Student - Innovation & Data

At Agidens, we enhance process efficiency, quality, and safety in sectors like life sciences, food and beverage, chemicals, and infrastructure. Embracing the digital era, we have established a dedicated Data Science and Artificial Intelligence team to innovate and provide data-driven solutions. This strategic shift towards DS/AI highlights our commitment to using advanced technologies to tackle complex challenges and improve operations, helping our clients predict outcomes, make smarter decisions, and achieve superior operational efficiency.

**What will you do?**:
Topic 1 - P&ID Analysis Tool

Piping and Instrumentation Diagrams (P&IDs) are crucial engineering documents that map out the piping, instruments, and control systems of industrial processes. At Agidens, we frequently work with P&IDs for various projects. However, these diagrams are often shared as simple PDFs or scanned images, making version comparisons a highly manual, time-consuming, and error-prone task.

Proposed solution:
This project will focus on developing an AI-powered tool to automate P&ID comparisons using computer vision, Optical Character Recognition (OCR), and other best practices for extracting structured data from scanned diagrams. The tool will help engineers identify differences between versions, extract key components (such as valves, sensors, and pipelines), and highlight changes in layout or annotations, thereby accelerating engineering workflows and improving accuracy.

Topic 2 - Automated Data Audits for Industrial Processes

Agidens frequently performs data audits for clients using process data from their Historian systems. However, these audits are often manual and time-consuming, and valuable insights can be missed without a standardized review process. Additionally, correlating machine-level data with higher-level systems like Manufacturing Execution Systems (MES) or Enterprise Resource Planning (ERP) systems is often underutilized, even though it can reveal root causes for performance issues.

Proposed solution:
This project will focus on building an automated data audit tool that performs standardized health checks on Historian data dumps, quickly identifying patterns, anomalies, and performance issues (e.g., detecting underperforming machines). Additionally, the tool will correlate machine-level data (ISO-95 level 2) with insights from MES (level 3) and ERP (level 4) systems to uncover underlying causes, such as maintenance issues or supply chain delays. The project will leverage statistical techniques, time-series analysis, and possibly machine learning to generate actionable reports for engineers and operations teams.

**Who are you?**:

- Currently enrolled in the 3rd year of a bachelor’s program or in a master's degree in computer science, physics, mathematics, or a related field
- Strong proficiency in Python
- Excellent verbal and written communication skills in English
- Experience with deep learning libraries such a PyTorch is a plus, as well as familiarity with cloud deployment and a basic understanding of industrial processes

**What do we offer?**:
Let's get together