Analytical modeling of supply chain quality management coordination and integration: A literature review

Abstract

Development of analytical models on coordination and integration of quality management in the supply chains context is an ongoing research avenue. The purpose of this paper is to identity the main contributions, model types, applied tools, and research trends on analytical modeling of supply chain quality management (SCQM) coordination and integration. This paper develops a comprehensive literature review and a taxonomical classification on the studies published from 2000 to 2018, which proposed analytical models for SCQM coordination and integration. The pending issues to be solved in analytical modeling of SCQM coordination and integration are focused on how to develop dynamical models that incorporate a greater number of factors and agents of the supply chains. The new models to be proposed should consider multiple products, time periods, supply chain levels, and adequate performance indicators and objective functions, which allow analyzing how quality management practices affect the supply chain overall performance.

KEY WORDS:

• coordination
• integration
• modeling
• supply chain quality management
• taxonomy

About the authors

Juan M. Cogollo-Flórez is a professor in the Department of Quality and Production, Instituto Tecnológico Metropolitano-ITM, Medellín, Colombia. He received a master’s degree in management engineering in 2011 from the Universidad Nacional de Colombia. He is currently a doctoral student in engineering - industry and organizations at Universidad Nacional de Colombia. His current research interests are performance measurement, supply chain quality management and advanced statistical quality control.

Alexander A. Correa-Espinal is a full professor in the Department of Organizational Engineering, Universidad Nacional de Colombia, Medellín, Colombia. He received a doctorate in statistics and operational research in 2007 from the Universitat Politècnica de Catalunya (Spain) and the master’s degree in industrial engineering in 1999 from the Universidad de los Andes (Colombia). His current research interests are advanced design of experiments, advanced statistical quality control, and total quality management.