A Comparison of Data Models in Chemical Engineering

Several data models have been developed in the domain of chemical engineering as the basis of specialized computer-aided tools, for the exchange of data between different tools, or to obtain a better understanding of the domain in order to improve its work processes and to provide specific support functionalities. All these data models where developed independently from each other and for specific applications. Within this paper, a comparison of different chemical engineering data models, that are currently developed and used, is attempted. First some fundamentals of data modeling will be presented. General requirements of data models are given as well as requirements that are specific to chemical engineering. These requirements and the covered data scope build the basis for the discussion and comparison of the data models. Based on this analysis, open issues in data modeling are derived that need to be approached in order to obtain high quality data models as a basis for information management and support of concurrent engineering.

[1]  Gabor Karsai,et al.  The new metamodeling generation , 2001, Proceedings. Eighth Annual IEEE International Conference and Workshop On the Engineering of Computer-Based Systems-ECBS 2001.

[2]  Manfred Nagl,et al.  Tool integration via interface standardization , 1998 .

[3]  Yoram Reich,et al.  Building Agility for Developing Agile Design Information Systems , 1999 .

[4]  James F. Davis,et al.  Sharable engineering knowledge databases for intelligent system applications , 1997 .

[5]  B. Chandrasekaran,et al.  Functional Representation and Causal Processes , 1994, Adv. Comput..

[6]  J. R. Whiteley,et al.  Knowledge-based interpretation of sensor patterns , 1992 .

[7]  Wolfgang Marquardt,et al.  Towards integrated information models for data and documents , 2004, Comput. Chem. Eng..

[8]  Gabor Karsai,et al.  Model-embedded on-line problem solving environment for chemical engineering , 1995, Proceedings of First IEEE International Conference on Engineering of Complex Computer Systems. ICECCS'95.

[9]  Alison McKay,et al.  A Framework for Product Data , 1996, IEEE Trans. Knowl. Data Eng..

[10]  Yuji Naka,et al.  PLANT ONTOLOGIES BASED ON A MULTI-DIMENSIONAL FRAMEWORK , 2022 .

[11]  William E. Lorensen,et al.  Object-Oriented Modeling and Design , 1991, TOOLS.

[12]  Wolfgang Marquardt,et al.  Integration of data models for process design — first steps and experiences , 2000 .

[13]  Yoram Reich,et al.  Designing the process design process , 1997 .

[14]  Wolfgang Marquardt,et al.  An object-oriented representation of structured process models , 1992 .

[15]  Wolfgang Marquardt,et al.  Computer-aided process modeling with MODKIT , 2001 .

[16]  Gabor Karsai,et al.  Model-Integrated Computing , 1997, Computer.

[17]  Yuji Naka,et al.  A life-cycle approach for model reuse and exchange , 2002 .

[18]  Andreas A. Linninger,et al.  A systems approach to mathematical modeling of industrial processes , 2000 .

[19]  Ming Liang Lu,et al.  A Multidimensional Design Framework and Its Implementation in an Engineering Design Environment , 1999 .