Our research group is equipped with a suite of specialized tools and platforms that support high-quality applied research in Lean Six Sigma, process improvement, and operational excellence. These resources enable members to conduct robust statistical analyses, model processes, manage complex projects, and deliver impactful results in academic and industrial contexts.
Below is an overview of the key resources utilized by the group:
Minitab is a core statistical analysis tool used extensively in Six Sigma projects. It supports process capability studies, regression analysis, hypothesis testing, control charts, and more. It enables researchers and students to analyze data effectively and make evidence-based decisions.
Quality Companion is used for organizing improvement projects, mapping process flows, and integrating tools such as Fishbone diagrams and FMEA. It supports the full DMAIC cycle and enhances documentation and reporting in quality improvement projects.
Microsoft Visio is used for creating professional flowcharts, value stream maps, SIPOC diagrams, and process models. It helps visualize current and future states of processes, supporting Lean-based waste reduction and redesign efforts.
SmartPLS is used in advanced statistical modeling, particularly in structural equation modeling (SEM). It is valuable for validating measurement models and exploring relationships in behavioral and managerial research contexts tied to operational excellence.
The group uses project management tools like Microsoft Project, Trello, and Gantt charts to plan, execute, and track improvement initiatives. These tools help maintain clear timelines, responsibilities, and milestones for both student-led and faculty-driven research projects.
Integration with Internal and External Resources
The group utilizes the support provided by the Deanship of Scientific Research at the University of Jordan in several projects. In addition to internal tools, the group benefits from partnerships with industry and academic institutions, allowing access to real factory data, operational environments, and funding opportunities. These external resources are essential for validating research outputs in live contexts.