Fast, efficient, highly connected – smart manufacturing is revolutionizing industry through the use of modern technology and the exchange of relevant data from all areas. But the path to smart manufacturing solutions and Industry 4.0 also poses major challenges for companies. We have summarized what is behind the buzzword smart manufacturing, where the concept is already creating added value today and where it often falters.
Definition: What is meant by smart manufacturing?
Smart manufacturing is an umbrella term for a number of technological and organizational innovations that have been introduced in recent years. Sensors connected via the Internet monitor all sub-steps and generate data that is further processed using artificial intelligence, among other things. This innovative approach is enabling industrial companies to make revolutionary advances in terms of adaptability, efficiency and future viability.
The main drivers of this process are further developments in the fields of data science, sensor technology/monitoring and artificial intelligence. They provide for technical and organizational improvements in the entire production process. Furthermore it has been recognized that an automated data exchange between all subareas of production is necessary to make the whole process as efficient as possible. Only in this way can the individual areas work together effectively and form a unit, the smart factory.
Smart manufacturing should be understood as an ongoing process of further development. Increasing automation, new, intelligent manufacturing software and ever more extensive collection and use of data are creating new optimizations. Industrial companies that opt for the path to smart manufacturing will have to question traditional methods and ways of thinking. In return, they will be rewarded with greater dynamism, efficiency and resilience to market changes.
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Background: The history of smart manufacturing
In industrial manufacturing there has always been a remarkable interest in making improvements and increasing productivity. With the invention of the steam engine, the mechanical loom, and the general shift toward machine-based manufacturing, the first industrial revolution began around 1760. Since then, innovations such as the widespread use of steam locomotives and rail transportation have been adopted at a rapid rate.
The second Industrial Revolution, beginning around 1870, saw the emergence of the first businesses that meet our current definition of “industry.” Assembly line production became standard, and the introduction of standard parts and the availability of inexpensive steel made it possible to use machinery on a scale previously unthinkable.
After the end of World War II, digital control methods and the first computers found their way into manufacturing. The third industrial revolution and the information age had begun. With the ability to process data effectively, widespread automation and efficiency gains were possible.
In the context of the fourth industrial revolution, Industry 4.0 or intelligent production, new technologies, methods and insights are being adopted quickly and without reservation in industry, and a huge market for smart manufacturing has emerged. Data science has become an important discipline which is “fed” by an increasing number of sensors. Combined with major advances in artificial intelligence, this is creating the basis for ever more efficiency gains.
Smart manufacturing technologies
Unlike earlier phases of industrial advancement, Industry 4.0 is not based on a few dramatic inventions (steam engine, mechanical loom, first computers …). Instead, it is the evolution of key areas and their synergistic effects on each other that leads to the rapid improvements.
Among the central technologies are:
- The Internet of Things (IoT). Virtually every conceivable object is being equipped with sensors, computing capacity and software and connected to other devices via the internet. A huge amount of data can be obtained through this network. The IoT probably has the greatest potential in the industrial sector, but it is also becoming more widespread in other fields.
- Smart manufacturing and the IoT are now inextricably linked, as only by networking devices and sensors can the necessary data be obtained. The development of the “Internet of Things” is clearly favored by the fast 5G network, but can also be realized with other networks.
- Powerful data processing: Data science has become a central discipline in the digital age. It must be able to process the extensive information gathered by sensors in the IoT network and by other sources. Since the data is the basis for subsequent optimizations and automations, it has enormous value for companies.
- Predictive Analytics: With a wealth of data, it is possible to make reliable forecasts. This creates potential for optimization and enables companies to identify problems before they occur. For example, predictive maintenance uses sensors and a big dataset to analyze the condition of machines to find the best times for maintenance and avoid breakdowns. A smart farm, on the other hand, uses sensors to collect data on soils, water, environment, etc., and use it to create data models that predict when action is needed and significantly increase yield.
- Digitization: What is a smart factory or smart manufacturing without the people who run and improve it? Workers are being included in the digital fabric of modern manufacturing and are experiencing numerous improvements as a result. Augmented reality (AR) or virtual reality (VR) solutions are increasing their safety and simplifying their work. Devices like smart glasses (in combination with the right smart glasses software) integrate workers into the web of smart manufacturing software, providing vital information and streamlining workflows.
Advantages and disadvantages
The use of smart manufacturing and automation technology offers a number of unique advantages for industrial companies. At the same time, however, there are issues that must be considered during implementation.
Key benefits include:
- Improved measurement and control of operations through sensors and big data. This allows for more flexible deployment and makes companies more efficient and future-proof.
- Increased employee satisfaction as their own work becomes more valuable and less repetitive. The many new, technical tasks also offer great potential for further training and personal development and attract new talent.
- Higher quality and lower probability of errors, as the system’s sensors and analysis capabilities allow for better quality control.
- Lower maintenance and operating costs due to optimized workflows and savings from predictive maintenance.
- The ability to build a smart warehouse, reducing warehousing costs – while improving performance.
- Reduced waste production and energy consumption through optimized operations and increased efficiency.
The main disadvantages are:
- High initial cost to enter the smart manufacturing market. Setting up the infrastructure, skilled workers, etc. requires large amounts of time and capital. Companies are therefore well advised to start the transformation as early as possible.
- There is a shortage of skilled workers such as data scientists, analysts and IT specialists, who are essential for building and operating the complex systems.
- If the smart manufacturing transformation is rushed, pursued improperly or without full commitment, damage is imminent as the old production methods are attacked but the new procedures are not yet established.
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Smart vs. traditional industry: What are the differences?
While traditional industrial production is based on high volumes through permanent utilization of machines, smart manufacturing adopts a different approach: Here, the right parts, at the right time, and the right conditions are produced. This is possible through the use of fully integrated systems that work together collaboratively.
This can neutralize two central problems of the previous approach: Errors in production are often discovered only after the respective operation has been completed, resulting in large amounts of waste; in addition, a longer (and expensive!) setup time is required to prepare the machines accordingly.
How to implement smart manufacturing
Moving to smart manufacturing is not a simple project, but a long and continuous process. Companies must set goals to pursue along the way:
- Measure the efficiency, costs, quality and other key performance indicators and make them visible
- Set up sensors and collect data from a wide variety of sources and store it in a structured way
- Use data models and artificial intelligence to make initial deductions and start optimizing them
- Continuously learn, improve ad use best practices.
Implementing intelligent manufacturing methods is a big challenge – but with an experienced partner like TeamViewer, it can be achieved quickly. For example, our highly sought-after Frontline series can easily deliver over 40% efficiency gains with a short setup time, as proven in practice. You can also find more information in our Smart Glasses Guide.