## 1 Introduction
As stated in [22], in Greece, the value added to the manufacturing of food, beverages, and tobacco is very high compared to other developed countries. In Greece, the food sector plays an important role in the level of export share and in a positive trade balance; however, there is a lack of digital transformation within companies and little adaption of Industry 4.0 technologies and techniques to the industrial landscape [23]. In this case study, a Digital Shadow architecture will be proposed, adopting edge computing technology to increase the digitization and digitalization level of the PI to move towards Industry 4.0 standards. According to [24; 25; 26; 27; 28; 29; 30], Digital Shadow is a next-generation information system that allows a more efficient operation of value-creation systems and provides holistic data from multiple and diverse sources to support the decision-making process. Digital Shadow is a key component of the visibility intelligence level and contributes to make, in near real-time, management decisions, as stated in real data [31]. The development of Digital Shadow architecture will be used in the implementation of edge computing technology to bring the services and utilities of cloud computing closer to the end user [32]. Edge computing technology is characterized by fast processing and quick application response time [33]. Based on the above-mentioned ideas, the key advantages of integrating Digital Shadow technology into a conventional food industry production line are the multiple benefits that will be analyzed in the following. More specifically, Digital Shadow technology offers various advantages, such as enhanced efficiency by identifying bottlenecks, reducing waste and boosting productivity. It also improves quality control by detecting any defects or contamination and alerting managers immediately, which can prevent costly recalls and improve customer satisfaction. In addition, implementing this technology ensures compliance with safety regulations and protocols related to temperature control, sanitation and allergen management. Real-time data analysis can help managers in informed decision making, especially when dealing with issues such as equipment breakdowns or supply chain disruptions. Ultimately, Digital Shadow technology can lead to long-term cost savings for companies by optimizing production processes, reducing waste and improving quality control, which can result in increased profitability and competitiveness. Furthermore,integrating Design of Experiments (DOE) with Digital Shadow technology in a traditional production line contributes towards the following benefits:  
1. Enhanced Process Optimization: The statistical technique of DOE can be employed to identify critical factors that affect a particular process, enabling companies to optimize production. By using Digital Shadow technology, real-time data can be collected from production processes to pinpoint the most significant factors affecting efficiency, quality, and safety. This combination enables companies to continuously optimize production processes and to lower production costs. 2. Improved Quality Control: With Digital Shadow technology, companies can monitor production processes in real-time, gather data from sensors and devices, and ensure that quality parameters are met. By using DOE techniques, companies can identify critical factors affecting product quality and adjust them to improve quality consistency. The combination of DOE and Digital Shadow technology ensures that products are consistently produced with high quality and meet or exceed customer expectations. 3. Increased Efficiency: Digital Shadow technology allows for the collection of industrial big data sets in real-time, giving production managers insights into how to optimize production processes. By using DOE techniques, companies can identify the most significant factors affecting production efficiency, such as machine speed, temperature, or pressure.