Nikon > Case Studies > Ensuring Safe Jam-making for Delicious Results

Ensuring Safe Jam-making for Delicious Results

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 Ensuring Safe Jam-making for Delicious Results - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Computer Vision Software
Applicable Industries
  • Food & Beverage
Applicable Functions
  • Process Manufacturing
Use Cases
  • Object Detection
  • Software Design & Engineering Services
The Challenge

In jam and fruit spread manufacturing, there is a process to eliminate foreign objects and impurities contained in the materials. Until now, that inspection has been conducted by human eyes, however, there were several issues such as the heavy physical burden on employees and inconsistent detection accuracy. Due to the wide variety of raw materials and differing shapes of fruits, it was considered extremely difficult to automate this inspection process.

The Customer
About The Customer

Jam manufacturing company.

The Solution

Nikon repeated a basic experiment from 2015 and started joint development of an automatic inspection system for foreign objects and impurities. The company measured the spectral reflectance characteristics of raw materials and samples of foreign objects/impurities, and selected the combination of optical filters that could most easily distinguish between the two. Also, Nikon utilized deep learning, a type of AI, to improve the detection accuracy of foreign objects and impurities from taken images.

Operational Impact
  • [Process Optimization - Real Time Monitoring]

    For the first time in the industry, Nikon realized effective automatic inspection of foreign objects and impurities in jam and fruit spread manufacturing. By introducing this foreign material inspection system, AOHATA Corporation achieved both improvement of detection accuracy and reduced burden on the workforce.

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