PETRONAS Refinery Unlocks $8.5 Million USD Per Year in Profit with Scheduling Automation Solution
公司规模
1,000+
地区
- Asia
国家
- Malaysia
产品
- Aspen Petroleum Scheduler
- Aspen Refinery Multi-Blend Optimizer
技术栈
- Database Management
- Scheduling Automation
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 功能应用 - 企业资源规划系统 (ERP)
适用行业
- 石油和天然气
适用功能
- 流程制造
用例
- 需求计划与预测
- 过程控制与优化
服务
- 系统集成
关于客户
PETRONAS is the national oil company of Malaysia and holds ownership and control of the petroleum resources for the entire country. It has grown from being the manager and regulator of Malaysia’s upstream sector into an oil and gas corporation, ranking among the FORTUNE Global 500. Recently, PETRONAS Melaka Refineries faced the challenge of creating an integrated refinery scheduling model to eliminate many standalone spreadsheets and leverage multi-user interaction under a single network. Any petroleum scheduling software considered had to be compatible with their current planning tool.
挑战
PETRONAS Melaka Refineries faced the challenge of creating an integrated refinery scheduling model to eliminate many standalone spreadsheets and leverage multi-user interaction under a single network. The process was long and tedious, and led to different versions of the same schedule — which increased the likelihood for errors and resulted in less than optimal crude production.
解决方案
To reduce error and improve collaboration, PETRONAS implemented Aspen Petroleum Scheduler and Aspen Refinery Multi-Blend Optimizer to automate the scheduling model under a single database. To better align planning and scheduling, AspenTech helped develop a customized template to integrate both Aspen Petroleum Scheduler and Aspen Refinery Multi-Blend Optimizer with PETRONAS’ current planning tool. The software allowed greater visibility and agility into the refinery model, yielding higher margins and lower production costs. Now schedulers can plot planned, scheduled and actual targets, while seeing variances as they occur and make necessary changes in a single network for better scheduler collaboration. As schedulers make changes, automated alerts notify the other schedulers of the changes, making it easier to adjust the schedule.
运营影响
数量效益
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