Integration of Predictive Analytics and Quality Management Systems for Early Defect Detection in Oil and Gas Infrastructure Construction

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@article{1725094,
      author = {Mohammad Faisal Khan},
      title = {Integration of Predictive Analytics and Quality Management Systems for Early Defect Detection in Oil and Gas Infrastructure Construction},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {5},
      pages = {2406-2415},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1725094.pdf},
      abstract = {Predictive analytics can help oil and gas construction teams prioritize earlier inspections. This paper proposes a design that connects structured construction events, verified quality outcomes, risk scoring and inspector-led triage within an existing quality management system. It distinguishes forecasts of future nonconformity from automated screening of an image already acquired. A structured narrative review informs the selection of data, baseline methods, evaluation criteria and operational safeguards. An illustrative piping workflow and a numerical example show how lead time, inspection capacity and prevalence influence deployment. A prospective pilot is proposed to test operational value and detect unintended changes in inspection coverage. Its relevance to Saudi industrial development lies in traceable handover, development of inspection and analytics capability and avoidance of preventable late rework. The paper presents a conceptual framework rather than measured field performance.},
      keywords = {Predictive analytics, quality management systems, oil and gas construction, defect detection, weld inspection, Saudi Vision 2030},
      month = {November},
  }