About Us
Grad Studies
MACC Researchers
Dr. Chris L. E. Swartz
Professor and Director, MACC
Dofasco Chair in Process Automation and Information Technology
Dep. of Chemical Eng.

McMaster University
1280 Main Street West
Hamilton, ON L8S 4L7

Office: JHE-360
Voice: (905) 525-9140 x 27945
Email: swartzc@mcmaster.ca

[view profile on department website]

BSc(Eng) Chemical Engineering, Cape Town
PhD Chemical Engineering, Wisconsin
MAIChE, MCSChE, P.Eng., (Ontario)

Design for Dynamic Performance
Dynamic Optimization
Optimal Planning and Scheduling
Optimization and Control of Batch Process Systems using Data-Driven Models
Real Time Optimization
Supply Chain Optimization

Research Interests

Current trends of competition in an increasingly global market place, rising costs, and tightening environmental constraints make it increasingly important for process plants to be operated efficiently and in an environmentally responsible manner in order to remain competitive. This includes operation of individual process units, process plants, as well as the supply chains of which they are part. Mathematical optimization provides a tool for addressing this - as the basis of both decision-support and model-based control systems, and for optimal process design. My research focus is on applied optimization and automation of process systems, with the goal of developing mathematical formulations and solutions to improve the economics of operations, subject to prevailing operational, safety and environmental constraints. Key research thrusts are described below.

Design for Dynamic Performance

The design of a plant can have a significant impact on its ability to be satisfactorily controlled. Our research group has been involved in the development of optimization-based computational strategies, both for assessing plant operability and for incorporating operability requirements into optimal design calculations. A current application seeks to identify design limitations to transition speed in air separation plants, where rapid response to demand and electricity price changes is highly beneficial.

Dynamic Optimization of Process Operations

We consider optimization of transient processes described by differential-algebraic equation (DAE) systems in several contexts, with a focus toward industrial applications. (i) Electric arc furnaces (EAFs) are widely used in the steel industry for melting scrap, and are large consumers of electrical energy. Our group has been involved in the development of modeling and computational strategies for dynamic optimization of industrial EAF systems. (ii) Shutdowns in chemical processing plants are detrimental both to plant economics and critical product characteristics. We have developed formulation and computational strategies for determining optimal operating policies in the face of shutdowns in multi-unit operations, with application to a Kraft pulp mill. Current work extends the approach to include model discontinuities, handling of uncertainty through feedback, and optimal relaxation of specifications under abnormal operating conditions. (iii) A further area of study within our group is the interaction between model predictive control (MPC) and a higher-level optimization layer. This includes analysis of the performance of LP-MPC cascade control systems - a common configuration in commercial MPC implementations, and the analysis and development of dynamic real-time optimization (D-RTO) systems that utilize a dynamic model at the supervisory optimization level.

Computational Strategies for Large-Scale Dynamic Optimization

We are exploring the use of parallel computing approaches for the solution of large-scale dynamic optimization problems under uncertainty. A multiple-shooting approach is utilized for solving the dynamic optimization problem, with the uncertain parameter space discretized into a finite number of scenarios. The independent integration tasks are distributed among multiple processors for parallel solution.

Optimal Scheduling and Planning

Our research in this field is driven primarily by industrial needs, and our studies typically involve close collaboration with industrial partners. Recent and current studies include optimal raw material purchasing and plant operation under uncertainty in steel manufacturing, the development of optimal scheduling and planning formulations for an industrial food processing application, and optimal scheduling of converter aisle operations in a nickel smelting plant. In addition, we are exploring strategies for reactive scheduling, and systematic integration of planning and scheduling.

Supply Chain Optimization

Key drivers in the process industry toward an increased focus on supply chain technologies are increasing pressure to reduce costs and inventories due to market competition, a shift from commodity products toward low-volume, demand-driven specialty products, globalization of operations, and more rapidly fluctuating demands. Within our group, we consider strategies for optimal supply chain operation and design, as well as the development of computational tools for supply chain performance analysis. Work in this area includes (i) a novel robust model predictive control formulation for application to process supply chain systems, (ii) a supply chain formulation that includes time-limited transportation contracts within an optimal supply chain design, and (iii) development of a systematic framework for supply chain operability analysis, motivated by Canadian forest products industry transformation from commodity production to integrated biorefineries producing biofuels and specialty chemicals, where flexibility and responsiveness to accommodate market variation, feedstock variability and fluctuating customer demands is a key consideration.

Industrial Collaboration Our group collaborates with several industries through the McMaster Advanced Control Consortium (MACC), and the McMaster Steel Research Centre. MACC fosters industrially relevant research in process systems engineering and provides a community of academic researchers and industrial practitioners who share knowledge and experiences.

MACC Publications

  • Wang, H.Mastragostino, R.Swartz, C. L. E. Flexibility analysis of process supply chain networks, Computers & Chemical Engineering,, 84 409421 (2016) [ Publisher Version ]
  • Shyamal, S.Swartz, C. L. E. A Multi-rate Moving Horizon Estimation Framework for Electric Arc Furnace Operation, IFAC-PapersOnLine,, 49 (7) 11751180 (2016) [ Publisher Version ]
  • Cao, Y.Swartz, C. L. E., Baldea, M, Blouin, S Optimization-Based Assessment of Design Limitations to Air Separation Agility in Demand Response Scenarios, J Process Control,, 33 37-48 (2015) [ Publisher VersionOpen Access Version (free) ]
  • Washington, I.Swartz, C. L. E. Multi-Period Dynamic Optimization for Large-Scale Differential-Algebraic Process Models under Uncertainty, Processes,, 3 (3) 541-567 (2015) [ Publisher VersionOpen Access Version (free) ]
  • Washington, I.Swartz, C. L. E. Design under uncertainty using parallel multi-period dynamic optimization, AIChE Journal, (2014) [ Publisher Version ]
  • Mastragostino, R.Patel, S.Swartz, C. L. E. Robust decision making for hybrid process supply chain systems via model predictive control, Computers & Chemical Engineering,, 62 (5) 37-55 (2014) [ Publisher Version ]
  • Mastragostino, R.Swartz, C. L. E. Dynamic operability analysis of process supply chains for forest industry transformation, Ind Eng Chem Res,, 53 9825-9840 (2014) [ Publisher Version ]
  • Hazaras, Matt, Swartz, C. L. E.Marlin, T. E. Industrial application of a continuous-time scheduling framework for process analysis and improvement, Ind Eng Chem Res,, 53 259-273 (2014) [ Publisher Version ]
  • Chong, Z.Swartz, C. L. E. Optimal operation of process plants under partial shutdown conditions, AIChE Journal,, 59 (11) 4151-4168 (2013) [ Publisher Version ]
  • David Gerardi, Marlin, T. E.Swartz, C. L. E. Optimization of Primary Steelmaking Purchasing and Operation under Raw Material Uncertainty, Int Eng Chem Res,, 52 1238312398 (2013) [ Publisher Version ]
  • Hazaras, Matthew J., Swartz, C. L. E.Marlin, T. E. Flexible maintenance within a continuous-time state-task network framework, Computers & Chemical Engineering,, 46 (15) 167-177 (2012) [ Publisher Version ]
  • Mastragostino, R.Swartz, C. L. E. Operability considerations in process supply chain design for forest industry transformations, Paper 614e, AIChE Annual Meeting, Minneapolis., (2011)
  • Chong, Z.Swartz, C. L. E. Discontinuous modeling formulations for the optimal control of partial shutdowns, Proc. 18th IFAC World Congress, Milan, (2011)
  • Cao, Y.Swartz, C. L. E., Baldea, M. Design for dynamic performance: Application to an air separation unit, Proc. American Control Conference, San Francisco., (2011)
  • Hazaras, M., Swartz, C. L. E.Marlin, T. E. Optimal scheduling of an industrial food manufacturing facilit, Paper 356e, AIChE Annual Meeting, Salt Lake City., (2010)
  • Chong, Z.Swartz, C. L. E. Model-based control of multi-unit systems under partial shutdown conditions, American Control Conference, St. Louis, Missour, (2009)
  • Nikandrov, A., Swartz, C. L. E. Sensitivity analysis of LP-MPC cascade control systems, Journal of Process Control,, 19 16-24 (2009) [ Publisher Version ]
  • Soliman, M., Baker, R., Swartz, C. L. E. A mixed-integer formulation for back-off under constrained predictive control, Computers and Chemical Engineering,, 32 2409-2419 (2008) [ Publisher Version ]
  • MacRosty, R.D.M, Swartz, C. L. E. Dynamic optimization of electric arc furnace operation, AIChE J,, 53 (3) 640-657 (2007) [ Publisher Version ]
  • Lam, D.K., Baker, R., Swartz, C. L. E. Reference trajectory optimization under constrained predictive control, Canadian Journal of Chemical Engineering,, 85 454-464 (2007) [ Publisher Version ]
  • Baker, R., Swartz, C. L. E. Interior point solution of multilevel quadratic programming problems in constrained model predictive control applications, Industrial and Engineering Chemistry Research,, 47 81-91 (2007) [ Publisher Version ]
  • Chong, Z.Swartz, C. L. E. Dynamic re-optimization and control under partial plant shutdown scenario, AIChE Annual Meeting, (2006)
  • Baker, R., Swartz, C. L. E. Interior point solution of integrated plant and control design problems with embedded MPC, AIChE Annual Meeting, (2006)
  • Chong, Z.Swartz, C. L. E. A modeling language for dynamic optimization, CSChE Annual Meeting, (2006)
  • Nikandrov, A., Swartz, C. L. E. Stability and performance of LP-MPC cascade control systems, CSChE Annual Meeting, (2006)
  • MacRosty, R.D.M., Swartz, C. L. E. Optimization as a tool for process improvement in EAF operations, AISTech Conference, (2005)
  • MacRosty, R.D.M., Swartz, C. L. E. Dynamic modeling of an industrial electric arc furnace, Industrial and Engineering Chemistry Research,, 44 8067-8083 (2005) [ Publisher Version ]
  • Young, J.C.C., Baker, R., Swartz, C. L. E. Input saturation effects in optimizing control - inclusion within a simultaneous optimization framework, Computers and Chemical Engineering,, 28 1347-1360 (2004) [ Publisher Version ]
  • Soliman, M., Balthazaar, A.K.S., Swartz, C. L. E. Modeling and model-based control of an oxygen delignification unit, Control Systems Conference, (2004)
  • Baker, R., Swartz, C. L. E. Inclusion of actuator saturation as complementarity constraints in integrated design and control, DYCOPS 7, (2004)
  • Baker, R., Swartz, C. L. E. Rigorous handling of input saturation in the design of dynamically operable plants, Industrial and Engineering Chemistry Research,, 43 5880-5887 (2004) [ Publisher Version ]
  • Baker, R., Swartz, C. L. E. Simultaneous solution strategies for inclusion of input saturation in the optimal design of dynamically operable plants, Optimization and Engineering,, 5 5-24 (2004) [ Publisher Version ]
People by Picture