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GRP — Manufacturing Modernization & Industry 4.0

Jan 2019 – Sept 2022  ·  Head – Business Process (Indonesia)

$1M+
Annual savings (procurement)
80%
Inventory movement improvement
Months→Days
Procurement cycle
25+
ERP departments re-architected

I led the digital transformation of Gunung Raja Paksi — Indonesia's largest privately-owned steelmaker — during one of the most consequential periods in its history: its transition from a private company to a publicly listed entity. The mandate covered ERP modernization across 25+ departments, AI-driven procurement intelligence, C-suite analytics, and operational digitalization — all while keeping a 50-year-old steel plant running at full capacity.

Key Contributions

  • Cross-functional program leadership: managed engineering, OT, IT and analytics teams to deliver plant modernization roadmaps.
  • Process digitization & automation: replaced manual handoffs with automated data capture, sequence control and alarm analytics.
  • Real-time operations analytics: designed and rolled out dashboards and alerts for production, quality and maintenance KPIs.
  • Data platform & integrations: built ingestion pipelines from PLCs/SCADA to a central lake, enabling near-real-time analytics and reporting.
  • Change management & capability building: trained plant teams on new dashboards, SOPs and decision workflows to ensure adoption.

Context & Challenges

GRP operated multiple brownfield facilities with heterogeneous control systems and fragmented reporting. Key challenges included:

  • Legacy SCADA/PLC systems with inconsistent data models across lines.
  • Lack of near-real-time visibility into yield losses and scrap drivers.
  • Manual quality reconciliation and slow root-cause analysis cycles.
  • Pressure to increase throughput while maintaining product quality and safety.

Approach

The program used a phased, risk-managed approach:

  • Phase 1 — Rapid assessment and quick wins (data collection, pilot dashboards).
  • Phase 2 — Stabilize OT integrations (protocol adapters, unified tags, edge buffering).
  • Phase 3 — Central data platform (ingest, storage, near-real-time transforms) and enterprise reporting.
  • Phase 4 — Optimization loops: predictive maintenance, scrap reduction models and operator decision support.

Solution & Technology

Delivered an integrated stack combining OT adapters, streaming ingestion, curated serving layer and BI/visualization:

  • Edge adapters & buffering (MQTT / Kafka edge bridges) for reliable PLC/SCADA telemetry.
  • Streaming and batch pipelines (Kafka + Spark/Flink) to produce operational data streams and aggregates.
  • Serving layer (ClickHouse / Postgres) for sub-second KPI queries consumed by dashboards.
  • Model operationalization for scrap prediction and yield optimization (Python ML pipelines).
  • BI & dashboards (Power BI / QuickSight) with governed semantic models for leadership & operations.

Business Impact

  • $1M+ annual savings from AI-driven procurement intelligence — predictive scrap pricing and FX trend forecasting enabling optimal sourcing decisions.
  • Procurement cycle: months → days — automated workflows and real-time supplier intelligence collapsed decision time across the procurement chain.
  • Inventory movement improved 80% — QR-code tracking, mobile asset management, and just-in-time availability eliminated stock bottlenecks.
  • ERP modernized across 25+ departments — unified finance, HR, production, and maintenance data for the first time in the company's history.
  • Board-level data governance enabled — C-suite dashboards delivered data-driven strategic decisions during the IPO transition process.
  • Operational transparency at scale — real-time scrap cost dashboards and location-aware sourcing guidance reduced procurement cost volatility.

Selected Visuals

Click any image to enlarge.

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