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

Regular Issues

• A robust optimisation model for a dual-objective software reliability growth model with multiple fault types  
  by Mohammadreza Namdar, Rassoul Noorossana 
  Abstract: Reliability and development costs are two significant criteria that highly dependent on software release time and test termination time. Simultaneous optimisation of both criteria is a substantial challenge in current projects. Studies in the literature usually suffer from some of the following drawbacks; 1) considering a single objective function (reliability or development costs); 2) not considering the uncertainty of the parameters; 3) considering one type of software fault, whereas multiple fault types with different debugging costs can occur in real condition; 4) ignoring the discounted rate in cost optimisation. This paper presents a dual-objective robust optimisation method for joint optimisation of the development discounted costs and reliability considering the various fault types with different debugging costs to cover the mentioned weaknesses. Eventually, it analyses the model performance through a case study. The findings prove the distinguished role of uncertainty and the interest rate on both objective functions.
  Keywords: robust optimisation; software reliability; multiple fault types; dual-objective mathematical model; cost optimisation.
  DOI: 10.1504/IJQET.2025.10071173
   
  
• High-Quality Liquor Prediction through Machine Learning and PCA Advancements  
  by Rupa Rani, Aman Sanger 
  Abstract: Machine learning is increasingly applied in diverse industries, including healthcare, astronomy, and hospitality. In the growing liquor industry, predicting high-quality liquor using machine learning can significantly enhance production efficiency and reduce costs. This study proposes a model that combines random forest (RF) with principal component analysis (PCA) to predict liquor quality based on chemical properties, grape growth conditions, and production processes. The model achieves a high accuracy of 91.68%, outperforming traditional methods by effectively capturing non-linear feature interactions. PCA is used to reduce dimensionality and balance the dataset, making the prediction process more efficient. The proposed RFPCA model provides deeper insights into the variables influencing liquor quality and demonstrates better performance compared to previous studies. This approach not only supports quality assessment but also helps liquor manufacturers maintain consistency and control over production. Additionally, demographic analysis assists in identifying ingredients that affect the quality, ensuring improved consumer satisfaction.
  Keywords: Machine Learning; High-Quality Liquor; RFPCA (Random Forest Principal Component Analysis); Decision Tree Algorithm; SVM; Logistic Regression.
  DOI: 10.1504/IJQET.2025.10073093
   
  
• Inductive WPT based NDT for Surface Defects Detection in Metals  
  by Junaid Ahmed Bhatti, Rajab Ali, Abdul Qudoos 
  Abstract: Detecting cracks in industrial materials during maintenance is a challenge. This study explores a non-destructive testing method for crack detection using wireless inductive power transfer (IPT). The proposed technique is suitable for identifying small defects in metals due to its inductive coupling operation which enables efficient energy transfer and frequency separation. Two inductive coil probes are used as eddy current sensors to detect surface defects in aluminium and copper samples, with 3 and 5 fracture points, respectively. A vector network analyser connected to the transmitter and receiver aids in measurement. Principal component analysis (PCA) and independent component analysis (ICA) are applied to restore data, linking features to physical coordinates for comparison. The peaks in the PCA and ICA charts reveal a direct relationship between defects with fractures and those without fractures. This study enhances non-destructive testing capabilities for fracture detection in industrial applications, providing more comprehensive safety and maintenance procedures.
  Keywords: WPT; Destructive; Non-destructive; Analysis; ICA; PCA; Coils; Sweep Frequency; Resonance; Defects; Penetration; Conductance; Eddy current; Transmitter; probes.
  DOI: 10.1504/IJQET.2025.10073191
   
  
• The Impact of ESG Decoupling on the Financial Performance of SMEs: Evidence from Korean SMEs  
  by Eun-Young Kim, Jae-Eun Lee, Yong-Seok Choi, Hyun-Woo Kim, Ga-Rog Han 
  Abstract: Drawing on new institutionalism and legitimacy theory, this study conceptualises ESG decoupling as the gap between targeted and actual ESG activities in small and medium-sized enterprises (SMEs) and investigates its effects on financial performance. Using data from 127 Korean SMEs, the results reveal that environmental decoupling has no significant impact on financial performance, social decoupling negatively affects financial performance, while governance decoupling positively affects it. Theoretically, this research extends the decoupling concept to the ESG domain and provides empirical evidence of financial implications for SMEs. Practically, the findings suggest that SMEs should engage in genuine social initiatives to minimise the negative consequences of social decoupling, while setting ambitious governance targets that, when paired with strong managerial standards, may enhance financial performance.
  Keywords: ESG Decoupling; Financial Performance; Korean SMEs; Legitimacy Theory; Theory of New Institutionalism.
  DOI: 10.1504/IJQET.2025.10073450