Process Modelling (BPM)
for Manufacture of refined petroleum products (ISIC 1920)
Petroleum refining is intrinsically a process-driven industry with highly integrated, continuous, and complex operations. Each unit operation, from crude desalting to catalytic cracking, involves precise control, safety protocols, and significant energy consumption. BPM is perfectly suited to...
Strategic Overview
The 'Manufacture of refined petroleum products' industry is characterized by highly complex, integrated, and continuous processes, making Process Modelling (BPM) an indispensable tool. Refining involves a multitude of interconnected units, from crude distillation to sophisticated conversion processes, each with specific operating parameters, safety protocols, and environmental considerations. BPM provides a graphical and analytical framework to dissect these intricate workflows, enabling the identification of bottlenecks, redundancies, and areas of 'Transition Friction' that impede efficiency, increase costs, and elevate operational risks (LI01, PM01, DT06).
By mapping out current-state (as-is) and desired future-state (to-be) processes, refiners can systematically optimize throughput, reduce energy consumption (LI09), enhance product quality, and improve safety compliance (PM03, LI07). This is crucial for an industry where even minor operational inefficiencies can lead to substantial financial losses due to high capital and operational costs, coupled with potential environmental liabilities (LI08). BPM supports data-driven decision-making, providing a clear understanding of how changes in one part of the refinery impact others.
Ultimately, BPM facilitates continuous improvement in a highly regulated and high-stakes environment. It is instrumental in fostering a culture of operational excellence, enhancing real-time operational visibility (DT08), and ensuring the refinery can adapt more agilely to market demands and regulatory changes, thereby improving both short-term efficiency and long-term resilience against systemic risks and supply chain disruptions (LI05, LI06).
5 strategic insights for this industry
Interdependent Unit Operations & Cascading Effects
Refinery operations are highly interdependent; a change or inefficiency in one unit (e.g., crude distillation unit) can have cascading effects throughout the entire refinery (e.g., impacting feed quality to catalytic cracking, hydrotreating). BPM is critical for visualizing these interdependencies, understanding potential bottlenecks (LI03), and modeling the impact of operational changes to avoid unintended consequences and optimize overall refinery performance (LI05).
Safety, Compliance, and Environmental Integration
Process modeling is essential for integrating safety protocols, emergency response procedures, and environmental compliance requirements directly into operational workflows. By visually mapping these aspects, refiners can identify potential hazards, ensure adherence to stringent regulations (LI07, DT04), and minimize environmental liabilities (LI08), thereby reducing operational risks and potential downtime.
Logistics and Inventory Optimization
From crude intake and storage to intermediate product movement, blending, and final product dispatch, refinery logistics are complex and capital-intensive. BPM helps in mapping out these logistical flows, identifying points of friction (LI01), optimizing inventory levels (LI02) for various intermediate and final products, and streamlining transportation processes to reduce costs and improve lead times (LI05).
Energy Efficiency and Waste Heat Recovery
Refining is one of the most energy-intensive industries. BPM can pinpoint specific areas within processes where energy is consumed inefficiently or where waste heat can be recovered. By modeling energy flows, companies can identify opportunities for process modifications, equipment upgrades, and operational adjustments to reduce energy costs and improve the refinery's carbon footprint (LI09, ER01).
Data Integration and Operational Blindness
Many refineries suffer from data silos and fragmented systems (DT06, DT08), leading to operational blindness. BPM, when integrated with real-time data from SCADA/DCS systems, can provide a unified view of processes, enabling better monitoring, anomaly detection, and decision-making. This helps overcome information asymmetry (DT01) and improves overall operational control.
Prioritized actions for this industry
Develop Comprehensive End-to-End Process Maps for Core Operations
Systematically map all critical refinery processes, from crude arrival to product dispatch, including inter-unit flows and utility systems. This provides a baseline ('as-is') for identifying bottlenecks, redundancies, and areas of high 'Transition Friction' (LI01, PM01) across the value chain, crucial for strategic optimization.
Integrate Safety, Environmental, and Quality Protocols into Process Models
Embed all critical safety procedures, environmental compliance steps, and product quality checks directly into process models. This ensures these non-negotiable requirements are an integral part of operations, reducing risk, improving compliance (LI07, DT04), and minimizing the potential for costly incidents or fines (LI08).
Leverage Digital Twin Technology for Process Simulation and Optimization
Implement digital twins of key refinery units or the entire facility. This allows for real-time simulation of process changes, 'what-if' scenarios, and predictive maintenance, enabling proactive optimization, minimizing downtime, and testing improvements virtually before physical implementation (DT08, PM03).
Establish Cross-Functional Process Improvement Teams
Form teams comprising operators, engineers, maintenance personnel, and supply chain specialists to review and refine process models. This collaborative approach ensures practical relevance, secures buy-in from those executing the processes, and leverages diverse expertise to identify the most impactful improvements (DT07).
Automate Data Collection and Analytics for Continuous Process Monitoring
Implement systems to automatically collect, aggregate, and analyze real-time operational data (e.g., from DCS, LIMS, historians) and feed it into process models. This enables continuous monitoring of process performance against benchmarks, rapid detection of deviations, and data-driven insights for ongoing optimization and predictive anomaly detection (DT06, DT01).
From quick wins to long-term transformation
- Map one critical, high-impact process (e.g., crude unit operation, specific product blending sequence) to identify 2-3 immediate improvement areas.
- Conduct workshops with operators to document 'as-is' processes and identify pain points, leveraging their tacit knowledge.
- Implement visual management boards for key process KPIs in control rooms.
- Develop 'to-be' process models with clear, measurable improvements and integrate them with existing SCADA/DCS systems for real-time monitoring.
- Train operators and engineers on process modeling software and methodologies for ongoing optimization.
- Pilot digital twin applications for a single, complex refining unit (e.g., FCC, Hydrocracker) to optimize throughput or energy consumption.
- Standardize processes for critical maintenance and turnaround procedures.
- Establish an enterprise-wide process architecture that covers all refinery operations and interfaces with supply chain and commercial functions.
- Full deployment of digital twin technology for the entire refinery, enabling predictive optimization and 'lights-out' operations for certain units.
- Integrate AI/ML algorithms with process models for autonomous control and self-optimization capabilities.
- Develop a centralized 'Center of Excellence' for process modeling and operational analytics.
- Over-complicating models, leading to 'analysis paralysis' or models that are too complex to be practical.
- Lack of active involvement and buy-in from operational staff, leading to models that are not used or trusted.
- Neglecting data quality and integration, resulting in 'garbage in, garbage out' for models.
- Failing to link process improvements directly to tangible business KPIs (e.g., cost savings, throughput increase, safety metrics).
- Treating BPM as a one-time project rather than a continuous improvement initiative.
- Underestimating the change management required to embed new processes and ways of working.
Measuring strategic progress
| Metric | Description | Target Benchmark |
|---|---|---|
| Process Cycle Time Reduction (%) | Percentage decrease in the time taken to complete a specific process from start to finish. | 5-15% reduction in identified bottleneck processes. |
| Operational Uptime/Availability (%) | Percentage of time a unit or the refinery is operational and producing product, excluding planned maintenance. | >95% for continuous operations. |
| Energy Consumption per Barrel (GJ/bbl) | Total energy consumed per barrel of refined product. A direct measure of process efficiency. | Year-on-year reduction; benchmark against top-quartile industry performance. |
| Yield Improvement (%) | Increase in the percentage of higher-value products obtained from a given crude slate. | 1-3% improvement for key conversion units. |
| Incidence Rate (Safety/Environmental) | Number of safety incidents (e.g., LTI, recordables) or environmental excursions per million hours worked/per year. Process models can reduce risks. | Continuous reduction towards zero. |
Other strategy analyses for Manufacture of refined petroleum products
Also see: Process Modelling (BPM) Framework