MVP of a Smart Data Mapping Module for Quality and Defect Data Analysis in Discrete Manufacturing

Purpose and goal

The project aims to develop an MVP of a Smart Data Mapping Module within our main Platform to address inefficiencies in how discrete manufacturing industries manage operational data required for quality and defect analysis. The goal is to create a methodology and prototype software module that enables manufacturers to map data sources (e.g., sensors, machines) and capture metadata for improved data usability. This will reduce data preparation time and lay the foundation for AI-driven analysis.

Expected effects and result

The project will deliver: *A methodology for mapping data units and metadata in manufacturing environments. *A prototype software module with a visual mapping interface and metadata management capabilities. Expected effects include: *Reducing data preparation time by up to >70%. *Achieving atleast 60% coverage of assets and checkpoints in pilot implementations. *Enabling faster, more accurate quality and defect analysis, improving operational efficiency and supporting Industry 4.0 initiatives.

Planned approach and implementation

The project involves three work packages: 1. Data Mapping Framework: Develop a methodology to map data units and metadata with workshops and research (Months 1–2). 2. Module Design: Create the design and architecture of the visual mapping interface and metadata system (Months 3–4). 3. Prototype Development and Validation: Build, test, and validate the module in collaboration with industry partners (Months 4–6).