completion is a challenging phenomenon for project managers. Various factors play an indispensable role in the success of a project. The objective of this study is to examine the role of project managers’ personalities in project success with the moderating role of external environmental factors i.e., political, economic, social. The study includes 145 project managers from 36 large‐scale construction projects, from both the public and private sectors. The big five personality model was used to evaluate the personality traits of project managers and triple constraint criteria (cost, time, and quality) was used to gauge project success. Data has been collected through a well‐structured questionnaire. The analysis of data indicated that personality traits like extraversion and openness are positive predictors of project success, whereas conscientiousness, agreeableness, and neuroticism did not have any direct relationship with project success. Importantly, the findings of this study concluded that external environmental factors—like political, economic, and social— moderately influence the link of specific project managers’ personality traits to project success. The role of external environmental factors as moderators has been discussed. The findings indicate the essential personality traits, as well as the role of external factors for achieving project success. The research contributions have relevance to both theory and practice and provide a deeper insight that is useful for individuals, organizations, researchers, practitioners, and decision‐makers