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Rustenburg: Process Optimisation Specialist posted by Network Finance

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Job Description

About the Role

Network Finance is seeking a Process Optimisation Specialist to enable stable, predictable, and optimised processing operations through digital process control, advanced analytics, and system-enabled optimisation capabilities. The successful candidate will provide deep technical and analytical capability to improve operational stability, controllability, and optimisation.

Key Responsibilities

  • Provide technical input and optimisation requirements into the definition, review, and maintenance of MES (Level 2–3) data context standards.
  • Design, deploy, and continuously improve loop tuning and Advanced Process Control programmes.
  • Develop and maintain analytical models to quantify process stability, variability drivers, control effectiveness, and optimisation benefits.
  • Perform diagnostic and statistical analytics, including trending, variance analysis, correlation analysis, and regime detection.
  • Interpret high-level plant indicators such as instability, excursions, and abnormal operating conditions.
  • Analyse operational variability driven by feed changes, operating modes, and process conditions to improve detect-to-correct response through system-based logic and automation.
  • Implement and technically support dynamic water balance systems.

Requirements

  • Grade 12 (NQF 4)
  • BEng or BSc in Chemical Engineering, Industrial Engineering, Electrical (Control) Engineering, or equivalent

Qualifications

  • Lean or Six Sigma certification
  • APC, MES, control systems, or industrial analytics certifications

Salary & Benefits

  • Salary details not mentioned in the original job description.

Key Analytical Deliverables

  • Control and optimisation performance models.
  • Root cause analysis outputs explaining control- and system-driven performance deviations.
  • Optimisation and APC benefit tracking models with defined baselines and measurable performance improvements.
  • Predictive or pattern-based indicators supporting early detection of abnormal or unstable operating conditions.
  • Analytics-enabled IOC dashboards with clear thresholds, alerts, and decision triggers.
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People Enablement

  • Coach operators, control room personnel, and engineers on APC usage, analytics interpretation, and control optimisation principles.
  • Contribute to IOC and control room training materials.
  • Support structured operational performance discussions through analytics-driven insights.

Resource & Delivery Management

  • Prioritise APC, analytics, and process control improvement backlogs in collaboration with optimisation and automation leadership.
  • Plan and coordinate testing and deployment windows aligned with OT change management, approval processes, and system continuity requirements.
  • Support optimisation governance by establishing quantified baselines, benchmarks, and improvement tracking through analytics.

Stakeholder Engagement

  • Engage with plant operations, engineering, maintenance, control rooms, automation teams, and data specialists to support optimisation enablement.
  • Interface with APC, MES, analytics, and automation solution providers to support deployment and continuous improvement.
  • Collaborate with operational leadership to ensure analytics-driven optimisation initiatives align with plant priorities.

Risk, Safety & Compliance

  • Ensure all MES contributions, APC logic, analytics models, and loop tuning changes comply with site safety rules and approved management-of-change processes.
  • Ensure dynamic water balance systems and optimisation analytics are accurate, auditable, and defensible for compliance purposes.
  • Ensure optimisation activities respect operational envelopes, safety constraints, and production priorities.

Role Outcomes & KPIs

  • Improved process stability and controllability.
  • APC adoption across approximately 70% of targeted circuits.
  • Loop tuning adherence of approximately 85%.
  • Dynamic water balance compliance of approximately 95%.
  • Reduced unexplained process variability.
  • Reduced time from deviation detection to corrective action.
  • Increased percentage of optimisation initiatives supported by quantified analytics evidence.

Job Experience & Skills Required

  • Minimum of 5 years’ experience in process control, advanced automation, or analytics-driven optimisation within mineral processing or heavy industrial environments.
  • Hands-on experience in loop tuning, APC deployment, and control optimisation.
  • Proven ability to apply analytics to explain operational variability and quantify optimisation impact beyond descriptive reporting.
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How to Apply

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