The research has been sponsored by the National Science Foundation, DOE/Sandia, Caterpillar, John Deere, and the University of Illinois.

Green profit design: enabler for sustainable design and manufacturing

We develop foundations for modeling the link between product design (pre-life) and take-back and recovery (end-of-life) and evaluating which design is better than others and why. Our framework can analyze how architectural differences affect product recovery and what design properties are desirable from the end-of-life perspective. Using the framework, designers can answer the question, ``which product design is better and why from the whole life cycle perspective.”  Ultimately, they can find optimal product design with greater recovery profit.

Application areas: consumer electronics (cell phone, personal computers, etc.), automotive vehicles, military combat systems, heavy-duty equipment, and building design.

Sustainability


Product and design analytics: trend-mining design

The goal of a firm to produce a portfolio of products is to maximize the profit while meeting the needs of customers. This product design and development process is modeled as a hierarchical decision making process. Research agenda includes predictive data mining for demand analysis, innovative new product concept generation, and green, environmentally conscious design.

Application areas: green product design and manufacturing, product family design and optimization, product pricing and production planning, production scheduling, and reconfigurable/changeable system design.

Multidisciplinary design optimization (Analytical Target Cascading)

For large-scale system design, traditional all-in-one approach is not feasible due to its complexity. Based on decomposition and coordination theories, multidisciplinary design optimization (MDO) approaches have been successful to address issues related to the multidisciplinary design. Built upon Analytical Target Cascading (Kim, 2001), research agenda include developing coordination strategy based on Lagrange dual formulation, propagation of uncertainties in hierarchical formulation, transformation of hierarchical approaches to non-hierarchical approaches, and mathematical programming with equilibrium constraints.

Application areas: automotive and consumer electronics portfolio design, changeable/dynamic system design such as automotive engine and deduster, and dual-use (civilian/military) system design.


ATC framework


Reconfigurable product family: air quality assurance and aerodynamic particle separators

We develop foundations for reconfigurable product family design optimization. In this work, a top-down product family design methodology is developed that enables product design engineers to identify the optimal number of product architectures directly from the customer preference data set by employing data mining attribute weighting and clustering techniques. The methodology also presents an efficient component sharing strategy to aid in product family commonality decisions. Two key data mining models are integrated in this work to help guide the product design process: (1) the ReliefF attribute weighting technique that identifies and ranks product attributes, and (2) the X-means clustering approach that autonomously identifies the optimal number of candidate products. Product family commonality decisions are guided by once again employing the X-means clustering technique, this time to identify the
components across product families that are most similar. A family of prototype aerodynamic air particle separators is used to evaluate the efficiency and validity of the proposed product family design methodology.

Application areas: air quality assurance systems design, aerodynamic particle separators, deduster family

deduster


Energy systems engineering and design informatics - conventional, renewable, or hybrid energy generation, conversion, and distribution

We develop a dynamic multi-mode design methodology for an efficient energy conversion system. The research will characterize and model key design aspects of an engineering system that must undergo multiple operating conditions, formalize the design methodology, and validate the methodology in a realistic energy conversion system design case. The design methodology utilizes the idea of equilibrium (or complementarity) constraints in a multidisciplinary design optimization framework. The research provides and validates a new class of problems and solutions for dynamic multi-mode system design that is emerging from the energy conversion system design practices in industry, including alternative energy sources.

Application areas: diesel engine, wind energy generation, hybrid energy generation combining multiple sources.


windfarm
Complementarity

System of systems optimization for product, process and service design

We aim at developing a holistic modeling methodology that captures the system of systems as a dynamic transient entity rather than static compilation of single systems. Research agenda includes analyzing choice behavior of customers, modeling preference/demand, designing product for operations, and planning multistage design and operations.

Application areas: transportation system, health care, product family design (cellular phones, hand tools, brake system), vehicle routing problem, flow management problem, quality in manufacturing and transactions, hierarchical design under uncertainty, system entity protection and recovery.


Concurrent Design for Aircraft and Routing


System of Systems Optimization e.g. US Electric Power Grid and Combat Systems



Journal publications

Harrison Kim also publishes full-length conference papers in peer-reviewed conferences in ASME, AIAA, IEEE, Design Society, and INCOSE.

J42. Avrithi, K. and Kim, H. M. "Optimization of Piping Supports and Supporting Structure," Accepted, Transactions of ASME: Journal of Pressure Vessel Technology, 2017.

J41. Quan, N. and Kim, H. M. "Numerical Assessment of the Greedy Algorithm for Solving Quadratic Knapsack Problems in Grid-based Wind Farm Layout Optimization," under review, 2016.

J40. Kim, H.M., Cluzel, F., Leroy, Y., Yannou, B. and Bertoluci, G., "Research perspectives in sustainable design," under review, 2015.

J39. Kwak, M. and Kim, H. M. "Assessing the economic and environmental impact of off-road equipment from the customer’s perspective: a model for integrated life-cycle costing (LCC) and life-cycle assessment (LCA)," under review, 2013.

J38. Lee, G., Ahn, H., Kim, H. M. and Lee, C. "Environmental and Economic Impacts in Scenario-Based Automotive Part Replacement: A Case Study of Constant Velocity (CV) Joint Replacement in Korea," under review, 2015.

J37. Quan, N. and Kim, H. M. "A Mixed Integer Linear Programing Formulation for Unrestricted Wind Farm Layout Optimization," Transactions of ASME: Journal of Mechanical Design, Vol. 138, 2016.

J36. Kwak, M. and Kim, H. M. "Green Profit Maximization through an Integrated Pricing and Production Planning for a Line of New and Remanufactured Products," Journal of Cleaner Production, 2016.

J35. Kwak, M. and Kim, H. M. "Modeling Time-Varying Advantages of Remanufacturing: Is a ‘Reman’ Better than a ‘Brand New’?," Transactions of ASME: Journal of Mechanical Design, Vol. 138, 2016.

J34. Ma, J. and Kim, H. M. "Predictive Model Selection for Forecasting Product Returns," Transactions of ASME: Journal of Mechanical Design, Vol. 138, 2016.

J33. Ma, J. and Kim, H. M. "Highly Customizable Product Family Design with Predictive, Data-Driven Family Design Method," Research in Engineering Design, pp. 1-17, September, 2015.

J32. Ma, J. and Kim, H. M. "Predictive Usage Mining for Life Cycle Assessment," Transportation Research - Part D,  Vol. 38, pp. 125-143, July 2015.

J31. Ma, J. and Kim, H. M. "Continuous Preference Trend Mining for Optimal Product Design with Multiple Profit Cycles," Transactions of ASME: Journal of Mechanical Design, Vol. 136, 2014.

J30. Ma, J., Kwak, M. and Kim, H. M. "Demand Trend Mining for Predictive Life Cycle Design," Journal of Cleaner Production, Vol. 68, pp. 189-199, 2014.

J29. Kwak, M. and Kim, H. M. "Design for lifecycle profit with a simultaneous consideration of initial manufacturing and end-of-life remanufacturing," Engineering Optimization Journal, Dec. 2013.

J28. Lu, S. and Kim, H. M. "Wind Farm Layout Design Optimization Through Multidisciplinary Design Optimization with Complementarity Constraints," Engineering Optimization Journal, Vol. 46, No. 12, pp. 1669-1693, 2014.

J27. Kwak, M. and Kim, H. M. "Market Positioning of Remanufactured Products with Optimal Planning for Part Upgrades," Transactions of ASME: Journal of Mechanical Design, Vol. 135, No. 1, 2013.

J26. Rojas, A. and Kim, H. M. "Incorporating Security Considerations Into Optimal Product Architecture and Component Sharing Decision in Product Family Design," Engineering Optimization Journal, Vol. 44, No. 1, pp. 55-74, 2012.

J25. Kannan, A., Shanbhag, U.V. and Kim, H. M., "Addressing supply-side risk in uncertain power markets: stochastic Nash models, scalable algorithms and error analysis," Optimization Methods and Software, 2012.

J24. Kwak, M., Kim, H. M. and Thurston, D. "Formulating Second-Hand Market Value as a Function of Product
Specifications, Age, and Condition
," Transactions of ASME: Journal of Mechanical Design, Vol. 134, No. 3, 2012.

J23. Tucker, C. and Kim, H. M. "Trend Mining for Predictive Product Design," Transactions of ASME: Journal of Mechanical Design, Vol. 133, No. 11, 2011.

J22. Kwak, M., Behdad, S., Zhao, Y., Kim, H. M. and Thurston, D. "E-waste Stream Analysis and Design Implications," Transactions of ASME: Journal of Mechanical Design, Vol. 133, No. 10, 2011.

J21. Kannan, A., Shanbhag, U.V. and Kim, H. M., "Strategic Behavior in Power Markets under Uncertainty," Journal of Energy Systems, Vol. 2, No. 2, 2011.

J20. Rojas, A. and Kim, H. M. "Optimal Component Sharing in Product Family by Simultaneous Consideration of Minimum Description Length and Impact Metric," Engineering Optimization Journal, October, Vol. 43, No. 2, pp. 175-192, 2011.

J19. Kwak, M. and Kim, H. M. "Assessing Product Family Design from an End-of-Life Perspective," Engineering Optimization Journal, Vol. 43, No. 3, pp. 233-255, 2011.

J18. Ramani, K., Ramanujan, D., Bernstein, W., Zhao, F., Sutherland, J., Handwerker, C., Choi, J., Kim, H. M. and Thurston, D., "Integrated Sustainable Life Cycle Design: A Review," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 9, 2010.

J17. Lu, S., Schroeder, N., Kim, H. M. and Shanbhag, U., "Hybrid Power/Energy Generation System Design through Multidisciplinary and Multilevel Design Optimization Problems with Complementarity Constraints," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 10, 2010.

J16. Kwak, M. and Kim, H. M. "Evaluating End-of-Life Recovery Profit by a Simultaneous Consideration of Product Design and Recovery Network Design," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 7, 2010.

J15. Zhao, Y., Pandey, V., Kim, H. M. and Thurston, D. "Varying Lifecycle Lengths within a Portfolio For Product Take-Back," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 9, 2010, 2010. (The conference version won the best paper award in 2009 ASME IDETC/CIE Design for Manufacturing and Life Cycle Conference.)

J14. Lu, S. and Kim, H. M. "A Regularized Inexact Penalty Decomposition Algorithm for Multidisciplinary Design Optimization Problem with Complementarity Constraints," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 4, 2010.

J13. Behdad, S., Kwak, M., Kim, H. M. and Thurston, D. "Simultaneous Selective Disassembly and End-Of-Life Decision Making For Multiple Products," Transactions of ASME: Journal of Mechanical Design, Vol. 132, No. 4, 2010.

J12. Kim, H. M., Lu, S., Kim, B.-D. and Kim, J.-S., "Parallel, Multistage Model for Enterprise System Planning and Design," IEEE Systems Journal, Vol. 4, No. 1, pp. 6-14, 2010.

J11. Tucker, C., Kim, H. M., Barker, D., and Zhang, Y. "A ReliefF attribute weighting and X-means clustering methodology for top-down product family optimization," Engineering Optimization Journal, Vol. 42, No. 7, pp. 593 - 616, 2010.

J10. Tucker, C. and Kim, H. M., "Data-Driven Decision Tree Classification for Product Portfolio Design Optimization," Transactions of ASME: Journal of Computing and Information Science in Engineering, Vol. 9, No. 4, 2009.

J9. Tucker, C. and Kim, H. M., "Optimal Product Portfolio Formulation by Merging Predictive Data Mining with Multilevel Optimization," Transactions of ASME: Journal of Mechanical Design, Vol. 130, pp. 991-1000, April 2008. (Also, a finalist for the best student paper competition in the 11th AIAA/ISSMO MAO Conference, Sept., 2006.)

J8. Kim, H. M., Chen, W., and Wiecek, M., "Lagrangian Coordination for Enhancing the Convergence of Analytical Target Cascading," AIAA Journal, Vol. 44, No. 10, pp.2197 - 2207, 2006.

J7. Liu, H., Chen, W., Kokkolaras, M., Papalambros, P.Y., and Kim, H. M. "Probabilistic Analytical Target Cascading - A Moment Matching Formulation for Multilevel Optimization under Uncertainty," Transactions of ASME: Journal of Mechanical Design, Vol. 128, pp. 991-1000, July 2006 (also presented in 2005 ASME DAC).

J6. Kim, H. M., Kumar, D. K. D., Chen, W., and Papalambros, P. Y., "Target Exploration for Disconnected Feasible Regions in Enterprise-Driven Multilevel Product Design," AIAA Journal, Vol. 44, No. 1, pp. 67-77, 2006.

J5. Cooper, A. B., Georgiopoulos, P., Kim, H. M., and Papalambros, P. Y., "Analytical Target Setting: An Enterprise Context in Optimal Product Design," Transactions of ASME: Journal of Mechanical Design, Vol. 128, No. 1, pp. 4-13, 2006.

J4. Kim, H. M., Rideout, D. G., Papalambros, P. Y., and Stein, J. L., "Analytical Target Cascading in Automotive Vehicle Design," Transactions of ASME: Journal of Mechanical Design, Vol. 125, pp. 474-480, 2003

J3. Kim, H. M., Michelena, N. F., Papalambros, P. Y., and Jiang, T., "Target Cascading in Optimal System Design," Transaction of ASME: Journal of Mechanical Design, Vol. 125, pp. 481-489, 2003.

J2. Kokkolaras, M., Fellini, R., Kim, H. M., Michelena, N. F., and Papalambros, P. Y., "Extension of the Target Cascading Formulation to the Design of Product Families," Journal of Structural and Multidisciplinary Optimization, Vol. 24, Issue 4, pp. 293-301, 2002.

J1. Kim, H. M., Kokkolaras, M., Louca, L., Delagrammatikas, G., Michelena, N. F., Filipi, Z., Papalambros, P. Y., and Assanis, D., "Target Cascading in Vehicle Redesign: A Class VI Truck Study," International Journal of Vehicle Design, Vol. 29, No. 3, pp. 199-225, 2002.

Book Chapters

B3. Kwak, M. and Kim, H. M., "Product Family Design and Recovery for Lifecycle, Advances in Product Family and Product Platform Design (Edited by Simpson, T., Jiao, R., Siddique, Z. and Holtta-Otto, K.), Springer, 2013.

B2. Kumar, D.K.D., Chen, W., and Kim, H. M., "Multi-level Optimization for Enterprise Driven Decision-Based Product Design," Decision Making in Engineering Design (Edited by Lewis, K, Chen, W. and Schmidt, L.), ASME Press, 2006.

B1. Kokkolaras, M., Fellini, R., Kim, H. M., and Papalambros, P.Y. "Analytical Target Cascading in Design of Product Families," Product Platform and Product Family Design: Methods and Applications (Edited by Simpson, T.W., Siddique, Z., Jiao, J.), Kluwer Academic Publishing, New York, 2005.