What does refinery optimization look like today? When we look at how most refineries are optimized, one particular picture emerges again and again: Today’s refinery optimization processes are largely manual. They also depend on qualified personnel with in-depth refinery process knowledge and the appropriate optimization technology. Due to demographic change, these specially qualified employees are becoming increasingly rare. Long-standing, experienced specialists are retiring and, together with the employees, the knowledge associated with them is being lost.<\/p>\n
Other challenges of refinery optimization today include:<\/p>\n
The enormous potential of digitization will also prevail in traditional industries such as refineries. In the future, planning and scheduling optimization models will use disruptive technologies such as machine learning and\/or cognitive computer functions using live data. The goal is to achieve a step change in the refinement of refinery optimization. Why machine learning and\/or cognitive computing functions should be used?<\/strong><\/p>\n The benefits of this include:<\/p>\n However, this is not limited to refinery optimization. Similar possibilities exist in the optimization of oil and gas production and the production of petrochemicals. This technology has the potential to make a major contribution to the human resource and sustainability challenges facing the industry.<\/p>\n Are you ready for the future?<\/p>\n “Predictive Maintenance with Smart Sensors”<\/a><\/p><\/blockquote>\n\n
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