ORIGINAL ARTICLE
Underutilisation of SPC Within the Mining Industry: Insights, Cross-industry Comparisons, and Opportunities
1
Department of Applied Mathematics, AGH University of Cracow, Kraków, Poland
Submission date: 2024-10-28
Final revision date: 2025-01-25
Acceptance date: 2025-01-28
Online publication date: 2025-02-11
Publication date: 2025-02-11
Corresponding author
Stanisław Marek Halkiewicz
Department of Applied Mathematics, AGH University of Cracow, al. Mickiewicza 30, 30-059, Kraków
Department of Applied Mathematics, AGH University of Cracow, al. Mickiewicza 30, 30-059, Kraków
Civil and Environmental Engineering Reports 2025;35(1):190-212
KEYWORDS
TOPICS
ABSTRACT
Statistical Process Control (SPC) is a quality control methodology that has been adopted extensively across numerous industries. It serves as an effective instrument for identifying and resolving process inconsistencies and variability, ensuring optimal efficiency and consistent product quality. By leveraging statistical methods, SPC aims to minimise waste and ensure that a product meets quality standards. Despite the extensive implementation of SPC in various manufacturing sectors, including the automotive, electronics, healthcare and hi-fi technologies sectors, its application in the mining industry remains underdeveloped and lacks comprehensive documentation in academic literature. This article aims to address this gap by exploring existing applications and explaining the potential reasons why the mining industry is an outlier. Furthermore, it endeavours to propose innovative applications of SPC. It has been determined that the mining industry is sufficiently specific in nature to potentially render the known applications of SPC ineffective, due to the limited human control that can be exercised over the quality and characteristics of the mined ore or material. Consequently, alternative and unconventional methodologies employing SPC are proposed as a potential solution, including techniques for predicting the depletion of a source (or a vein). The article also offers guidelines for practitioners that can allow them to implement SPC methods more rigorously, while avoiding the issues identified herein. A discussion on where to look for potential areas of SPC implementation in mining is also offered.
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