International Journal of Quality Engineering and Technology (4 papers in press)

Regular Issues

• Quality insights: quality research and advancement in local manufacturing  
  by Adedeji B. Badiru 
  Abstract: Quality operations work best when approached from a systems perspective to improve quality of outputs. This is particularly essential when an optimisation framework is desired across national and geographical boundaries. A system is a collection of interrelated elements whose collective output, together, is higher than the mere sum of the individual outputs. For a systems approach to be practical, profitable, realisable, and optimisable, partnerships and collaborative frameworks must be instituted at the domestic level. Buying locally-made products is the most dependable approach to improving product quality. This paper presents a systems framework to justify buying locally-made products for the strategic goal of quality improvement. The DEJI systems model leads to a structured requirement for product design, evaluation, justification, and integration. In the premise of this paper, integration is with regard to the domestic platform of the manufacturer. The methodology of this paper is, particularly, essential for developing economies.
  Keywords: product quality; integration; local market; industrial development; DEJI systems model; consumer products.
  DOI: 10.1504/IJQET.2024.10066440
   
  
• The sign chart with variable control and warning limits  
  by Mohammed Kadhim Shanshool, Shashibhushan B. Mahadik, Ravindra E. Deore 
  Abstract: Control charts with variable design parameters demonstrate improved statistical performance when compared to their counterparts with static design parameters. However, in case of some processes, the implementation of the charts with variable sampling interval and/or variable sample size can be complex because of the switches between sampling interval lengths and/or that between sample sizes. This paper proposes a sign chart for process location with variable control and warning limits (VCWL), whose implementation is just as simple as that of the static sign chart, and even so it demonstrates significantly better statistical performance than the later chart. The mechanism of the VCWL sign chart is illustrated through real-data examples.
  Keywords: non-parametric control charts; adaptive control charts; average run length.
  DOI: 10.1504/IJQET.2024.10066834
   
  
• Thermo-mechanical analysis of ventilated discs used in disc brakes by various design parameters: a review  
  by Manoj Subhash Patil, Harshal Ashok Chavan 
  Abstract: Disc brake systems play a pivotal role in the automotive industry, ensuring both safety and performance in vehicles across the globe. This paper presents a thorough review of thermo-mechanical analyses conducted on disc brake systems, aiming to consolidate existing knowledge in this vital area of research. The review examines the basic operating principles of disc brakes, focusing on the mechanisms that produce and dissipate heat during braking as well as the analytical and computational approaches used to analyse the thermal behaviour of disc brakes. Furthermore, this review scrutinises the mechanical aspects of disc brakes, encompassing their structural mechanics, stress analysis, and material selection. The influence of design parameters, such as disc geometry and material, on mechanical performance is also discussed. Furthermore, it identifies potential areas for future research, including advancements in simulation techniques, materials, and design strategies, with the ultimate goal of enhancing disc brake safety, reliability, and performance.
  Keywords: thermo-mechanical; brake disc; optimisation; temperature; stress; deformation.
  DOI: 10.1504/IJQET.2024.10066881
   
  
• A lightweight deep learning ensemble model based on convolutional neural network for deepfake detection in videos  
  by Richa Gupta, Varun Borar, Nishika Khatri, Rakesh Garg, Neetu Singla, Ritvik Garg 
  Abstract: The advancement in Artificial Intelligence has promoted significant growth in developing highly realistic forged and manipulated media, commonly known as deepfakes. As a result, deepfakes have been associated with several positive applications in the education and entertainment industries. However, at the same time, deepfakes have the potential to be part of criminal activities, such as identity theft, pornography, or spreading false information resulting in distrust in digital media. As technology continuously evolves, it is crucial to ensure the development of techniques or algorithms to prevent unintended consequences. A lightweight and computationally efficient convolutional neural network (CNN) model, NVNet, to detect media forgery is proposed. The CNN model is trained on a dataset extracted from FaceForensic++. The dataset consists of four facial forgeries: i.e., Deepfakes, Face2Face, FaceSwap, NeuralTexture and original sequences. At last, we propose an ensemble model trained on different datasets to detect deepfakes.
  Keywords: deepfakes detection; synthetic media; artificial intelligence; convolutional neural network; CNN; detection techniques; ensemble model.
  DOI: 10.1504/IJQET.2024.10067101