Artificial Intelligence for Right First Time

Right-First-Time Analysis

This project analyses how Right-First-Time (RTF) is tracking within the company and provides management with better insights into how in-process variables are impacting efficiency. It also identifies what variables are having an impact on key Food Safety and Quality metrics such as unexplained spikes in Thermophilic Counts, a customer QA issue.

Right-First-Time (RFT) in a Food Company is defined as the product produced perfectly, every time, with no resources, such as time and/or money being wasted correcting errors, quality, or food safety deviations.

Because of the complexities of food, how each food company processes its products, the varying nature and perishability of different food products, Right-First-Time is often hard to define and then measure objectively.

The Right-First-Time Analysis project

Food Safety Intelligence is tasked with:

  • Identifying and tracking process variables related to Right-First-Time
  • Deploying a series of learning algorithms aimed at identifying useful patterns and insights that management could use to act on.
  • Understanding the specific process controls within the food manufacturing process (independent variables) and relate these to the challenges the company faces, such as reduced Right-First-Time (RFT) percentages and unexplained spikes in Thermophilic Counts and pathogen detection post-pasteurisation, such as Bacillus cereus (dependent variables) 

The Right-First-Time Analysis approach

Our project uses both qualitative and quantitative data measurement within the food manufacturing process.

Summary of learning

The project will provide management with better insight into:

  • Unexplained Right-First-Time (RFT) percentages variance, that can be better controlled
  • In-process variables that potentially impact unexplained spikes in Thermophilic Counts, that operators can be more cognizant of.