D-cube & Veltia Labs for Life implement the research program “SmartLab 4.0” in the Agrifood Industry

An innovative, automated, and integrated solution for the Agrifood Industry using machine learning and state-of-the-art technologies

It was our great pleasure to have participated in the EU-GR Co-founded Research Program, called “SmartLab 4.0”, with the code: Τ2ΕΔΚ-00478, in the last 30 months, alongside Veltia Labs for Life, our trusted partner.

The whole Program began in October 2020 and was completed in May 2023.

This project’s innovation lies in the application of Machine Learning and Artificial Intelligence technologies to enable continuous, automated communication between measurement machines/ instruments and the central laboratory information management system.

The development of the smart laboratory management system is expected to impact the Agrifood Industry in economic and business aspects.

Presenting the SmartLab 4.0 research program

The Smart Laboratory Information System project’s basic idea was the automation and the seamless blending of machines, people, processes, and data, to formulate cutting-edge trends that drive the disruption of the modern industry.

Industry 4.0 was actually the first industrial revolution in which our country, Greece, was challenged to participate actively. “SmartLab4.0” aimed to create a wide range of innovative and efficient research activities, that allows for rapid deployment in Veltia Lab for Life production lines. At the same time, we were challenged to offer an integrated solution based on high-end technologies like artificial intelligence (ai), machine learning, and data analysis, with direct economic and business impact on the industry.

SmartLab project’s main goal

D-Cube joined forces with Veltia Labs for Life to fulfill 2 common visions for the project:

1) Accommodate the digital transformation of the “Veltia Labs for Life” production line to “Lab of the Future”

2) Develop, demonstrate, and commercially exploit a novel vertical solution in the field of laboratory analysis in the Agrifood industry

How the SmartLab 4.0 research project was implemented

This research project included the development of a smart lab system, using machine learning and artificial intelligence. The basic system incorporated all the processes carried out in typical laboratories (such as Environmental, Dietary, Microbiological, and Residual),to broaden the market share to which the final system will be addressed. The basic system was integrated with smart-edge agents which allowed machine-to-machine communication and made the measurement of samples (chemical analyzers, weight measurements, etc.) rapid and uninterrupted.

Additionally, innovative deep learning methods based on the development of recurrent neural network (RNN) were designed to enable data analysis of interconnected machines and detect any unexpected behavior. A major parameter was the incorporation of an Internet of Things background to distribute real-time information about the laboratories to achieve direct supervision.

In order to upgrade customer service, an Extranet system was developed to provide information regarding the progress of customer samples and their measurements in real-time (traceability of analyzes). Finally, we collected and qualitatively analyzed all data to lead to a business intelligence system that favors decision-making based on a wide range of reports and indicators (statistics, correlation rules, graphs, etc.).

What the SmartLab 4.0 research project included

The 30-month-long project covered diverse state-of-the-art activities, including data acquisition and data analysis in various use cases, keeping into consideration the commercial exploitation of the final solution.

Special attention was paid to the definition of S.M.A.R.T. objectives along with quantitative and qualitative Key Performance Indicators. Furthermore, dissemination of the achievements of the project was the top priority of the consortium which took advantage of multiple and diverse communication channels.

Fulfilled modules developed for the SmartLab 4.0

With our main goals in mind, we followed a specific set of tasks to design and develop an advanced smart laboratory system, using machine learning and artificial intelligence. More specifically:

Smart laboratories development

1. Development of “Smart Laboratory Information System” incorporating all of the processes carried out in typical laboratories such as Environmental, Dietary, Microbiological and Residual laboratories.

Complete digitization of the life cycle of the laboratories, from the receipt of the samples, the measurement and opinion of the results to the printing of the certificates, and the automation of the communication with the customers.

Smart edge agents development for machine-to-machine communication

2. The Development of smart edge agents for machine-to-machine communication

We developed Smart interfaces in order to automatically read and transform machine data, with the goal of speeding up sample servicing and minimizing human error.

Neutral Network for anomaly detection development

3. The development of a Neural Network, through artificial intelligence algorithms, for the detection of incorrect measurements by machines (anomaly detection)

Intelligent recurrent machine learning network to recognize unexpected machine behavior, in real-time.

IIoT background development

4. Development of IIoT background for real-time production monitoring

Unified system for collecting, recording, processing, and monitoring the flow of samples and laboratory processes in real-time.

Extranet development

5. Development of a communication system with Customers (Extranet)

Dynamic customer service platform with automated certificates and opinions download as well as updates generation regarding the progress of their samples, in near real-time.

Business Intelligence development

6. Development of a business intelligence system (Business Intelligence)

Multi-criteria reports to support decision-making and optimization of production processes.

During these 6 development phases, D-cube had four stages of individual tasks, using machine learning and state-of-the-art technologies to formulate cutting-edge trends that will propel the transformation of the modern Agrifood industry.

Budget and funding for the Smart Laboratory Information System program

The overall budget available for the “SmartLab 4.0” research program was 461.375,00 €. D-cube had a budget of 216.500,00 € with €173,200 being allocated from public funds. Veltia had a budget of €244,875, with €159,168.75 being funded from public expenses.

The project was implemented within the framework of the “Research – Create – Innovate” Action, with co-financing from the European Union’s European Regional Development Fund (ERDF) and national resources through the Operational Programme “Competitiveness, Entrepreneurship, and Innovation”, as well as the support of The Special Service for the Management of the Operational Program Competitiveness, Entrepreneurship, and Innovation and the Special Service for the Management and Implementation of Actions in the fields of Research, Technological Development, and Innovation.

Our goal in developing project “SmartLab4.0”

The final aim of this research project is the “SmartLab4.0” to be registered as a Commercial Laboratory Information Management System (LIMS), as well as for it to be established in all the subsidiaries of Veltia Group and, if desired, in laboratories of the Tentamus Group which consist of more than 100 labs worldwide.

Furthermore, we aspire for it to be commercially exploited in small and medium-sized laboratories outside the Tentamus network, all around the world. Tentamus’ laboratory has already received a demo of the software to evaluate it.

Do you wish to find out more? Visit https://www.d-cube.eu/smart-laboratory-information-system/

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