4. Developing a Project Description
This article contains the following sections:
- Gathering Materials
- Sample Project Description
You are responsible for creating a detailed project description for the implementation team to follow. Later, the Sight Machine teams will use this description to develop the project’s statement of work.
The project description should include sections such as:
- Introduction/Executive Overview
- Risk Factors or Concerns
- Key Contacts
- Process Details (e.g., Industry Overview, Line/Process Mapping)
- Information About the Data (e.g., Connectivity and Data Sources)
- Sample Data Exploration (e.g., File Exploration, Data Model Alignment)
You can refer to the Sample Project Description section below for more information.
To develop an accurate and useful project description, you will collect a variety of materials from the customer, some of which you should already have after evaluating the project landscape. You can use the checklist below to mark your progress.
Materials Describing the Physical Process
- Gather or create factory, plant, and division flowcharts and diagrams. See Examining the Physical Process in Evaluating the Project Landscape.
- Take pertinent photographs/videos.
- Collect verbal descriptions from stakeholders.
Materials Describing the Data from the Process
- Identify all in-scope data sources. For example:
- Identify the data payloads (i.e., connectivity information) of the data sources. For example:
- Build a network data flow diagram to illustrate the customer data infrastructure, showing which machines can access the cloud, etc. For example:
- Build a matrix of current data assets in relation to the AI Data Pipeline manufacturing model. For example:
Materials Describing the Goals in the Data Project
- Indicate the users of the data, as well as their roles and responsibilities. See Analyzing the Organizational Functions in Evaluating the Project Landscape.
- Describe the types of data problems that the customer wants to solve. These customer value propositions are user stories based on issues or questions the customer has about the machines’ real-time telemetry.
- Find examples of data problem statements. These are the success criteria by which the customer will judge the success of the project (i.e., the customer return on investment, or ROI). For example:
- Collect data from process historian (30 second fidelity), quality, and APA separator file.
- Baseline should account for seasonal variability (via historical data) and include the major mT of production per day (calculated from separator flow in m3/h).
- Develop a map that relates implantation team tasks to customer values. See Building a Customer Value Map in Evaluating the Project Landscape.
Sample Project Description
The following sample shows all of the sections that a project description should contain.