Analysis of Operator Skills and Automation on Spare Parts Accuracy
DOI:
https://doi.org/10.5281/zenodo.21704366Keywords:
Dimensional accuracy, operator skills, raw material quality, automation accuracy, CNC machining, Libyan oilfield workshopsAbstract
This study examines the impact of operator skills, raw material quality, and automation accuracy on the dimensional accuracy of spare parts produced in Libyan oilfield workshops. Grounded in an integrated theoretical framework combining Human Capital Theory, the Resource-Based View, and Socio-Technical Systems Theory, the research employed a quantitative-correlational design with data collected from 150 machinists and CNC operators through structured questionnaires. Multiple regression analysis revealed that all three independent variables significantly influence dimensional accuracy, collectively explaining 62.3% of its variance. Automation accuracy emerged as the strongest predictor (β = 0.368, p < 0.001), followed by operator skills (β = 0.351, p < 0.001) and raw material quality (β = 0.312, p < 0.001). These findings demonstrate that dimensional accuracy is not determined by a single factor but by the synergistic interaction of human, material, and technological elements. The study contributes to theory by empirically validating an integrated framework in the context of resource-constrained Libyan workshops. Practically, it provides workshop managers with evidence-based guidance for resource allocation, emphasizing the need for balanced investments in workforce training, material quality assurance, and automation maintenance. The research addresses a critical gap in understanding precision manufacturing within developing industrial contexts, offering implications for improving operational reliability and safety in Libya's petroleum sector.
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