The rapid development of Industry 4.0 technologies has changed the manufacturing environ-ment and enabled smarter, more efficient and automated systems(What is Industry 4.0? n.d.). The introduction of the Digital Model and OPC-UA (Open Platform Communication Unified Ar-chitecture) can be an important step towards improving the efficiency, resilience, and security of manufacturing systems. A smart factory driven by digital model, real time data exchange with OPC UA and advanced simulation tools can revolutionize manufacturing process world-wide. Through the integration of virtual models and physical systems, manufacturers can im-prove accuracy and optimise workflows, open the way for an intelligent and sustainable opera-tions.

This article explores how the Savonia Smart Factory uses digital model, OPC-UA connectivity and automation to achieve efficiency and optimization. It offers information on the infrastruc-ture of the factory, how OPC-UA helps with real-time communication, and how Visual Compo-nents helps create a dynamic digital model. This combination of technology not only enhances production processes but also provides educational and research benefits and demonstrate how smart factory technologies can influence manufacturing in the future. The following sections explore the infrastructure, connectivity frameworks, and simulation tools that develop this fac-tory as a standard for modern manufacturing systems to highlight the huge possibilities of us-ing digital twins and advanced communication architectures into industrial process.

Overview of Savonia Smart Factory

The Savonia Smart Factory, a Lucas-Nülle Smart Factory is an example of a small-scale, effec-tive, and educationally focused Industry 4.0 installation(Lucas- Nülle, n.d.). This smart facto-ry focusses in producing three-piece boxes, each of which consists of a top part, a bottom part, and a bolt. It includes essential component of a normal Industry. 4.0 smart factory and the necessary hardware to function.

The hardware configuration of the factory consists of 8 modular conveyor belts, each of which is built to act as a station for a particular task. There are six stations set up for assembling parts and final product consists of two colour options for each part: the top and bottom pieces are black and white, while the bolts are red plastic or metal. Each station has a RFID read-er/writer, two magnetic sensors, a motor, and a Siemens Simatic S7-1200 programmable logic controller (PLC). Each Siemens S7-1200 PLC is connected to a Siemens S7-1500 PLC (Master PLC) and Siemens HMI touch control via Profinet Industrial Ethernet Protocol. Additional sta-tions that manage quality control and the removal of completed products which ensure an effi-cient production loop. The quality control station has a camera, a computer for running soft-ware, and two lights—a backlight and a ring light. (Figure 1)

Figure 1. Savonia Smart Factory (Khan, 2024)

Customer orders are placed by using a webshop that is connected to the factory’s Enterprise Resource Planning (ERP) system. A continuous loop of conveyor belts and stations carries the whole manufacturing process (Figure 2). Starting at IMS3A, the transport carrier collects the bottom part of the product from either IMS3A (black part) or IMS3B (white part). The transport carrier proceeds anticlockwise to the IMS4 station to collect the top part from either IMS4A (black part) or IMS4B (white part). The optional bolts IMS5A for red and IMS5B for metal are collected from the following two stations. Once assembly is complete, it goes to the IMS6 quality control station, which is running by the machine vision program. After a quality check, the IMS7 station removes the product from the production loop and allow the transport carrier to return to the start point for the next assembly loop. This factory focused on effec-tiveness, accuracy, and adaptability makes it a good example of how Industry 4.0 concepts can be used in real life applications. (Khan, 2024)

Figure 2. The smart-factory loop diagram (Martikainen, 2022 and Lucas Nülle GmBh)

The role of OPC-UA connectivity

OPC-UA is an important standard for industrial automation and communication that guarantees connectivity between different systems and devices. Through improved connectivity and real-time data exchange, it supports reliable, secure, and organised data transfer between different systems. Because of this features, OPC UA is play an important role in Industry 4.0 frameworks which supports easy integration of many technologies. (Hoppe, n.d.)

OPC UA gives manufacturers the ability to monitor, control, and optimise operations by ensur-ing reliable and secure connectivity. Its ability to narrow barriers in communication between different protocols guarantees a single platform for data exchange despite system variety. It is a scalable and flexible solution for a range of industrial applications since it enables organisa-tions to connect old and modern technologies without causing major problems. (Ladegourdie & Kua, 2022)

One main advantage of OPC is it has included many security features such as confidentiality, integrity, authentication, authorization, encryption and message signing. These features im-prove operational safety in smart factories by reducing cyber threats and protecting sensitive industrial data. As industries become more dependent on technology, secure communication frameworks such as OPC UA are necessary for maintaining productivity and resilience. (Soft-ware Toolbox, n.d.)

The implementation of OPC-UA serves as the basic communication framework that connects the digital model with the physical systems of the Savonia Smart Factory (Figure 3). This technolo-gy enables seamless and secured data exchange and ensures integration between the PLC and simulation platforms such as Visual Components.

Figure 3. Smart Factory OPC-UA Server- Client Architecture (Khan, 2024)

A key component of this setup is the Siemens S7-1500 Master PLC, which serves as the primary communication gateway. This PLC collects data from the manufacturing stations controlled by Siemens S7-1200 PLCs. All operational data across the factory can be accessed by connecting the OPC-UA client software to the Master PLC.

The Siemens TIA Portal enable the configuration of the OPC-UA server in the S7-1500 with the required security instances includes the server URL, Endpoints, security policies, and authentica-tion and authorisation settings. To provide continuous connectivity, firewall rules were also es-tablished to permit communication across specific ports (Figure 4). The OPC-UA server was ac-tivated after the PLC project was compiled and deployed via the TIA Portal (Figure 5).

Figure 4. OPC-UA Server activated in the Master PLC within Siemens TIA Portal (Khan, 2024)

Figure 5. Activated the server with PLC variables from the smart factory by compiling and downloading the PLC project (Khan, 2024)

The Smart Factory develops a reliable and dynamic communication network using this OPC-UA framework. It improves efficiencies in operation, real-time monitoring, and reduces the gap be-tween digital models and physical operations. (Khan, 2024)

Digital model

Visual Components: Digital Model Platform Founded by a team of simulation specialists in 1999, Visual Components is a top manufacturer of 3D industrial simulation software and solutions. The Visual Components platform has a huge library of more than 3,000 preconfigured and usable components including robots, conveyors, industrial machinery and tools. Visual Components makes digital design techniques flexible and scalable by allowing the easy import of custom CAD models into the 3D workspace. Through its OPC-UA interface, the platform supports industrial systems such as Siemens S7 PLCs, ABB, Fa-nuc, Doosan, and KUKA.Sim. (Visual Components, n.d.)

The development of the digital model of the Savonia Smart Factory was made possible by Visu-al Components. This digital 3D model replicates equipment, design, and production procedures of the actual plant (Figure 6). Each of the component stations and modular conveyor belts in the virtual environment include RFID readers/writers, magnetic sensors, and products convey-ors. A virtual simulation of the production process is made possible by robot controllers that control component placement.

Figure 6. Smart Factory 3D Digital Model (Khan, 2024)

Same as the real factory, at IMS3A the simulation starts, and the transport carrier collects bot-tom part of the product either black (IMS3A) or white (IMS3B). The carrier continues in an anticlockwise loop to collect the top part in black (IMS4A) or white (IMS4B). Bolts in red plastic or metal are available at stations IMS5A and IMS5B. At IMS7, a human operator re-moves the assembled product from the production loop and the empty carrier returns to the beginning to start the next cycle (Figure 7).

Figure 7. The 3D Digital model with available components of Smart Factory (Khan, 2024)

This digital model offers engineers and operators several advantages. It allows users to analyse processes, optimise performance, and simulate production scenarios. Besides, the OPC-UA con-nection enables real-time data pairing between the physical factory and the digital model. This digital model is synchronised with sensor and factory component variables which allows real-time operation monitoring and analysis (Figure 8).

Figure 8. OPC-UA Server (Siemens TIA Portal) and OPC-UA Client (Visual Components) con-nected with paired variables during the simulation. (Khan, 2024)

The Savonia Smart Factory can increase production efficiency, decreases breakdowns, and im-proves operational insight by using Visual Components. The platform gives operators the ability to test different configurations, find obstacles, and optimise operations in a risk-free virtual environment. This platform can be important for educational purposes since it allows experts and students to get hands-on experience with advanced industrial technologies. (Khan, 2024)

Benefits of the digital model integration

The integration of Savonia Smart Factory Digital Model has many benefits:

Enhanced Efficiency: With the help of digital model operators can detect problems, optimize workflows, and monitor production processes in real time. This proactive strategy can increase output while reducing interruptions in operations.

Improved Accuracy: The OPC-UA server-client configuration ensures accurate data transfer, reduces errors and improves operational reliability. The ability to synchronize with several sen-sors and devices enhanced the resilience of this architecture.

Cost Savings: Virtual testing and simulation can save time and money by reducing the re-quirement for physical prototype. Digital model monitoring can lower the possibility of costly implementation errors.

Increased Safety: Operators can test scenarios and detect issues using the digital model without getting people or equipment in danger. In high-risk operations, this capability can be helpful in preventing accidents.

Educational Value: The smart factory serves as a learning tool that offers students for Indus-try 4.0 careers by providing them with practical experience with advanced technologies. This platform with Digital Model offers an opportunity to connect academic expertise with real-world application.

Scalability: This digital model makes it easier to scale the operation of the factory because of its modular design and integration. It is possible to plan and test future expansions and up-grades in this digital environment for further deployment.

Benefits of OPS-UA integration

There are several advantages of utilising OPC-UA into smart factories like the Savonia Smart Factory, which changes the management and optimisation of industrial operations:

Interoperability: OPC-UA enables easy communication across systems and devices from dif-ferent vendors which create a unified network that can handle a wide range of industrial appli-cations. This solved the compatibility problems and enhanced system integrity.

Real-Time Data Exchange: Real-time transmission of data improves operational effective-ness and decision-making. Manufacturers can use it to quickly monitor processes, detect difficul-ties, and make necessary improvements.

Scalability and Flexibility: OPC-UA is built to easily adapt with the rising needs of an opera-tion. Because of its flexibility, manufacturers can include new systems, devices, or technologies without redesigning the infrastructure.

Enhanced Security: OPC-UA protects operations from cyber threats and unauthorised access by ensuring the safety of data transfer by integrated security features like encryption, authenti-cation, and data integrity audits.

Supporting Digital Twin: OPC-UA offers the data structure required to build and manage digital twins. Predictive maintenance and advanced simulations become possible by providing accurate real-time data transmission.

Improved Operational Efficiency: This protocol can collect data and improve communica-tion for better resource utilization, reduced errors and optimized workflows. this helps to im-prove efficiency and cost-effectiveness.

Cross-platform Integration: OPC-UA supports system interaction including cloud-based sys-tems which allow remote monitoring, analytics and control. This ensures more operational flex-ibility and accessibility.

Standardized Framework: As a widely used standard, OPC-UA enables reliability in industri-al communication which lowers complexity and makes automation solution development and deployment easier.

Future Proofing Industrial Operation: The flexibility and scalability of OPC-UA ensure that smart factories keep up to date with emerging technologies, which improves the adoption of new ideas and allows them to stay relevant.

Conclusion and future work

The Savonia Smart Factory is an example of how automation can transform the manufacturing industry. With the combination of OPC-UA connectivity with simulation tools like Visual Com-ponents the smart factory achieve efficiency and optimisation. The physical and digital mod-el working together ensures that the manufacturing can adapt with changing industry demands.

Future developments can aim to transform digital model into digital twin and expand the capa-bilities with advanced analytics, machine learning and predictive maintenance. These develop-ments will increase the operational efficiency of the factory and open the door for wider appli-cations in multiple types of industrial domains. Virtual reality (VR) and Augmented Reality (AR) tool integration can also create new opportunities for training and operational insights.

Acknowledgement

Work was carried out with funding from North Savo Regional Council “Automaatio- ja Tekoäly -Tiedoksi (AuToTIE)” -project. A80154 –1.4.2023 – 31.3.2026

Authors:

Md Khan
Project Assistant
md.khan@savonia.fi

Dr. Rajeev Kanth
Principal Lecturer

Rajeev.kanth@savonia.fi

References:

Hoppe, S. (n.d.). OPC Unified Architecture Interoperability for Industrie 4.0 and the Internet of Things. www.opcfoundation.org

Khan, M. (2024). OPC UNIFIED ARCHITECTURE AND DIGITAL REPLICA FOR CRITICAL INFRA-STRUCTURE NETWORKS. https://urn.fi/URN:NBN:fi:amk-2024052716614

Ladegourdie, M., & Kua, J. (2022). Performance Analysis of OPC UA for Industrial Interoperability towards Industry 4.0. IoT, 3(4), 507–525. https://doi.org/10.3390/iot3040027

Lucas- Nülle. (n.d.). https://www.lucas-nuelle.us/. Retrieved December 17, 2024, from https://www.lucas-nuelle.us/

Martikainen, V.-P. (2022). QUALITY CONTROL WITH MACHINE VISION In a smart factory environ-ment AUTHOR Vesa-Petteri Martikainen. https://urn.fi/URN:NBN:fi:amk-2022121530236

Software Toolbox. (n.d.). Exploring OPC UA Security Concepts. Retrieved December 19, 2024, from https://opcconnect.opcfoundation.org/2020/06/exploring-opc-ua-security-concepts/?

Visual Components. (n.d.). Visual Components. Retrieved December 17, 2024, from https://www.visualcomponents.com/

What is Industry 4.0? (n.d.). IBM. Retrieved December 17, 2024, from https://www.ibm.com/topics/industry-4-0?

Lista of figures

Figure 1. Savonia Smart Factory (Khan, 2024)

Figure 2. The smart-factory loop Diagram (Martikainen, 2022)

Figure 3. Smart Factory OPC-UA Server- Client Architecture (Khan, 2024)

Figure 4. OPC-UA Server activated in the Master PLC within Siemens TIA Portal (Khan, 2024)

Figure 5. Activated the server with PLC variables from the smart factory by compiling and downloading the PLC project (Khan, 2024)

Figure 6. Smart Factory 3D Digital Model (Khan, 2024)

Figure 7. The 3D Digital model with available components of Smart Factory (Khan, 2024)

Figure 8. OPC-UA Server (Siemens TIA Portal) and OPC-UA Client (Visual Components) connected with paired variables during the simulation. (Khan, 2024)