Increased efficiency, process optimisation, higher productivity and improved energy management – the advantages of smart manufacturing are multifaceted and on everyone's lips. But what is behind the buzzword and how does it relate to Industry 4.0? In this guide, we shed light on what smart manufacturing is all about, the advantages it offers and the use cases available to companies.
Definition: Smart manufacturing
‘Smart manufacturing enables fully integrated, collaborative manufacturing systems that respond in real time to changing requirements and conditions in the factory, in the supply network and in customer needs.’
At least, that is how the National Institute of Standards and Technology defines the term smart manufacturing. Here we encounter a familiar phenomenon with definitions: they often sound terribly complicated.
So how could we explain it more simply? Let's try this:
Our definition
Smart manufacturing refers to the integration of advanced technologies into the production process to increase efficiency, flexibility and quality. By networking machines and sensors, analysing large amounts of data and using cyber-physical systems, a data-driven, adaptable and highly precise manufacturing environment is created.
The aim is to maximise productivity, reduce costs and respond more quickly to market changes, enabling overall optimised and future-proof production.
Hopefully, that clarifies things a bit! If you are familiar with the subject matter, you now have a quick overview of everything you need to know about smart manufacturing. And for everyone else? Don't worry, this guide will help clear up any questions you may have. So, let's get started!
Smart manufacturing: the basics
So how can smart manufacturing be made even easier to understand? The answer is not that simple, as there are many related terms involved, such as IIoT, AI, Industry 4.0 and digital transformation.
If your head is spinning, don't worry – we'll take the time to explain it step by step. Let's start with some background information.
Although some of these technologies are already being used in companies, this is usually only on a limited scale and without the possibility of scaling up. However, the full potential can only be realised through systematic implementation using precise machine learning operations and the application of AI platforms.
That is why this is our core business. We not only support you in setting up the necessary systems, but also in imparting the necessary expertise to benefit from AI in the long term.
How does smart manufacturing work?
Smart manufacturing is not an isolated concept, but rather the result of comprehensive developments. And in order to recognise the true potential of smart manufacturing, it is important to understand these developments and how they are connected:
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Digital transformation:
Digital transformation is the overarching process that a company undergoes as it evolves into an Industry 4.0 enterprise. It is the strategic endeavour to integrate digital technology into all areas of an organisation.
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Industry 4.0
Industry 4.0 describes the fourth industrial revolution and stands for the use of smart, digital technologies in manufacturing companies to increase productivity, efficiency and flexibility.
Industry 4.0 is therefore a continuous process of digital transformation in manufacturing. Smart manufacturing, on the other hand, is what a company implements in its manufacturing to reach this stage of development.
Smart Manufacturing vs. Smart Factory
At first glance, these two terms appear to be synonymous – but there are actually important differences. Smart manufacturing and smart factories are closely related, but differ significantly in their focus and scope:
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Smart manufacturing describes the entirety of production processes and technologies that are optimised through the intelligent use of data, automation, machines and people. It refers to the improvement of the entire value chain, from material procurement to the delivery of the finished product.
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The smart factory is a sub-area of smart manufacturing. It refers to an automated and networked factory. Machines and systems work autonomously and communicate with each other to make processes more efficient and flexible, with a focus on real-time data processing, self-optimisation and predictive maintenance.
In summary:
Smart manufacturing encompasses the entire production process, while the smart factory is an intelligent, autonomous manufacturing facility within this process.
IIoT, AI and big data – the technologies behind smart manufacturing
Smart manufacturing relies on a complex interplay of modern technologies that are closely integrated with one another to enable intelligent, networked and flexible production. Here are some of the key technologies that form the basis of smart manufacturing:
Industrial Internet of Things (IIoT)
The Industrial Internet of Things (IIoT) forms the basis for Industry 4.0. It connects sensors, instruments and devices in industrial applications such as manufacturing and energy management.
This connectivity enables automatic data collection and analysis, leading to higher productivity and efficiency. IIoT is crucial for the automation and self-monitoring of industrial machines.
The connection between IIoT and smart manufacturing is therefore crystal clear: Smart manufacturing uses IIoT technologies to optimise production processes. Together, they enable smart, efficient and flexible manufacturing and thus form the heart of Industry 4.0.
Cyber-physical systems (CPS)
Cyber-physical systems (CPS) are integrated systems that link physical processes with digital technologies to enable seamless networking and interaction.
They connect mechanical and electronic components with digital control and monitoring elements that communicate via various networks, such as the Internet.
The networking is both wired and wireless and enables real-time interaction between the various system components.
CPS play a central role in smart manufacturing, as they enable the monitoring and control of production processes in real time, thus ensuring greater flexibility and efficiency. They form the backbone for the autonomous control and self-optimisation of production systems.
Cloud Computing
Cloud computing provides IT services such as servers, storage and software via the Internet. This allows companies to use computing resources flexibly without having to build their own infrastructure, which reduces costs and increases efficiency. They only pay for the services they actually use, and resources can be scaled as needed – ideal for smart manufacturing.
Cloud computing becomes crucial when combined with cyber-physical systems (CPS). CPS collects data that is stored and processed centrally in the cloud. This enables companies to analyse production data in real time and optimise processes flexibly.
Big data, AI and advanced analytics
Smart manufacturing generates huge amounts of data, which is collected and analysed using big data technologies. Advanced data analytics, including predictive analytics, extract valuable insights from this data that contribute to process optimisation, product quality improvement and downtime reduction.
AI (artificial intelligence) and ML (machine learning) go one step further: they recognise patterns, make predictions and optimise processes autonomously.
Big data is not only used to store and initially analyse large amounts of data, but also forms the basis for training AI models that rely on extensive data sets to make accurate and powerful predictions. At the same time, AI is used to analyse big data more efficiently and gain deeper insights.
This mutual relationship makes it possible to extract specific information from the data and recognise patterns that would remain hidden without the use of AI.
Robotics and automation
Robots and automated systems perform a wide range of tasks in a smart manufacturing environment, from assembly and quality control to logistics. These technologies enable greater precision, increased efficiency and the ability to work around the clock.
Modern robots are also often collaborative, meaning they work directly with humans and assist them with complex or dangerous tasks.
Virtual and augmented reality (VR/AR)
VR and AR have many applications in smart manufacturing, from employee training and machine maintenance to the simulation of production processes.
AR can be used, for example, to display real-time information directly in the field of vision of technicians, which is used in worker assistance systems, for example. These systems provide support in production monitoring, machine maintenance and repair, and the assembly of complex components.
VR is used to virtually test and optimise production lines before they are implemented in the real world, which avoids costly mistakes and increases efficiency.
Digital twins
Digital twins are virtual models of physical objects, production lines or even entire factories. These digital replicas enable detailed monitoring, analysis and optimisation of their real-world counterparts. Continuous synchronisation with the physical world allows companies to monitor processes in real time and make adjustments before problems even arise.
Smart manufacturing – a kaleidoscope of innovations
Now that we have navigated the jungle of definitions surrounding IIoT, AI, Industry 4.0 and digital transformation, smart manufacturing has become more tangible. It is like a well-oiled clockwork in which all the gears mesh perfectly – except that these gears are made of high-tech components and vast amounts of data.
The result: connected, intelligent manufacturing processes that are flexible, efficient and highly adaptable.
Companies that rely on this are not only fit for the future, but can also react to changes at lightning speed, fulfil customer requirements and strike an elegant balance between costs and quality.
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Advantages of smart manufacturing
Are you familiar with this problem? Old machines without digital connectivity, fluctuating quality and rigid production processes that are unable to respond to change? Challenges like these make it difficult to remain competitive in an increasingly digital world.
This is exactly where smart manufacturing comes in. Not only does it offer solutions to these familiar problems, it also brings a host of other benefits:
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Increased efficiency: By automating and optimising production processes, companies can significantly increase their efficiency. Machines and systems communicate with each other to ensure that production processes run smoothly and without errors.
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Cost reduction: By analysing real-time data and using predictive maintenance, downtimes are minimised and the service life of machines is extended, resulting in significant cost savings.
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Flexibility and adaptability: Smart manufacturing enables a rapid response to changes in demand or market conditions. Production lines can be flexibly adapted to produce new products or variants.
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Higher product quality: Thanks to precise monitoring and control of production processes, quality problems can be identified and rectified at an early stage, which improves product quality and reduces waste.
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Sustainability: Through optimised resource utilisation and reduced energy consumption, smart manufacturing contributes to sustainability and helps companies achieve their environmental goals.
Challenges on the road to smart manufacturing
The introduction of smart manufacturing therefore offers numerous advantages, but the path to achieving it is paved with various challenges. Many companies struggle with the following problems in particular:
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Lack of structure and responsibility: Clear structures and responsibilities are often lacking to effectively implement digitalisation projects. This leads to few or no resources being made available, as there is a lack of understanding of the ROI compared to the high management costs.
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Lack of data: Ensuring a sufficient quantity of high-quality data is a major challenge. Without this, systems cannot work efficiently, which makes it difficult to implement specific use cases.
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Individual processes: The specific requirements of each company require tailor-made solutions. Without careful adaptation and integration into existing systems, efficiency gains will not be achieved.
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Costs and resources: The high initial investments in infrastructure and qualified personnel require careful cost-benefit analysis. Companies must ensure that the necessary resources are available for successful implementation.
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IT-OT convergence: The integration of information technology (IT) and operational technology (OT) is crucial, but also challenging. Without a strategic approach, isolated projects often lead to inefficient processes and information gaps.
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Employee acceptance and participation: Digital transformation can cause uncertainty and resistance among employees. Early involvement and consideration of their concerns is crucial for successful adaptation to new solutions.
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IT security and data protection: Increasing connectivity increases vulnerability to cyber attacks and places high demands on data protection. Companies must develop new security concepts to prevent data leaks and protect their innovative strength.
Use cases – How companies are implementing smart manufacturing
Smart manufacturing unleashes its potential through the targeted use of digital technologies. To illustrate how these technologies improve everyday production, we present three use cases.
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Condition Monitoring:
Condition monitoring is an ideal entry point into digitalised production. It involves continuously monitoring machines and systems in order to detect faults and material fatigue at an early stage. Sensors record the actual status, which is then compared with the target values. If there are any deviations, appropriate measures can be taken immediately.
IoT gateways and hubs connect the machines and efficiently evaluate the data so that all relevant information is available to the plant operator.
The result: improved machine efficiency and increased safety. Condition monitoring also forms the basis for predictive maintenance, which will be discussed in the next section.
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Predictive maintenance:
Predictive maintenance – proactive maintenance. This is a maintenance process based on intelligent data analysis that prevents unplanned machine downtime. Thanks to real-time data processing and regular analysis of historical data, it is possible to predict precisely when maintenance is required.
The result: Better planning, higher machine availability, optimised spare parts provision and longer service life for the systems. Resource consumption is also reduced, as maintenance can be planned specifically and efficiently between orders. This requires the machines to provide and transmit data digitally.
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Predictive Quality
Predictive Quality focuses on predicting and ensuring product quality in the production process. To this end, Predictive Quality aims to identify and resolve potential quality issues early on, before they affect the end product. By analysing real-time and historical data, production patterns and deviations can be identified that indicate potential quality issues.
The result: less scrap, less rework and overall improved product quality. Predictive Quality is an essential component for further optimising manufacturing processes in smart manufacturing and increasing production efficiency.
Smart manufacturing: Ready for the future?
Despite the challenges companies face when implementing smart manufacturing, we believe the advantages outweigh the disadvantages. Technologies are constantly evolving, and so are the possibilities. Now is a good time to set the course for the future and further develop your own manufacturing processes. Are you ready to take this step?
FAQs about smart manufacturing
How can smart manufacturing contribute to sustainability?
Through the optimised use of resources, the reduction of energy consumption and waste, and the efficient planning of production processes, smart manufacturing helps companies achieve their environmental goals.
How do I start implementing smart manufacturing in my company?
Start by developing a clear digital strategy that is aligned with your business goals. Identify suitable use cases, select the right technologies and develop a scalable architecture that supports future growth.
How does smart manufacturing differ from traditional manufacturing?
Smart manufacturing uses digital technologies such as IIoT, AI and machine learning to automate, optimise and make production processes more flexible. Unlike traditional manufacturing, it enables real-time adaptation to changing conditions and better integration of production systems.
Albrecht Lottermoser is a Senior Smart Factory Expert at MaibornWolff. The mechatronics and engineering sciences expert specialises in automation, robotics, human-robot cooperation and intelligent process control. He supports organisations and companies in numerous research and industry projects relating to smart factories, digitalisation and artificial intelligence.