A strategy for enhancing the operational agility of petroleum refinery plant using case based fuzzy reasoning method. (4th March 2018)

• Record Type: Journal Article
• Authors: Zhang, Zhiping; Chen, Dingjiang; Feng, Yuzhong; Yuan, Zhihong; Chen, Bingzhen; Qin, Weizhong; Zou, Shengwu; Qin, Shui; Han, Jifei
• Is Part Of: Computers & chemical engineering. Volume 111(2018)
• Page Start: 27
• Page End: 36
• Publication Date: 2018-03-04
• Subjects: Reformulated case structure -- Case base -- Fuzzy matching -- Fluidized catalytic cracking unit -- Smart process manufacturing; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2017.12.021
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A fuzzy matching based approach to retrieve cases from the case base of petrochemical plants was developed for enhancing the operation agility. Based on the case disturbance method, a general optimization problem is formulated to find the optimal parameters of the FMF. A new criterion, namely stability number is proposed as the performance metric for quantifying different FMFs, based on which an appropriate FMF could be chosen. An application of the strategy to a practical FCCU of Sinopec Company is demonstrated. Abstract: Operational agility, which represents the capability of the plant/facility regarding the fast detection and adaption to the new situations facing external/internal changes, is commonly regarded as one of central-properties for Smart Process Manufacturing. Clearly, operational agility significantly affects the plant/facility performance such as profit and safety. In this work, a strategy for enhancing the operational agility of petroleum refinery plants is proposed. For this strategy, the accumulated data sets from the industrial plants as well as the high-fidelity simulation activities are firstly processed to formulate the case base with a determined structure. Fuzzy matching is adopted to evaluate the similarity between the new coming case and the potential one in the formulated case base. A new criterion, namely stability number, is proposed as the performance metric for choosing an appropriate type of Fuzzy membership function (FMF). Furthermore, an optimization model is set to optimize parameters of the selected Fuzzy membership function. The application of the proposed strategy to an industrial Fluidized Catalytic Cracking Unit (FCCU) is performed to demonstrate the relevant effectiveness.