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MANUFACTURING AUTOMATION SYSTEM FOR CHIPBOARD FURNITURE COMPONENTS

Project background:

The client manufactures chipboard furniture components. Due to increasing demand, there is a need to optimize production process and implement automated solutions.

Biggest challenges: A variety of equipment (produced by different manufacturers), robots and processes must be integrated into a unified, automated system.

Solution:

Apply develops management software that automates production processes.

Every component produced must undergo a complete production cycle. First, a large chipboard is cut to the required size. Then, the edges are glued, fixing holes are drilled, and components are shelved. Finally, the order is assembled and sent out for palletization. Customer chooses the algorithm, and in the final stage, furniture components are stacked on pallets based on that algorithm.

The control system developed ensures the complete automation of this production process. The system is active, it plans ahead, and it can be optimized on a number of parameters. It ensures automated operation of the robot arms, conveyors, various sensors and manipulators.

Integrations have been created with the client’s internal databases and various types of equipment.

Key benefits:

• Improved efficiency of the production process;
• Improved process and resource planning;
• Improved competitiveness.

SMART SELF-SERVICE CHECKOUT

Project background:

The objective was to develop a self-service checkout by using a computer vision solutions in terms to improve customer service, make existing processes more efficient and make daily taskseasier for employees. This technology allows to automate product recognition, reducing the need for manual input and speeding up the checkout process.

Biggest challenges: the variety of the food and its appearance, different placements of the food on the plate (stacked on top of each other, covered with sauce, etc.).

Solution:

Developed a self-service checkout system that recognises food by visual appearance. The system recognises food placed on a tray below the system screen, generates a shopping list, exchanges data with the POS database to obtain a price, generates a shopping list and displays it on the screen. The system is integrated with the payment process and customer loyalty card acceptance call.

The system also includes a user-friendly UI for the checkout screen, a backend, and a cashier/administrator view for solving different situations.

Computer vision and machine learning solutions are built into the system and tailored specifically for this task. Visual data processing is real-time.

Key benefits:

• Modernised customer service;
• Optimised workforce and efficiency.

CHICKEN EGG PRODUCTION ACCOUNTING AND QUALITY CONTROL SOLUTION

Project background:

The objective was to develop AI solutions to replace existing mechanical solutions. Firstly, to perform online egg counting from each hen house and determine egg quality (by shape, color, shell structure, and deviations from quality criteria). Secondly, during production egg-cracking equipment could not determine when the machinery needed improvement, specifically when the cracking knives needed to be sharpened or replaced which affected the quality of the final product.

Biggest challenges: products have similar visual characteristics, which makes classification difficult.

Solution:

Production monitoring system has been developed and implemented to automate the collection of data on the amount and quality of eggs produced per hen house per day. This enables the assessment of production volumes and hen health status. The system also monitors quality of theproduced eggs by analysing the quality of the egg whites and yolks, which is used to determine whether the technical equipment needs improvement.

The system works in real-time. Computer vision and machine learning solutions have been developed and adapted to perform two different tasks – egg quality and counting control and quality control of cracked eggs. The data is collected from a real environment – production site, and is integrated with the company’s accounting system. The system works in a containerised environment.

Key benefits:

• Improved production process, reduced production line downtime;
• Optimised costs for data acquisition and processing;
• Accelerated extraction and processing of quality data;
• Real-time tracking and remote monitoring.