CIC Supervisor – Underground

About the role

The CIC Supervisor – Underground will lead the refurbishment and maintenance of underground CIC equipment at the Obuasi Gold Mine. Reporting to the CIC Superintendent, you will ensure plant availability, safety and cost‑effectiveness while supporting the mine’s transformation into a fully mechanised operation.

Key responsibilities

• Apply total quality management principles to achieve zero‑defect and safety objectives.
• Gather performance data and report to the CIC Superintendent.
• Conduct periodic audits and reviews of CIC refurbishment and later maintenance activities.
• Develop and execute condition‑monitoring routes, including visual, infrared, ultrasonic, motor‑current, flux and simple NDT checks.
• Analyse vibration, IR and other predictive‑maintenance data to assess equipment health and trigger corrective actions.
• Generate work requests in SAP for planning and scheduling of refurbishment/maintenance.
• Perform routine condition‑monitoring using advanced portable data collectors and diagnose rotating‑machinery issues.
• Participate in root‑cause failure analysis and maintenance review programmes.
• Identify and implement cost‑reduction initiatives and propose savings projects.
• Coordinate refurbishment work with contractors, monitor equipment performance on the asset‑health system and report issues promptly.

Required profile

• Proven experience in underground mining equipment maintenance or refurbishment.
• Strong understanding of condition‑monitoring techniques and predictive‑maintenance principles.
• Ability to work autonomously, self‑motivated and safety‑focused.
• Experience preparing reports and audits for senior supervision.
• Good organisational skills to coordinate contractors and manage work requests.

Required skills

• SAP (work‑request creation and maintenance planning)
• Infrared thermography
• Ultrasonic testing
• Vibration analysis
• Motor‑current analysis
• Flux data collection
• Simple non‑destructive testing (NDT)
• Condition‑monitoring of rotating equipment
• Predictive‑maintenance data analysis
• Root‑cause failure analysis