Gwangjae Kim
Pohang University of Science and Technology · 経営学
研究室紹介
Professor Gwangjae Kim's research lab specializes in advanced manufacturing systems and service innovation, focusing on the optimization of complex multiresponse and multistage manufacturing processes. The lab develops data-driven methodologies such as Patient Rule Induction Method (PRIM) for multiresponse optimization and applies them to real-world industrial challenges in sectors like steel, automotive, and semiconductors. It also pioneers design frameworks for experience-centric services (ExS) and product-service systems (PSS), emphasizing customer experience and strategic business model innovation. The lab integrates statistical modeling, quality function deployment, and visual design tools to support industrial R&D and sustainable competitive advantage.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15SUMMARY A modelling approach to optimize a multiresponse system is presented. The approach aims to identify the setting of the input variables to maximize the degree of overall satisfaction with respect to all the responses. An exponential desirability functional form is suggested to simplify the desirability function assessment process. The approach proposed does not require any assumptions regarding the form or degree of the estimated response models and is robust to the potential dependences
A product-service system (PSS) is a novel type of business model that integrates products and services in a single system. It provides a strategic alternative to product-oriented economic growth and price-based competition in the global market. This research proposes a methodology to support the generation of innovative PSS concepts, called the PSS concept generation support system. The models and strategies of 118 existing PSS cases were analyzed, and the insights extracted were used to develop
Click to increase image sizeClick to decrease image sizeKey Words: Quality function deploymentTarget Design characteristicsOptimizationSpreadsheet