Opportunities, Strategies and Technologies
Digitalization in Production
By integrating digital technologies into various areas of production, companies are seeking to make manufacturing processes more efficient, flexible and future-proof. The following article provides an overview of the opportunities, challenges, strategies and technologies associated with the digitalization of production.
Definition
Digitalization – Definition and related terms
Digitalization in production means connecting machines, software and people on the factory floor digitally: data from machines and equipment is captured automatically, analyzed centrally and used to monitor, control and automate production processes – instead of relying on paper or isolated systems. In industry, this development is also referred to as Industry 4.0.
In the narrower, technical sense, digitalization refers to the conversion of analog values (signals) into digital formats that can be processed by computers.
In everyday language, however, the term often refers to the possibilities that arise from developments in the area of digital technologies. These include e.g. the processing of large amounts of data, the creation of digital goods and business models, as well as networking via digital media. In this article, we will also use the term digitalization to describe the use of modern digital technologies in production.
The multitude of opportunities and changes that arise from the use of digital technologies are also described using terms such as "Digital Transformation" or "Digital Revolution". In industry, the trend of advancing digitalization is also referred to as "Industry 4.0".
Potentials
Potentials of digitalization in production
A key element of digitalization lies in the ability to process increasingly large amounts of data.
In production, digitalization not only ensures that more and more relevant data can be provided by sensors, controllers and other systems, but also allows these data volumes to be processed by specialized software applications. With the help of suitable interfaces and protocols, production-related data can be transferred across different levels within a company.
This opens up many new possibilities for monitoring, controlling and automating production processes, which we will discuss in more detail below.
Another important aspect are the opportunities for improved communication and collaboration in production – between individuals, teams and departments, and even between different companies. Optimized communication structures are increasingly becoming a prerequisite for managing complex coordination tasks (global supply chains and locations, more individualized customer orders, etc.).
Digitalization is one of the most important drivers in production optimization. By using advanced technologies in combination with a Continuous Improvement Process (CIP), manufacturing companies are trying to make their processes more efficient, productive, qualitative, flexible and sustainable. On the one hand, the aim is to reduce or replace inefficient processes, whilst also utilizing new technologies in innovative ways, sometimes leading to entirely new business segments.
Benefits
How do manufacturing companies benefit from digitalization efforts?
In production, a wide range of areas and processes can benefit from digitalization initiatives. To make progress measurable, it is important that companies define clear objectives and regularly evaluate their implementation (e.g. using suitable production metrics).
Below, we list some specific optimization and cost reduction opportunities that can be achieved as a result of digitalization projects:
Automation
Flexibility
Less downtime
Product quality
Team coordination
Suppliers and partners
Knowledge management
Commissioning and maintenance
Energy management
Time to market
Traceability
New business models
Digital production management with manubes
With manubes, you are able to systematically automate production processes and visualize all areas of a production in real time.
The manubes platform offers worldwide access via web browser, easy operation and maximum security for production data.
Implementation
Digitalization strategies in production
The successful digitalization of a production environment requires a carefully planned strategy that takes into account both technological and organizational aspects.
More often than not, the integration of new technologies and solutions brings about fundamental changes to existing processes. Therefore, employee acceptance is also an important criterion for the success of digitalization projects.
At the heart of modern digitalization strategies in production is the intelligent networking of devices, software, people and processes. A central goal is the connected worker – operators equipped with digital tools that allow them to perform tasks more efficiently and precisely.
To exploit the full potential of modern software solutions and processing capacities, it is important that machines and devices in production are made accessible as data sources for Machine Data Acquisition. The targeted exchange of data within and between the shop floor (production hall, workshop) and the top floor (management and administration level) not only opens up potential for comprehensive monitoring of systems, resources and workflows, but also new possibilities for more effective production planning and production control.
Implementation
Interfaces
Interfaces and protocols are needed to connect machines and devices on the factory floor with each other and with local and higher-level software applications.
Data not only has to be collected and transmitted (often in real time and at regular intervals), but may also have to be converted into suitable formats and brought together in a central location. The quality of the data also plays a crucial role – for example, when monitoring production plants based on selected parameters.
One of the biggest challenges in production digitalization is to integrate a large number of different machines and devices as data sources while keeping the effort for developing and managing integration solutions to a minimum. Another key task in the planning and implementation of digitalization strategies is the prevention of security vulnerabilities.
In order to address the challenges described above, standardized interfaces have been developed for use in industry. One of the most important ones is OPC UA, a communication standard that standardizes the exchange of data between different machines, devices and software applications. Today, numerous machine manufacturers as well as software development implement OPC UA interfaces by default. At the same time, solutions exist to make older equipment capable of providing data through OPC UA.
Some of the most used communication protocols in production are MQTT and Modbus.
Implementation of digitalization projects
Assessment
Larger digitalization projects usually start with an assessment that evaluates existing systems, machines and workflows in terms of weak points and potential for optimization.
Define objectives
In order to measure progress and to create a clear guideline for all further actions, the next step is to define objectives. These could be time savings for manual activities, a reduction in downtime or more efficient communication channels.
Select and pilot technologies
Suitable technologies are then selected based on the previously defined objectives. These are often initially tested in pilot projects and, if successful, expanded to other areas or locations.
Train employees
Training and raising awareness among employees is also an important step in implementing digitalization projects and can have a significant impact on their success.
Improve continuously
Furthermore, digitalization is not a one-time project, but an ongoing process. Existing solutions should be regularly evaluated and optimized. Companies that embrace new technologies early on have the opportunity to gain competitive advantages.
Implementation
Brownfield and greenfield approaches to digitalization
When considering digitalization strategies, a distinction can be made between so-called “brownfield” and “greenfield” approaches.
The greenfield approach describes the creation of a digitalized production environment from scratch. In contrast to the brownfield approach, no existing structures need to be taken into account. In practice, the greenfield approach therefore most closely describes the planning and construction of a new factory.
In contrast, the brownfield approach refers to the integration of modern digital technologies into an existing production environment. The latter often includes older equipment that was built before digital networking in production became a requirement.
For most companies, the brownfield approach reflects reality. Digitalization projects have to be aligned with existing facilities and structures, which in practice are often gradually upgraded and modernized. One of the biggest challenges is to keep the complexity low and still achieve the highest possible level of interoperability and flexibility.
The actual measures taken often depend on the degree of digitalization already achieved by a company. For example, the implementation of a "paperless production" is often one of the first digitalization-related objectives, followed by initiatives for more extensive networking, data processing and process automation.
Comparison
Greenfield or brownfield – what is the difference?
| Criterion | Greenfield | Brownfield |
|---|---|---|
| Starting point | A new build from scratch | An existing production environment with installed equipment |
| Existing structures | Do not need to be taken into account | Set the framework for the digitalization project |
| Typical case | Planning and building a new factory | Modernizing a production that is already running |
| Approach | Digitally connected from day one | Equipment is upgraded step by step, often starting with pilot projects |
| Biggest challenge | Planning the entire production environment | Connecting older machines while keeping complexity low |
| Prevalence | Rare | The reality for most companies |
Technologies
Key technologies in production digitalization
Many digitalization strategies and solutions in production are based on a range of key technologies and technology concepts, which we will discuss in this section.
Cloud Computing
Computing power and storage over the internet
Cloud computing refers to the provision of computer resources over the internet, including storage space and computing power. In production, cloud platforms and cloud software offer the possibility of managing data from different production sites in a central location, allowing for collaborating independently of location and reducing IT administration. A wide range of software solutions for production are now offered in the cloud as part of a "Software-as-a-Service" model – from classic MES and ERP applications to specialized platforms for digital production management such as our product manubes. The major advantage over classic on-premise software is that the entire infrastructure, including necessary maintenance and updates, can be outsourced.
What is cloud computing?Edge Computing
Processing data at the source
Edge computing refers to the collection and processing of data at or near the data source. The word "edge" refers to the "edge of the network". In production, edge technology can be used in various areas. Local preprocessing of data may be performed to extract relevant information from large amounts of data, structure it and make it available via suitable interfaces. One example application are Edge gateways that collect local sensor and device data and then transmit it to central systems such as cloud-based IoT platforms. Our cloud platform manubes uses Edge Nodes to establish secure and bidirectional connections to local machines, devices and databases.
- Edge Nodes in manubes
- Edge gateways
Augmented and Virtual Reality
Overlaying information, simulating equipment
Augmented Reality (AR) and Virtual Reality (VR) offer a range of applications in modern production environments. Examples are supporting maintenance staff by (virtually) displaying additional information, planning and simulating new machines and entire production lines before they are built, as well as providing training in virtual environments.
- Maintenance
- Plant planning
- Training
Artificial Intelligence
Analyzing large amounts of data
Artificial intelligence (AI) is also increasingly being used in production. Suitable algorithms enable the analysis of large amounts of production data. A common application is predictive maintenance, where data is evaluated to predict equipment failures and determine the ideal time for maintenance. AI solutions also offer great potential in data preparation. Decision-makers in production planning depend on the right data being available at the right time. The AI-based Chat Assistant integrated into our manubes platform analyzes existing data structures and provides answers to production-related questions within seconds.
- Predictive maintenance
- Chat Assistant
Optimize your production with manubes
manubes offers a central platform for production data management, data visualization and workflow-based process automation.
Manufacturers gain access to a variety of innovative tools in order to quickly develop their own applications – tailored to their requirements.
Frequently asked questions about digitalization in production
What does digitalization in production mean?
Digitalization in production is the digital connection of machines, software and people in manufacturing. Production data is captured automatically, analyzed centrally and used to monitor, control and automate production processes. In industry, this is also referred to as Industry 4.0.
What are the benefits of digitalization in production?
The main benefits are less manual work, shorter downtimes, assured product quality and more flexible production processes. On top of that come better coordination between teams, departments and partners, and traceability of products and processes. The full list is in the Potentials section.
What are examples of digitalization in production?
Typical examples are digital work instructions on a tablet instead of paper, digital checklists for cleaning and maintenance, OEE dashboards showing machine data in real time, push notifications when a fault occurs, a digital shift log and material checks via barcode scan. Paperless production is often the first step.
How do you start digitalizing production?
It starts with an assessment of existing systems, machines and workflows. This is followed by measurable objectives, the selection of suitable technologies in a pilot project and training for employees. Digitalization is not a one-time project, but an ongoing process.
What is the difference between digitalization and automation?
Digitalization makes data and processes available digitally, while automation lets machines or software carry out tasks without manual intervention. Digitalization is usually the prerequisite for automation – for example for workflow automation that automatically informs the person responsible when a fault occurs.
What is the difference between greenfield and brownfield?
Greenfield is building a digitalized production from scratch, brownfield is digitalizing an existing production with installed equipment. For most companies, brownfield is the reality. The comparison shows the differences.
How can older machines be connected?
Via standardized interfaces and protocols such as OPC UA, MQTT or Modbus. Where this is not possible directly, a device on site collects the data and passes it on securely to central systems – in manubes, this is done by Edge Nodes.
What role does artificial intelligence play?
AI analyzes large amounts of production data, for example to predict equipment failures (predictive maintenance) or to answer questions about production data within seconds. Find out more under AI in production.
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