Department of Industrial and Physical Pharmacy Personnel - Gintaras V. (Rex) Reklaitis
Specialization: Process Systems Engineering, Computer Aided Process Operations, Batch Process Design, Scheduling and Analysis
EducationBS, Illinois Institute of Technology, 1965
MS, Stanford University, 1969
PhD, Stanford University, 1969
Research: Process Systems Engineering, Computer Aided Process Operations, Batch Process Design, Scheduling and Analysis
Professor Reklaitis' research involves the application of computing and systems technology to support the design and operation of processing systems. A long term goal is to create a framework for and demonstrate the feasibility of fully computer integrated chemical manufacturing. Areas of recent emphasis are investigation of approaches to support batch and semi-continuous operations as well as methodology for plant- and enterprise-wide planning and optimization.
Batch process design encompasses the selection of processing recipe, operational schedules, equipment number and sizes, plant layout, and the staging of plant expansions. Batch plant design problems are challenging because they involve discrete choices, dynamics, and parameter uncertainty. Their solution requires developments in process and logistical decision modeling, combinatorial optimization techniques, combined discrete-continuous simulation methods, and probabilistic decision tools such as Monte Carlo methods. Problems of current interest include synthesis and design for waste minimization.
Batch operational problems include the detailed scheduling of multipurpose production facilities, taking into account technical, production, and market driven uncertainties, and the integration of scheduling decisions with enterprise-wide planning and process unit control functions. In the process setting, schedules define the assignment of equipment and other resources to manufacturing tasks, the sequencing of the execution of these tasks, and the determination of the precise timing for their execution. Areas of current interest include the investigation of techniques for developing robust schedules which give good performance in the presence of uncertainty, dynamic strategies for deciding when rescheduling is most appropriate, and the integration of scheduling models with detailed unit operational models.
Plant-wide optimization and planning research is concerned with the formulation of mathematical models and development of large scale solution strategies under which the operation of production facilities, multiple interacting plant sites, and entire supply chains can be effectively coordinated. Current emphasis is on hybrid systems for performing the interpretation and filtering functions and the design of RTO systems which can accommodate combined batch and continuous plant operations. The planning research is concerned with the development of models and methods for addressing problems of planning under uncertainty, including R&D planning as well as supply chain optimization applications. The technologies which are employed for these purposes include large scale linear, nonlinear, and discrete optimization methods, statistical techniques, knowledge-based methods, as well as combined discrete-continuous simulation tools.
Honors and Credentials
Jung, J.Y., Blau, G., Pekny, J.F., Reklaitis, G.V., and Eversdyk, D., "A Simulation-based Optimization Approach to Supply Chain Management under Demand Uncertainty," Computers & Chem Engr, 28 2087-2106 (2004).
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This record was last updated on Nov 14, 2017 at 3:56 PM