HONEYWELL ENHANCES REFINING AND PETROCHEMICAL PLANNING SOLUTION

New Modelling Software Delivers Powerful and Flexible Solution to Help Refiners and Chemical Plant Operators Maximise Profitability
Honeywell today announced a major enhancement to its Refinery and Petrochemical Modelling System (RPMS) that  will improve model building and maintenance, case management, and optimisation to help plants maximise profitability. The new release, RPMS 500, incorporates analytics software that is based on the company’s innovative Intuition® process management to better apply planning results.

RPMS also helps refining and petrochemical firms assess their long-term investment options and understand the critical differences in potential yield and value of various feedstocks, as well as determining the best operating conditions over the planning horizon.
“RPMS Release 500 preserves the rich capability of RPMS while making it easier and more efficient to work with,” said Patrick Kelly, product director, Honeywell Process Solutions. “It also makes it simpler to build and maintain refinery planning models, and generate and review production plans. That helps provide information to help operators make the best production decisions. It includes a web-based tool that makes it easier for the broader organisation to access and analyse the information.”
Key new features with the RPMS 500 release include support for Windows™ 7/8 64-bit platforms, as well as tools to simplify migration to the current software version. Other enhancements provide improved case management, a new graphical user interface, HTML-based reporting, and improved optimisation capabilities.
These tools are critical to optimising the overall profitability of refining and petrochemicals operations and RPMS helps to drive and sustain improved profitability by enabling clients to assess more options and align the organisation more effectively to the plan. Effective planning is critical to help today’s process industries increase profitability. RPMS helps enable development and analysis of advanced mathematical programming models, utilising linear programming (LP) optimisation to answer key business questions related to raw material purchases, product specifications, plant operation, and distribution and logistics.