To establish quantitative and qualitative measures of mechanical 3D model BOMs (Bills of Materials, i.e. pipe, valves, and fittings) sampled from industry, and to characterize these measures over the lifetime of a project. Focus is on absolute measures and on rate of change of measures. Create a mathematical-data model that can be used to predict growth and risk in a project that is partway complete, just by taking a small time-lapse sample of BOMs from the project. Bonus would be to include budgetary pricing.

1. Data Collection: Gather mechanical 3D model BOMs (Bills of Materials) from industry samples, ensuring a representative selection across different projects and stages of completion. (Note that we have much experience with extracting useful information from BOMs and have developed both procedures and software to facilitate it. We can quickly get to the interesting analysis.)
2. Quantitative and Qualitative Measures: Define and establish quantitative and qualitative measures to evaluate the BOMs. This may include factors such as the number of components, complexity, compatibility, quality, and cost.
3. Characterization of Measures: Analyze and characterize the established measures over the lifetime of a project to identify patterns, trends, and variations. This involves assessing how the measures change over time and their impact on project outcomes.
4. Mathematical-Data Model Development: Create a mathematical-data model that incorporates the collected measures to predict project growth and risk. This model should be able to generate insights and forecasts by analyzing a small time-lapse sample of BOMs from an ongoing project.
5. Growth and Risk Prediction: Apply the developed mathematical-data model to predict growth and risk in a project based on the analysis of the sampled BOMs. The model should provide valuable insights into future project performance, enabling stakeholders to make informed decisions.
6. Budgetary Pricing Integration (Bonus): Explore the possibility of incorporating budgetary pricing information into the mathematical-data model. This involves linking BOM measures with cost data to provide estimates of project expenses, enabling better financial planning and budget management.
7. Analysis and Reporting: Conduct in-depth analysis of the collected data, present findings, and generate reports with actionable recommendations for PointVerge. The analysis should highlight areas for improvement, potential cost savings, and strategies to optimize materials management and project execution.

Sean, the Chief Technology Officer, will be available for regular check-ins to answer any questions, address concerns, and provide guidance throughout the project. Mobile phone, email, Zoom, and Teams are primary methods. Sean can offer guidance in mathematics and database design, SQL and procedural SQL, and some programming (Python, C++). Access to a dedicated test server on Azure will be given (Postgresql running on custom Linux Virtual Machine).