Journal of Manufacturing Engineering

Industry 4.0 technologies' effects on environmental sustainability - A systematic literature review

Mohamed El Merroun — 2022-12-01

In the existing literature, Industry 4.0 and its potential impact on environmental sustainability have been studied from different perspectives. However, Industry 4.0 is a concept that gathers different technologies that are not necessarily combined. It is clear that the combination of different technologies is the core value of Industry 4.0. However, the examination of each technology separately is crucial for determining the right combination of technologies for each specific case. Therefore, the following research provides a systematic literature review (SLR) of each technology included in Industry 4.0 and its effects on environmental sustainability aspects based on 107 research papers. 417 articles from the SCOPUS database, which contain the word Industry 4.0 in the title, abstract, and/or in the indexed keywords, were scanned by the command-line program Astrogrep to find the most common Industry 4.0 technologies. The results revealed that the Internet of Things (IoT) was mentioned 252 times, Artificial Intelligence/Machine Learning (AI/ML) 81 times, Simulation 38 times, Blockchain 30 times, Augmented Reality (AG) 27 times, and Additive Manufacturing (3D printers) 23 times. First, the study reviews the potential effects of the six technologies on different aspects of environmental sustainability. Later on, the challenges faced by organizations when applying these technologies for environmental purposes were reviewed, and new research scopes and future research directions were highlighted.

Assessment of surface quality in extrusion honing process using dimensional analysis approach

Jayasimha SLN — 2022-12-01

It is critical to obtain the desired surface quality on machined parts’ internal and external portions. The estimated level of surface texture can be induced on the outer regions using traditional finish machining processes such as grinding, honing, and so on. While the problem emerges when processing miniature core components such as micro bores and inlet/outlet valves. The EH approach overcomes this limitation of the conventional finishing method. It is a novel micromachining process that extrudes pressured flow of carrier media combined with abrasives into the confined passage to generate the desired level of surface texture. Due to the abrasion process, micromachining occurs by taking away negligible stock material. The present study focus on the impact of the number of passes at the specimen’s entry and exit sides of the carrier media. The improvements in the surface finish (Ra) on both sides, i.e. entry and exit, are also evaluated. A dimensionless expression for Ra is also developed. The relation is implemented using Buckingham’s π theorem, and the developed model is compared with experimental results. SEM analysis is made to portray surface texture produced by selected

Polyamides containing Oxadiazole ring moiety as corrosion inhibitor for Aluminium in acid solution.

subha c — 2022-12-01

Corrosion control of metals is an important activity of technical, economic, environmental, and aesthetical importance. The use of inhibitors is one of the best options for protecting metals and alloys against corrosion. This study involves the investigation of new and effective polymeric material for the application of corrosion inhibition on aluminium in the acid medium using chemical and electrochemical methods. Results obtained from weight loss and potentiodynamic and impedance methods confirm that polyamides containing oxadiazole rings in their backbone can act as effective corrosion inhibitors. The adsorption behaviour of this polymer on aluminium in 1N HCl was found to obey Langmuir adsorption isotherm. SEM studies confirmed the protective film formed on aluminium by the adsorption of Polyamides.

Investigation on Production of Edible Oil from Rice Husk

Murugesan A — 2022-12-01

Rice husk, the hard protective covering of the grain of rice (paddy), is a massive agricultural residue. Rice bran oil (RBO) also called wonder oil is well known for its numerous health benefits. The presence of a unique antioxidant called oryzanol contributes maximum antioxidant activity to rice bran oil. Rice bran oil has number of advantages over the other edible oil. The results showed that the rice bran has 21.44% of raw oil, with a chemical composition (based on fatty acids) of 48.48% oleic acid, 35.26% linoleic acid, and 14.54% palmitic acid, as well as a free fatty acid content of 8.15%. The oil contains vitamins such as B and E, proteins, fatty acids, antioxidants, collagen, elastin, oryzanol and ferulic acid. Antioxidants and Vitamin E are good for the heart as they reduce the amount of bad cholesterol and prevent cardiac arrest. Compounds such as oryzanol and ferulic acid are used as functional food supply ingredients. Apart from these benefits, the consumption of rice bran oil maintains the immune system, aids in weight loss, prevents diseases like cancer, relieves symptoms of menopause and enhances skin health. These advantages motivate capitalists to venture into rice bran oil manufacturing and thus can supply cooking oil and various other essential products that require rice bran oil as a component of it. Is. Although it is classified as an “oil”, rice bran oil is completely safe for consumption by patients with heart problems, diabetes, cholesterol, or high blood pressure. Because of all these benefits, you can expect good profits in the Rice Bran Oil Making Business.

Prediction of Weld Strength in Power Ultrasonic Spot Welding Process Using Artificial Neural Network (ANN) and Back Propagation method

Ziad Al Sarraf — 2022-12-01

In this presented work, an Artificial Neural Network (ANN) connected with the backpropagation method was employed to predict the strength of joining materials that were carried out by using an ultrasonic spot welding process. The models created in this study were investigated, and their process parameters were analyzed. These parameters were classified and set as input variables like applying pressure, time of duration weld and trigger of vibrating amplitude. In contrast, the weld strength of joining dissimilar materials (Al-Cu) is set as output parameters. The identification from the process parameters is obtained using several experiments and finite element analyses based on prediction. The results of actual and numerical are accurate and reliable; however, their complexity has a significant effect due to being sensitivity to the condition variation of welding processes. Therefore, an efficient technique like an artificial neural network coupled with the backpropagation method is required to use the experiments as input data in the simulation of the ultrasonic welding process, finding the adequacy of the modeling process in the prediction of weld strength and to confirm the performance of using mathematical methods. The results of the selecting non-linear models show a noticeable potency when using ANN with a backpropagation method in providing high accuracy compared with other results obtained by conventional models.