Food and Chemicals

Overview

In the food and beverage sector, Overall Equipment Efficiency (OEE), yield, throughput, and waste rate are key indicators used to evaluate operational efficiency. To practically improve these indicators and innovate processes,
physicochemical analysis based on data generated at the production site is essential.

The core element that enables this is the convergence of IT technologies like cloud computing and equipment-based OT technologies. This combination can integrate and standardize data, enhancing the visibility of production processes while simultaneously improving quality and efficiency.

SDT has been at the forefront of developing cloud-based data standardization technologies and non-destructive quality inspection solutions for agricultural and aquatic products to improve quality in the food and beverage industry.
In particular, SDT's technology focuses on detecting and removing defective products in real-time on the production line through a 100% inspection method rather than sampling.
This greatly contributes to increasing production efficiency, reducing waste rates, and enhancing consumer trust.

In the food and beverage sector, Overall Equipment Effectiveness (OEE), yield, throughput, and waste rate are key indicators used to assess operational efficiency. To effectively improve these indicators and innovate processes, a
physicochemical analysis based on data generated on the production floor is essential.

The key element that makes this possible is the convergence of IT technologies such as cloud computing and equipment-based OT technology. This integration can enhance the visibility of production processes by unifying and standardizing data, while simultaneously improving quality and efficiency.

SDT has been at the forefront of developing cloud-based data standardization technology and non-destructive quality inspection solutions for agricultural and aquatic products to enhance quality in the food and beverage industry.
In particular, SDT's technology focuses on detecting and removing defective products in real-time on production lines through 100% inspection rather than sampling methods. This significantly contributes to increasing production efficiency and reducing waste rates while bolstering consumer trust.

In the food and beverage sector, Overall Equipment Effectiveness (OEE), yield, throughput, and waste rate are key indicators used to assess operational efficiency. To practically improve these indicators and innovate processes, physical and chemical analysis based on data generated on the production floor is essential.

The core element enabling this is the integration of IT technologies, such as cloud computing, with facility-based Operational Technology (OT). This combination helps to integrate and standardize data to enhance visibility in the production process, simultaneously improving quality and efficiency.

SDT has been at the forefront of developing cloud-based data standardization technology and non-destructive quality inspection solutions for agricultural and marine products to enhance quality in the food and beverage industry. Notably, SDT's technology focuses on detecting and removing defective products in real-time from the production line through 100% inspection rather than sampling. This greatly contributes to increasing production efficiency and reducing waste rates while strengthening consumer trust.

The problems faced in the food sector

The food and beverage factory must comply with strict quality regulations and certifications, and it is important to meet safety and environmental standards for the products. However, there are challenges in maintaining quality consistency due to variations in raw material quality and slight changes in the process.

Small variations can affect product quality, making real-time quality control necessary. However, various environmental factors such as temperature, humidity, and pressure influence the process, creating difficulties in continuously monitoring and controlling quality fluctuations. Moreover, it is crucial to quickly detect and eliminate defective products, but the use of a wide range of equipment and systems in the process imposes many restrictions on swiftly identifying and removing defective items.

As a result, many quality control tasks are still carried out manually today, and due to the technical difficulties of 100% inspection, there is a reliance on sampling methods. This decreases the accuracy and consistency of quality control, increasing the risk of missing defective products and negatively impacting productivity.

Solution of SDT -
Data Standardization on the
Process Using Cloud Computing

SDT's Solution -
Data Standardization on the Cloud Computing Framework
Above the Process

Solution of SDT -
Data Standardization on
Process Using Cloud Computing

The large food manufacturing client conducted quality control of food using a sampling method, with each operator having different criteria for identifying defective products and manually removing them. This led to difficulties in the accuracy and consistency of quality control, which also affected productivity.

To resolve this, SDT provided the client with a machine vision solution utilizing public cloud technology. First, by conducting an on-site investigation, we selected the appropriate hardware (cameras, lighting, Frame Grabber, triggers, etc.) and software tailored to the client's site, and installed a line scan camera on the conveyor belt, automating the full inspection process and moving away from the previous sampling method.

With this solution, the client was able to establish a dashboard that monitors the number of defective products and the defect rate in real time and to implement data standardization through the cloud, enabling real-time monitoring and relational analysis with other processes. As a result, the efficiency of quality control has significantly improved, and defective products can now be accurately detected and removed in real time.

The large food manufacturing client was conducting quality control of food products through a sampling method, where each operator had different standards for identifying defective products and manually removing them. This resulted in difficulties in the accuracy and consistency of quality control, which also affected productivity.

To resolve this issue, SDT provided the client with a machine vision solution using public cloud technology. First, through an on-site inspection, hardware (camera, lighting, Frame Grabber, trigger, etc.) and software suitable for the client's site were selected and a line scan camera was installed on the conveyor belt, automating the full inspection process and moving away from the existing sampling method.

With this solution, the client was able to establish a dashboard to monitor in real-time the number of defective products and the defect rate, implementing data standardization through the cloud, which enabled real-time monitoring and correlation analysis with other processes. As a result, the efficiency of quality control significantly improved, allowing for accurate detection and removal of defective products in real-time.

SDT's solution - Quality inspection of agricultural products using SWIR cameras

Solution of SDT -
Quality Inspection of Agricultural Products Using
SWIR Cameras

The food and beverage industry has long utilized machine vision inspection. Notably, there are packaging inspections using line scan cameras, quantitative inspections using area scan cameras, and sorting by color using prism cameras. Machine vision technology is applied in various quality management tasks, such as beverage bottle inspections, ingredient classification, seal inspections, and foreign matter inspections.

SDT's quantum dot SWIR camera offers innovative technology that leverages the unique quantum mechanical properties of quantum dots in the 400 - 1,700nm range, allowing for inspections not only of external appearance but also of internal defects in foods in a non-destructive manner. For example, it is possible to check if an apple has bruises or is undergoing decay, enabling more precise management of food quality. This technology is effectively used in food quality control, grading of agricultural and marine products, and damage inspection, allowing for the identification of fine cracks or early signs of decay beneath the skin of produce through infrared imaging. It also plays an important role in evaluating damage from pests, moisture content, internal defects, and fruit quality to determine the optimal harvest time and ensure quality.

SDT's quantum dot SWIR camera provides higher efficiency and accuracy in quality management within the food and beverage industry at a reasonable price, establishing itself as a crucial technology for optimizing the quality of the production process.

The food and beverage industry has long utilized machine vision inspection. Notably, there are packaging inspections using line scan cameras, quantitative inspections using area scan cameras, and color classification using prism cameras. Machine vision technology is applied to various quality control tasks such as beverage bottle inspection, raw material classification, sealing inspection, and foreign object inspection.

SDT's quantum dot SWIR camera provides innovative technology that uses the unique quantum mechanical properties of quantum dots in the 400 - 1,700nm range, allowing for inspection of not only the appearance but also internal defects of food in a non-destructive manner. For example, it becomes possible to check whether an apple is bruised or undergoing decay, enabling more precise management of food quality. This technology is effectively used in food quality control, agricultural and fishery product grading, and damage inspection, and can identify fine cracks or early signs of decay beneath the skin of agricultural products through infrared imaging. Additionally, it plays a crucial role in determining the optimal harvest time and ensuring quality by assessing plant disease damage, moisture content, internal defects, and the quality of flesh.

SDT's quantum dot SWIR camera provides a higher level of efficiency and accuracy in quality management within the food and beverage industry at a reasonable price, establishing itself as an important technology for optimizing quality in the production process.

The food and beverage industry has long utilized machine vision inspection. Notable examples include packaging inspections using line scan cameras, quantitative inspections using area scan cameras, and color classification using prism cameras. Machine vision technology is applied to various quality control tasks such as beverage bottle inspection, ingredient classification, sealing inspections, and foreign matter inspections.

SDT's quantum dot SWIR camera offers innovative technology that utilizes the unique quantum mechanical properties of quantum dots in the 400 - 1,700 nm range, allowing for inspections not only of external appearances but also of internal defects in food through non-destructive means. For example, it is possible to check if an apple has bruises or is undergoing decay, which enables more precise management of food quality. This technology is effectively used in food quality control, agricultural and fishery product grading, and damage inspections, and can identify fine cracks or early signs of decay beneath the skins of agricultural products through infrared imaging. Additionally, it plays a crucial role in assessing pest damage, moisture content, internal defects, and fruit quality to determine optimal harvest times and ensure quality.

SDT's quantum dot SWIR camera provides higher efficiency and accuracy in quality management for the food and beverage industry at a reasonable price, establishing itself as a significant technology for optimizing quality in the production process.

General camera