Nikon Case Studies Ensuring Safe Jam-making for Delicious Results

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	Ensuring Safe Jam-making for Delicious Results Nikon

Ensuring Safe Jam-making for Delicious Results

Nikon

Technology Category	Analytics & Modeling - Computer Vision Software
Applicable Industries	Food & Beverage
Applicable Functions	Process Manufacturing
Use Cases	Object Detection
Services	Software Design & Engineering Services
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. Read More
About Customer	Jam manufacturing company. Read More
Customer Name	AOHATA Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Computer Vision Software

Applicable Industries

Food & Beverage

Applicable Functions

Process Manufacturing

Use Cases

Object Detection

Services

Software Design & Engineering Services

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.

About Customer

Jam manufacturing company.

Customer Name

AOHATA

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.

Impact #1	[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.

Impact #1

[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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Overview

Ensuring Safe Jam-making for Delicious Results

Operational Impact