Lean Construction Research Group

MISSION

The Lean Construction Research Group at Cal State East Bay aims at leading innovative research to serve industry members in their Lean journey. We strive to achieve this goal by intersecting innovative technology and mental health and wellness interventions with Lean techniques. We apply these solutions in real world situations through industry collaboration and partnership.

CURRENT EFFORTS

Promoting and Supporting Lean Journeys and Learning

The growing implementation of IPD requires that professionals receive just-in-time training on the founding principles and strategies of Lean design and construction. However, practitioners might not only have the time to participate in continuous training, but they might also not have a self-awareness of their knowledge. To support future learning, an individual assessment instrument was developed so practitioners could assess their knowledge and efforts in implementing Lean principles, develop self-awareness, and self-regulate their journey. The instrument was developed by leveraging experiences and literature in Lean construction principles as well as theories of self-regulated learning in educational psychology. The instrument has been implemented in several IPD projects and received over 100 responses, and is now hosted on the official Lean Construction Institute website. With the instrument, we hope to promote the growth of individuals’ knowledge and efforts through the entire delivery process of a project.

CLICK HERE FOR THE LEAN ASSESSMENT INSTRUMENT

PAST Efforts

Leveraging Mobile Technology to Reduce Construction Waste

Based on a field-driven case study, the team focused on the analysis and removal of waste through the use of video studies and process modeling. In this case study, the researchers worked with superintendents and field workers to record the installation process of facade systems for an office building. After the video recording and on-site interviews, the team process mapped the installation and identified various types of wastes, which caused the installation to run inefficiently. Based on this analysis the team was able to identify that the installation could save over $200,000 and 25 days of field work.