## Appendix A
### VSM in Analyze Site Selection Criteria
#### Design Phase  
This subsection describes the framework's applicability during the design phase, with each stage elaborated sequentially according to the corresponding rows in Table 7.  
Kaizen in Analyzing Structural Performance  
Figure 14 illustrates the use of Kaizen with BIM and AI Predictive Analytics to optimize structural performance in construction projects [88]. This cyclical process includes defining objectives, identifying issues, implementing improvements, and validating results, ensuring continuous refinement and high structural performance. The process starts with Defining Objectives and Baseline using BIM to model structural metrics like load capacity and material use. Identifying Issues apply AI simulations to detect inefficiencies such as overdesign or waste, supported by stakeholder workshops. In Propose and Implement Improvements, AI guides design adjustments, which are validated through BIM simulations and stakeholder review. Validate and Standardize confirms that the refined design meets all performance criteria, with lessons learned documented for future use. KPI impacts include cost savings from optimized material use, quality and safety improvements through validated structural performance, process optimization via AI-driven simulations, enhanced collaboration through real-time stakeholder engagement, and waste reduction by minimizing unnecessary material usage. TQM in Analyze Energy and Lighting Performance  
Figure 14 demonstrates the integration of BIM, Total Quality Management (TQM), and IoT to improve energy performance in building designs [89]. BIM provides a platform for energy simulations, IoT sensors supply real-time consumption data, and TQM ensures systems meet quality standards through continuous feedback. This process also applies to lighting performance optimization. Defining Energy Goals starts with BIM simulations to set targets, such as reducing consumption or achieving certifications like LEED or BREEAM. In Monitoring, IoT sensors capture real-time data on HVAC, lighting, and system efficiency, feeding this into BIM for comparison with targets. Identifying and Addressing Gaps uses TQM workshops to resolve issues like poor insulation or HVAC inefficiencies. Simulating and Validating Improvements updates the BIM model with proposed enhancements, validated through re-simulations. Feedback and Continuous Improvement uses IoT data to monitor performance post-implementation, refining future strategies. Key KPI benefits include cost savings through lower energy use, improved productivity from optimized systems, waste reduction by eliminating inefficiencies, enhanced quality and safety through compliance with standards, and ongoing process optimization via real-time IoT and BIM integration. Visual Management Techniques in Coordinating Design Models  
The diagram illustrates the use of Visual Management Techniques (VMT) to coordinate multidisciplinary design models [87]. It integrates a Common Data Environment (CDE) as the central platform, Kanban boards for workflow tracking, and AR/VR for enhanced spatial understanding. Standardized communication protocols and continuous improvement practices ensure team alignment and reduce errors. The process starts by Establishing a CDE (e.g., BIM 360, ProjectWise) to centralize models and documents. Visualizing the Workflow uses Kanban boards and color-coding to track progress transparently. AR/VR integration provides real-time spatial overlays and virtual walkthroughs to detect clashes and gather feedback. Standardizing Communication applies templates and symbols to unify project communication. Continuous Improvement is maintained through regular reviews and feedback loops. KPI benefits include improved time efficiency through real-time tracking, enhanced collaboration via AR/VR and CDE platforms, process optimization through automated updates and centralized data access, and waste reduction by minimizing errors and rework, supporting a more efficient design process.