LabV – The Material Intelligence Platform

AI in the Laboratory

Artificial Intelligence in Laboratory Practice - Part IV

Scenario 3: Visualizations on your fingertips with the help of AI

AI in the material testing lab - blog post series

Effective communication with suppliers is essential for maintaining high-quality standards and resolving issues promptly. This scenario demonstrates how AI can facilitate better communication internally and with suppliers by presenting data in a clear and impactful manner.

Handling and analyzing vast amounts of data can be extremely challenging. Traditional methods, such as manual data entry and analysis in Excel, are often time-consuming and prone to human error. This scenario illustrates how AI can streamline these processes, making it easier to identify critical correlations and trends in complex datasets.

The Problem

Communicating complex data issues clearly and effectively to suppliers. When quality issues arise, it is crucial to present the data in a way that is easily understandable and actionable for the supplier. Manual data presentation methods are cumbersome for highlighting specific problems
and their impacts.

The Solution

The AI digital assistant creates data visualizations quickly by using simple commands. The resulting graph produced by the prompt clearly shows that there is a problem with batch 4 from supplier C. Further analyses or visualizations can be easily created should the supplier require it.

graph of supplier viscosities

This scenario shows that the AI needs a certain data basis and quality to produce a usable output. Once the basis is available, AI is a user-friendly resource that makes laboratory quality control processes more efficient.

In the final blog post we will take a closer look at other prompts to calculate the quality metrics of Cp, Cpk, pp, Ppk. Or just download our case study below. 

whitepaper AI in laboratory practice

AI in Laboratory Practice

Everyone is talking about artificial intelligence (AI). In this case study however, we show how AI can be used in the lab on a practical level. 

Learn more in this case study:

  • How AI-based solutions can integrate fragmented laboratory data into a cohesive system
  • What AI can do in your lab to improve efficiency and to exploit all data
  • Practical examples of how AI can streamline data analysis
  • The benefits of an AI-powered data management platform in transforming laboratory operations, reducing errors, and saving time.

Download the case study now and discover what AI can do in your laboratory.

Free Download of the Case Study