(728d) Conceptual Modelling for Integrated Decision-Making in Process Systems
Researchers in the PSE area suggest that one way to build mathematical models is to create the first instance of a DMM from a conceptual description of a problem. After the first instance, model builders keep revising, extending, reducing, and refining mathematical models considering objectives, balances, physical properties, engineering practices, economic information, and many other elements related to the problem. This approach to building DMMs is very straightforward; the practice of systematic procedures has been successfully applied for decades. This work, however, proceeds with a considerably different approach and takes model building one-step further. The idea is to take a step back from the current PSE practices and model the model building procedures by using conceptual modelling. During the developments of the work, research questions have been: (i) how to build DMMs? and (ii) how to systematize decision-making model-building procedures?
The core component required to build DMM is the conceptual description of the reality, where the DMM is expected to function (i.e. from this conceptual description, systematization is feasible). In order to provide a comprehensive conceptual description, two comprehensive models related to the different domains of interest have been built: the Process Systems (PS) Domain for the conceptualization of the multi-level structure that appear in PS and Conceptual Constraint (CC) Domain for the conceptualization of operations research models. The PS Domain includes concepts and relations that appear in enterprise/process control standards (i.e. the process model, the physical model, and the procedural control model); the domain supports PS to build, design, and run to produce products. The CC Domain contains the required concepts and relations with the purpose of representing and identifying DMMs; the domain supports the building of DMMs with the conceptual representation. Overall, the developed methodologies for this framework are aimed at the systematic coordination and operation of the activities in PS taking into account the knowledge management throughout the (hierarchical) levels and DMMs.
A novel way of conceptualizing DMMs has been introduced with a new domain (the CC Domain) to support the systematic DMM building procedures. The CC Domain aims to conceptualize DMMs by classifying constraints, aggregating abstract pieces of information related to constraints, and generalizing occurrences in the input structure. Additionally, the domain integration between the PS Domain and the CC Domain is achieved. Finally, the core contributions are the DMM conceptualization by modelling elements of the CC Domain and the domain integration between the PS Domain and the CC Domain.
Afterwards, initial applications, related to the CC Domain supported/demonstrated through the PS Domain, have been introduced with the support of previous PS, DMMs, and conceptualization studies. Several procedures built through sequences and DMM construction algorithms along with case studies showing the systematic generation of DMMs have been presented as an application methodology. The algorithm and required sequences have been developed for the application of the CC and PS Domains for two general functionalities: identification and integration; different case studies have been introduced considering the multi-level functional hierarchies and provide a glimpse of implications of the framework. These procedures are capable of identifying DMMs using the CC Domain (i.e. DMM learning from state of the art) and using already established DMMs can be used to solve extended problems or problems from completely different domains. The core contribution is the functioning algorithms and sequences for the application of the CC and PS Domains.
One of the significant implications is the reduction of the time and effort on the mathematical model building. The aim is to at least provide a first comprehensive DMM instance. The developed methodologies may support non-specialists as well as model building specialists on the subject. While the work supports the non-specialist on building the first instance of their model without in-depth knowledge on the topic, PS Engineers can rely on this methodology to avoid the repetitive tasks related to the model building.
Overall, this work on the construction of DMMs, the âmodelling of the modelling processâ, has been developed as a contribution to the PSE area.
Financial support from the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (project AIMS DPI2017-87435-R and ECOCIS DPI2013-48243-C2-1-R), and AGAUR (2014-SGR-1092-CEPEiMA and grant FI) is fully appreciated.
Dombayci, C., CapÃ³n-GarcÃa, E., MuÃ±oz, E. and EspuÃ±a, A. (2017) âConstraint Identification and Integration Procedures in Multi-Level Hierarchical Systemsâ, in Computer Aided Chemical Engineering, pp. 2359â2364. doi: 10.1016/B978-0-444-63965-3.50395-0. Available from: http://linkinghub.elsevier.com/retrieve/pii/B9780444639653503950
Dombayci, C. and EspuÃ±a, A. (2017a) âModelling Decision Support Systems using Conceptual Constraints - Linking Process Systems Engineering and Decision Making Modelsâ, in Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. SCITEPRESS - Science and Technology Publications, pp. 147â154. doi: 10.5220/0006485201470154. Available from: http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/000648520...
Dombayci, C. and EspuÃ±a, A. (2017b) âSystematic decision-making models through Conceptual Constraintsâ, in Computer Aided Chemical Engineering, pp. 1873â1878. doi: 10.1016/B978-0-444-63965-3.50314-7. Available from: http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/000648520...