The Ultimate Guide to Digital Twin for Manufacturers

What is Digital Twin, and what can it do for my factory, employees, and production efficiency? How does it differ from other manufacturing software solutions? And where do these solutions fit in the bigger picture of Industry 4.0?

If you’re looking for advice to transform your traditional factory into a thriving business utilizing the latest key technologies of Industry 4.0, this page is for you. Here, we’ll cover the different types and examples of Industry 4.0 and leveraging Digital Twin effectively to take your business to the next level. Feel free to browse all the way to the end or click on a specific topic that interests you the most. Without further ado, let’s jump right in!

To understand Industry 4.0, we must first acknowledge its historical context. The advent of Industry 4.0 is commonly traced back to the early 2010s, although it is important to note that its development has been gradual and influenced by preceding technological advancements. The concept of Industry 4.0 was first introduced in 2011 in Germany as part of the government’s High-Tech Strategy for 2020. The initiative aimed to modernize the country’s manufacturing sector and maintain its competitiveness in the global market.

The term “Industry 4.0” itself was coined during this period and gained significant attention. It builds upon previous industrial revolutions, namely the mechanization of production (Industry 1.0), the advent of mass production through assembly lines (Industry 2.0), and the integration of computers and automation (Industry 3.0).

While the term originated in Germany, the concept of Industry 4.0 quickly gained traction worldwide as other countries recognized its potential for economic growth and technological innovation. Governments, industry leaders, and academic institutions across the globe began embracing the principles and exploring ways to leverage these technologies for industrial advancement.

Digital Twin refers to a virtual replica or digital representation of a physical object, process, or system. It is a dynamic and interconnected model that mimics the behavior, characteristics, and interactions of its real-world counterpart in real-time. 

A Digital Twin consists of three key components: the physical object or system itself, its corresponding virtual model, and the connection between the two. The virtual model is created using various data sources, such as sensors, IoT devices, historical data, and simulations. This virtual model reflects the physical object’s attributes, performance, and behavior, enabling real-time monitoring, analysis, and optimization. 

The main purpose of a Digital Twin is to bridge the gap between the physical and digital worlds, enabling a deeper understanding, monitoring, and control of the physical object or system. It serves as a valuable tool for visualization, analysis, simulation, and prediction. 

However, some companies define 3 main types of Digital Twin that are more related to Manufacturing and Process industry:  

Digital Twin and Industry 4.0 are interconnected in a symbiotic relationship, where Digital Twin serves as a key enabler and component of the broader Industry 4.0 paradigm.

Firstly, Digital Twin serves as a foundational technology for Industry 4.0. It enables the virtual representation and real-time monitoring of physical assets, systems, and processes, which aligns with the goals of Industry 4.0 to create interconnected, intelligent, and data-driven systems within the industrial sector.

Secondly, Digital Twins rely on real-time data from sensors, IoT devices, and other sources to maintain accurate representations of physical entities. This real-time data collection and connectivity align with the core principles of Industry 4.0, which emphasize the integration of information technology, IoT, and connectivity to enable seamless communication and data exchange within the industrial ecosystem.

Thirdly, Both Digital Twin and Industry 4.0 promote data-driven decision-making. Digital Twins generate vast amounts of data from physical assets and processes, which can be analyzed using advanced analytics, AI, and machine learning techniques. This data analysis facilitates real-time insights, predictive capabilities, and informed decision-making, aligning with the goals of Industry 4.0 to optimize processes, improve efficiency, and enhance productivity.

Digital Twins enable virtual simulation, modeling, and optimization of physical assets and processes. This aligns with the objectives of Industry 4.0, which aims to optimize production processes, reduce downtime, improve resource utilization, and enhance overall operational efficiency.

Digital Twin integrates with other key technologies associated with Industry 4.0, such as IoT, big data analytics, artificial intelligence, and cloud computing. This integration allows for the seamless exchange and analysis of data, leveraging advanced analytics and AI to drive optimization, automation, and innovation within the industrial ecosystem.

Together, Digital Twin and Industry 4.0 facilitate the transformation of traditional manufacturing processes into smart, connected, and digitized systems. They enable the creation of smart factories, digital supply chains, and agile production processes, resulting in improved productivity, flexibility, and competitiveness.

In manufacturing, a Digital Twin can represent a machine, production line, or an entire factory. By simulating and analyzing the virtual model, manufacturers can optimize production processes, perform predictive maintenance, and identify areas for improvement, ultimately leading to increased efficiency, reduced downtime, and cost savings. Furthermore, Digital Twins find applications in smart cities, transportation systems, energy grids, and more.

To get better understanding of provided by Digital Twin benefits, read our real-life Use Cases.

Now that we have analyzed the concept of Digital Twin, its types, and how it relates to Industry 4.0, we propose to continue the topic of Industry 4.0 and explore different product solutions that are presented on the modern markets.

“What is ERP, MES, MRP and how do they relate to the Digital Twin?” “Do I need a Digital Twin if there is MES?” “Is it enough to implement only ERP without Digital Twin?”

Such questions often arise among employees and owners of manufacturing enterprises who are on the path of transforming their enterprise into a Smart Factory. Let’s look for answers to these questions together.

ERP is an acronym for “Enterprise Resource Planning,” which refers to a comprehensive software system that integrates various business functions and processes within an organization.

At its core, ERP is designed to facilitate the flow of information and resources across different departments or divisions of a company. It acts as a central hub where data from various business operations, such as finance, human resources, manufacturing, supply chain management, and customer relationship management, are consolidated and managed in a unified manner.

The primary objective of implementing an ERP system is to streamline and optimize business processes, improve operational efficiency, and enhance decision-making capabilities. By consolidating data from different areas, ERP enables real-time visibility into key performance indicators, allowing managers and executives to make informed decisions based on accurate and up-to-date information.

An ERP system typically comprises a central database and a suite of interconnected modules or applications that cater to specific functional areas. These modules may include finance and accounting, human resources, inventory management, procurement, sales and marketing, production planning, and more. The modules are designed to meet the unique requirements of each department while seamlessly sharing data and facilitating communication across the organization.

ERP systems offer numerous benefits to organizations, including enhanced productivity, reduced operational costs, improved customer service, streamlined supply chain management, and increased data accuracy. By automating routine tasks and providing a holistic view of the business, ERP helps organizations streamline their operations, eliminate redundancies, and achieve greater efficiency.

On the other hand, a Digital Twin represents a digital replica or virtual representation of a physical object, system, or process. It is a concept that has gained significant traction in recent years, particularly in the context of Industry 4.0 and the Internet of Things (IoT). A Digital Twin is created by collecting real-time data from sensors, devices, or systems and using advanced technologies such as artificial intelligence (AI) and machine learning (ML) to simulate and model the behavior, characteristics, and performance of the physical counterpart.

While ERP focuses on integrating and managing organizational data and processes, a Digital Twin goes beyond that by providing a dynamic and interactive virtual model of a physical entity. It allows organizations to monitor, analyze, and optimize the performance of their assets, products, or systems in real-time. By leveraging data from the physical entity and running simulations or predictive analysis, a Digital Twin enables organizations to gain insights, make data-driven decisions, and identify potential issues or opportunities before they occur in the physical world.

In essence, ERP is primarily concerned with managing business processes and data within an organization, while a Digital Twin is a technological concept that represents a virtual replica of a physical entity, providing real-time monitoring, analysis, and optimization capabilities.

It is worth mentioning that there can be some intersections between ERP and Digital Twin technologies. Some ERP systems may incorporate Digital Twin concepts by integrating real-time data from IoT devices or sensors to provide enhanced visibility and decision-making capabilities. Similarly, Digital Twin models can utilize data from ERP systems to simulate and analyze the impact of various business processes or changes on the physical entity.

MES, which stands for Manufacturing Execution Systems, is a critical component of modern manufacturing operations. An MES is a software-based system that provides real-time visibility and control over manufacturing processes on the shop floor. It acts as a bridge between the enterprise resource planning (ERP) system, which manages high-level planning and resource allocation, and the actual execution of manufacturing activities.  

The primary objective of an MES is to monitor, track, and optimize the production activities in real-time. It captures data from various sources, such as machines, sensors, operators, and other systems, and provides comprehensive information about the status, performance, and quality of manufacturing operations. 

MES systems typically offer a wide range of functionalities, including: 

By integrating MES with other systems such as ERP, inventory management, and quality control, it enhances operational efficiency, reduces errors, improves product quality, and enables faster decision-making on the shop floor. 

Let us delve into differences between MES and Digital Twin: 

In summary, MES and Digital Twin represent distinct concepts in the realm of manufacturing. While MES focuses on real-time monitoring and control of manufacturing operations on the shop floor, Digital Twin goes beyond by creating a virtual replica of a physical asset or system for simulation, analysis, and optimization throughout its lifecycle. Both concepts offer unique advantages and applications in improving manufacturing efficiency, quality, and decision-making.

Material Requirements Planning, often referred to as MRP, is a methodical approach used in manufacturing and production planning to effectively manage and control the inventory of raw materials, components, and subassemblies required for production.

The primary objective of MRP is to ensure that the necessary materials are available at the right time, in the right quantities, and in the right location to meet the production schedule. It involves analyzing the demand for finished goods, taking into account the bill of materials (BOM), lead times, and inventory levels, and generating a plan that outlines the requirements for each material component.

The MRP process typically consists of the following steps:

By utilizing MRP, organizations can effectively manage their inventory levels, minimize stockouts and overstocking, and improve overall production planning. It enables better coordination between different departments, such as production, procurement, and inventory management, by providing a structured approach to material planning.

Now let us explore the differences between MRP and Digital Twin:

MRP is centered around material planning and procurement, ensuring availability for production schedules, while Digital Twin offers real-time monitoring, analysis, and optimization capabilities for assets or systems throughout their lifecycle. 

Described products can also interact and complement each other in some cases. For example, MRP calculations can be integrated into an ERP system, MES can be connected to both ERP and MRP systems for real-time data exchange, and Digital Twin models can utilize data from ERP, MRP, and MES for simulations and analysis. 

OEE (Overall Equipment Effectiveness) software is a tool used to measure and improve the efficiency and performance of manufacturing equipment. OEE is a key performance indicator that provides insights into how effectively a machine or production line is utilized and how efficiently it operates.

OEE software typically includes features and functionalities that help collect, analyze, and interpret data related to equipment performance. These tools help monitor and track various metrics that contribute to the overall equipment effectiveness, such as availability, performance, and quality.

Here are some common features found in OEE software:

When OEE software is integrated with Digital Twin technology, it creates an opportunity to enhance equipment performance through simulation and optimization. By linking the OEE software with the Digital Twin, manufacturers gain the ability to monitor and analyze equipment performance in real-time, simulate various scenarios, and proactively detect potential issues or inefficiencies before they manifest in the physical realm. This integration empowers manufacturers to make data-driven decisions, optimize equipment operations, and ensure a more efficient and effective manufacturing environment. 

OPC UA, which stands for Object Linking and Embedding for Process Control Unified Architecture, is a widely adopted communication protocol in the field of industrial automation and control systems. 

OPC UA software serves as a framework for exchanging information and data securely and reliably between different devices, systems, and software applications in industrial environments. It provides a standardized and interoperable means of communication, ensuring seamless connectivity and data exchange across diverse platforms and vendors. 

This software utilizes a client-server model, where the client applications can request and retrieve data from servers that host the desired information. OPC UA offers a rich set of features and functionalities that facilitate not only the transfer of real-time process data but also the exchange of complex data structures, historical data, alarms, and events. 

OPC UA software promotes interoperability and scalability. It enables seamless integration between different systems and devices, regardless of the underlying hardware or software platforms. This flexibility allows industrial organizations to leverage their existing infrastructure while incorporating new technologies and expanding their operational capabilities. 

In addition to this the software supports platform-independent data modeling, enabling the representation of complex data structures and hierarchies. Besides this one it’s key is an ability to provide a secure and robust communication framework. It employs various security mechanisms, including encryption, authentication, and authorization, to protect data integrity and confidentiality. This ensures that sensitive information remains safeguarded within industrial systems.

The relationship between OPC UA software and Digital Twin technology comes into play when the Digital Twin needs to communicate and exchange data with other systems and devices in the industrial environment. OPC UA provides a standardized and secure means of connecting the Digital Twin with the physical assets, control systems, and other software applications.

By utilizing OPC UA, the Digital Twin can seamlessly exchange data with the physical equipment, monitoring systems, and other software components in real-time. The Digital Twin can retrieve process data, historical data, and other relevant information using OPC UA communication. This allows the Digital Twin to accurately represent and simulate the behavior of the physical assets or processes it is mirroring.

Furthermore, OPC UA software can enable bidirectional communication, allowing the Digital Twin to not only receive data but also send control commands or parameter adjustments to the physical assets through the established communication channels. This capability empowers the Digital Twin to act as a virtual controller or optimizer, influencing the behavior and performance of the physical system.

Augmented Reality (AR) and Virtual Reality (VR) are immersive technologies that enhance or replace the user’s perception of reality.  

According to ReportLinker the global augmented reality in marketing market is expected to grow from $4.01 billion in 2022 to $4.54 billion in 2023 at a compound annual growth rate (CAGR) of 13.4%.   

Fortune Business Insights mentioned that the global virtual reality market size was valued at $19.44 billion in 2022 & is projected to grow from $25.11 billion in 2023 to $165.91 billion by 2030, exhibiting a CAGR of 31% during the forecast period.  

Although AR and VR have distinct characteristics and use cases, they can also intersect with the concept of 3D Digital Twin. Let’s explore each of them and their relationship to 3D Digital Twin. 

Augmented Reality overlays digital information, such as virtual objects, graphics, or data, onto the real-world environment. AR enhances the real world by adding computer-generated elements in real-time, allowing users to interact with both virtual and physical elements simultaneously. AR is typically experienced through devices like smartphones, tablets, smart glasses, or headsets with cameras and sensors.

In the context of a 3D Digital Twin, AR can be used to visualize and interact with the digital twin in the physical world. Users can use AR-enabled devices to see the virtual representation of the digital twin superimposed onto the real-world object or environment. This combination of real and virtual elements allows users to gain insights, perform maintenance tasks, or visualize information in a spatial context.

Virtual Reality is a technology that creates a fully immersive, computer-generated environment that simulates a realistic or fictional world. VR aims to transport users into a completely virtual experience by stimulating their vision, hearing, and sometimes touch or movement. VR is typically experienced through headsets that block out the physical world and replace it with a virtual environment.

In the context of a 3D Digital Twin, VR can provide an immersive and interactive experience within the virtual representation of the digital twin. Users can explore and interact with the digital twin in a virtual space, allowing for detailed inspection, simulation of scenarios, or training purposes. VR can offer a deeper sense of presence and immersion, enabling users to engage with the digital twin as if they were physically present in the virtual environment.

Both AR and VR technologies enhance the value and capabilities of Digital Twins, enabling organizations to make more informed decisions, optimize operations, and improve overall efficiency. Among all the benefits, 5 main groups can be distinguished:

3D modeling is the process of creating a digital representation or model of an object or environment in three dimensions. It involves using specialized software tools to construct a virtual 3D model that accurately depicts the shape, structure, and appearance of the subject.

The purpose of 3D modeling is to create a digital representation that mimics the real-world object or environment. This can include various elements such as geometry, textures, materials, colors, and sometimes animation. 3D models are typically created using computer-aided design (CAD) software or 3D modeling software.

The process of 3D modeling typically begins with the creation of a wireframe or skeletal structure that defines the basic shape and structure of the object. This is followed by adding details, refining surfaces, and applying textures and materials to enhance the realism of the model. Depending on the complexity and intended use of the model, additional attributes such as lighting, animation, or simulation properties may be incorporated.

3D modeling finds applications in a wide range of industries and fields. In architecture and product design, 3D models are used to visualize and refine concepts, create prototypes, and communicate ideas to clients or manufacturers. In the entertainment industry, 3D modeling is crucial for creating characters, props, and environments for films, video games, and virtual reality experiences. It is also used in scientific visualization, medical imaging, industrial design, engineering, and many other domains.

3D simulation refers to the process of creating and running computerized models or simulations that replicate real-world or imagined scenarios in a three-dimensional virtual environment. It involves the use of computer algorithms, mathematical models, and simulation techniques to mimic the behavior, interactions, and dynamics of objects, systems, or phenomena.

The goal of 3D simulation is to study, analyze, and predict the outcomes of complex systems or scenarios without the need for physical experimentation. By simulating the virtual environment, users can observe and interact with the simulated world, allowing for experimentation, exploration, and evaluation of various parameters, variables, or scenarios.

In 3D simulation, the virtual environment is typically represented by a three-dimensional model that incorporates relevant attributes, such as the geometry, physics, and behavior of the objects or entities being simulated. The model may include aspects such as motion, forces, collisions, lighting, and other physical properties to create a realistic and dynamic simulation.

3D simulation finds application in a wide range of industries and fields. For example, in engineering, 3D simulation is used to simulate the behavior of structures, fluids, or mechanical systems, aiding in design optimization, performance analysis, and testing. In the field of computer graphics, 3D simulation is utilized to create realistic visual effects, animations, and virtual worlds for films, video games, and virtual reality experiences.

In addition, 3D simulation is employed in areas such as physics, chemistry, social sciences, healthcare, and urban planning to model and understand complex phenomena and systems. It allows scientists, researchers, and decision-makers to simulate and explore scenarios that may be too costly, dangerous, or time-consuming to investigate in the physical world.

By running simulations, users can analyze the behavior, interactions, and outcomes of the simulated environment under various conditions, enabling them to make informed decisions, optimize processes, and gain insights that can lead to improvements or innovations in their respective fields.

A 3D Digital Twin is a virtual representation or model of a physical object, system, or environment that incorporates real-time data and simulations. It goes beyond a static 3D model by integrating dynamic and interactive elements that enable a digital replica to mirror the behavior, characteristics, and performance of its real-world counterpart.

A 3D Digital Twin is created by combining three key components: the physical object or system, real-time data capture, and a virtual representation. The physical object can be anything from a building, a machine, a vehicle, or even an entire city. Real-time data is collected from sensors, Internet of Things (IoT) devices, or other sources associated with the physical object or system. This data includes information about various parameters, conditions, and performance metrics.

The real-time data is then used to update and synchronize the digital twin, ensuring that it accurately reflects the current state of the physical object or system. This synchronization allows for continuous monitoring, analysis, and simulation of the digital twin, enabling users to gain insights, predict behavior, and make informed decisions based on real-time information.

With a 3D Digital Twin, users can visualize and interact with the virtual representation of the physical object or system. They can explore different viewpoints, navigate through the digital twin, and access detailed information about its components, attributes, and performance. Through simulations and what-if scenarios, users can assess the impact of changes or interventions, optimize operations, and plan for future improvements.

The applications of 3D Digital Twins are extensive. In industries such as manufacturing, energy, and transportation, digital twins are used to monitor and optimize operations, predict maintenance needs, and simulate various scenarios for efficiency and safety. In smart cities, digital twins can provide insights into urban planning, traffic management, and energy consumption. In healthcare, digital twins can aid in personalized medicine, patient monitoring, and surgical planning.

The integration of real-time data and simulations within a 3D Digital Twin offers a powerful tool for analysis, decision-making, and optimization. It allows users to have a holistic view of the physical object or system, facilitating better understanding, prediction, and control of its behavior and performance.