11 Biggest Digital Trends and Predictions for Manufacturing and Industry in 2023


10 najväčších digitálnych trendov a prognóz pre výrobu a priemysel na rok 2023

One crisis follows another crisis. Crisis management is becoming an everyday norm of business management. Having in mind this state of events, we select the biggest trends and technologies that will dominate the manufacturing industry in 2023.

One crisis follows another crisis. Crisis management is becoming an everyday norm of business management.

Despite the pessimistic outlook, most businesses continue to operate. Overcoming crises and obstacles has become a common part of every field, and it is no different in production and industry.

However, the solution to sudden and unexpected changes remains the same: innovation.

Also considering the current development of events, we looked at what trends and technologies will dominate in 2023.


The Industrial Internet of Things (IIoT) is not only a key but a fundamental technology of a digital revolution in industry. As the cost of IoT-enabled hardware and services to continue to fall, more manufacturing companies, warehouses, and other industrial operations are introducing IIoT into their premises.

The primary purpose why IIoT is being introduced is to

  • increase operation performance,
  • improve the safety of the working environment,
  • increase the efficiency of processes
  • and scale automation.

Among the most significant benefits of the industrial Internet of things is primarily the acceleration of digitization in production through:

  • complete process automation,
  • optimization of production flows,
  • monitoring and control of production and transport equipment in real time,
  • improving customer service
  • and reducing energy consumption.

But above all, no digital technology for industrial and production processes can do without a sufficiently reliable Internet of Things.

And with the ever-growing number of cloud services and application-as-a-service (EaaS, "Everything as a Service“), no operation without IIoT will achieve sufficient competitiveness. Nor will it be able to overcome the obstacles that await the industry.

industrial internet of things IIoT

2. DATA mining and deep ANALYSIS

The affordability of sensors coupled with powerful analytics creates an ideal environment for the added value brought by the Industrial Internet of Things. Affordable tools enable businesses to gain valuable insights from data generated in their operations or warehouses. These data are then used to optimize and fine-tune processes for greater efficiency and cost savings.

Additionally, advanced analytics technology enables businesses to create detailed predictive models that can predict future problems before they occur. This enables, for example, proactive maintenance interventions that lead to less expensive repairs or avoid delays due to unexpected breakdowns.

With the development of 5G networks in 2023, the Industrial Internet of Things will also continue to scale. Lower latency and higher response will

  • improve data speed,
  • contribute to more accurate data collection
  • and its real-time analysis.

Moreover, data analytics is becoming an inseparable tool, both technological and cognitive, for most essential decision-making processes. And not only for executive and managerial positions, but predictive models for prognostics are also becoming helpful for other job positions and classifications as well

  • from production planning
  • through purchase
  • expedition
  • up to maintenance.

However, deep data analysis is also relevant for project managers, production adjusters, and logistics employees. Based on data analysis, they can

  • remove bottlenecks in material flows and manufacturing processes,
  • slim down selected procedures
  • and fine-tune work-production methods.

data mining and deep analysis in manufacturing


As technology continues to advance, more and more companies are adopting smart factory and smart manufacturing concepts to increase their production capabilities and options. In 2023, we expect an even greater expansion of these concepts, as they, like the Industrial Internet of Things, are becoming a common part of the entire production sector in various forms.

In the coming years, we can expect a sharp increase in automation with intelligent technologies, which will enable more efficient production processes with lower costs, even in view of the lack of the necessary workforce.

  • Robotics,
  • artificial intelligence (AI),
  • machine learning (ML)
  • and data analysis

are just some of the technologies that will be used to

  • speed increase,
  • accuracy
  • and production efficiency.

In addition, AI-based predictive maintenance solutions will help businesses detect anomalies or errors early before they cause costly downtime on production lines.

In addition to automation and smart technologies, we can also expect greater integration and networking between businesses and industries. Smart factories are increasingly connecting with other industries such as healthcare, automotive, energy, retail, and logistics.

Such integrations will create new opportunities for collaboration between different sectors and result in improved services as such

  • customization of products to clients
  • and personalized customer experience.

Smart manufacturing and (semi-)automation initiatives based on smart technologies offer many advantages for businesses that want to remain competitive in an ever-changing market.

For example, they allow operations to become more efficient with improved insight into all aspects of the manufacturing process, from initial product design decisions to delivery. This allows manufacturers to quickly adapt production lines

  • changes in customer requirements,
  • market demand
  • or running out of stock.

Smart manufacturing offers a number of benefits including

  • better transparency in all processes,
  • simplified production and assembly procedures,
  • reduced downtime,
  • increased safety and ergonomics at workplaces.

An equally important procedure will be connecting conventional devices with intelligent technologies. And above all

  • digital (cyber) automation,
  • AI
  • and robots.

smart manufacturing and smart factory scaling


The deployment of autonomous devices is increasing every year. It is precisely the lack of qualified employees that accelerates the pace at which autonomous machines are put into operation. The persistent shortage of employees and their long-term increased turnover contribute to the profitability of purchasing or renting autonomous devices. Based on the ROI calculation, autonomous machines would not be so profitable if the situation in the labor market was stable.

Autonomous machines are capable of performing repetitive tasks such as

  • cutting,
  • drilling,
  • painting,
  • welding and more

with little or no human intervention. As they become more widespread, expect their use to reduce costs while increasing productivity and accuracy.

Operations related to logistics using AGV and AMR are already being added to the existing range of activities, especially in

  • supply of materials,
  • stock replenishment,
  • moving semi-finished products between production workplaces
  • and moving work-in-progress (WiP) products between individual halls or even businesses.

The higher rate of deployment of autonomous machines and devices is also related to ever-increasing robotization. Even in the case of companies that relied on manual labor for most of their operations.

the growth of autonomous machines


Predictive maintenance solutions use artificial intelligence (AI) and machine learning to identify potential problems with production or transportation equipment and prevent them. Predictive maintenance provides industrial enterprises with an invaluable tool

  • to maintain the efficient operability of equipment
  • and simultaneously optimize costs associated with unexpected downtime and repairs.

Using real-time data collected from sensors, predictive maintenance can monitor machine performance (OEE) and alert operators and managers

  • if the set limits are exceeded
  • or when components wear out excessively, which can lead to costly downtime.

Predictive maintenance solutions make it possible to make repairs or replace parts before significant equipment damage occurs. Thanks to this, the overall reliability of the operation increases.

Predictive maintenance not only saves costs by preventing equipment repairs, but also by optimizing energy consumption due to inefficient machine operation.

Other benefits of predictive maintenance include:

  • warning of impending failure or malfunctions,
  • optimizing productivity by identifying best practices and trends in the industry from other businesses (sharing and exchanging data),
  • reporting accurate information about the performance of individual devices in real-time.

Thanks to these benefits, manufacturing companies can remain agile in an ever-changing environment and simultaneously

  • reduce operating costs,
  • increase production
  • and improve quality control standards.

new generation of predictive maintenance


If a business has the Industrial Internet of Things (IIoT) and is introducing digital automation into its manufacturing and supply processes, it can rarely work without digital twin technology.

A digital twin is a virtual representation of a real process, product or device and helps to bridge the gap between physical and digital environments, making industrial processes more efficient.

This technology enables greater control over quality and safety through plausible process simulation. This allows businesses to better identify potential problems before they occur in real-world operations. With digital twin technology, engineers can analyze data in real-time to anticipate obstacles and make decisions faster.

Additionally, it improves communication between operations teams and designers as they can collaborate virtually using digital models. This technology allows manufacturing enterprises to react quickly in cases where it is necessary to implement modifications or adaptations to products without delay.

Designers and engineers can use simulations to test potential designs without having to physically build a prototype version first. Thanks to this, they can debug not only the product itself but also the process of its creation.

Companies that adopt this technology will gain

  • greater operability,
  • better use of resources
  • and reduced costs associated with production downtime due to fewer defects in their products.

This technology also offers businesses predictive analytics capabilities that allow them to forecast breakdowns or maintenance requirements before an actual need arises.

Digital twins can also provide greater insight into supply chain management by providing data on how materials are used.

But more importantly, digital twins are the secret weapon of digital automation.

In addition to simulations and transparency of data flows in production and supply, digital twins are also a tool to "animate" operational equipment. Digital twins enable non-smart devices to acquire a form of artificial intelligence and thus proactively enter processes.

Deploying this technology to a fleet of handling and transport equipment will enable the automation of supply processes. The devices, through its digital twin, the virtual avatar,

  • transmit information
  • coordinate with each other when performing work assignments
  • and they synchronize with each other so that the necessary parts are delivered in the right quantity and type, on time, and to the right place.

industrial digital twins


With increasing demand for products and services, as well as increased competition due to globalization, manufacturing companies worldwide are facing a shortage of skilled labor. They try to solve this deficiency primarily by

  • raising wages,
  • expanding social benefits
  • and retraining of workers.


To ensure that their employees are able to flexibly respond to the changing needs of their industry, many companies are trying to

  • retrain your employees on new technologies
  • and motivate them to acquire new skills.

Naturally, the expansion of skills is primarily linked to work with added value. By developing training programs for automated systems and providing sufficient support for learning new technologies, employers in manufacturing can

  • keep your teams up-to-date on current industry trends
  • while helping them become more effective in their work tasks.

Routine manual activities are being automated through robotization, while artificial intelligence (AI) solutions are also being deployed for mental work. The problem of a labor shortage is a pressing problem for many industries and businesses. Digital solutions can provide sustainable and effective solutions to this growing problem.

One of the ways digital solutions are helping to address labor shortages is through machine learning algorithms. These are used to analyze large amounts of data and identify trends or patterns from past experiences that provide important information for potential future decisions.

In addition to automation and AI-enabled decision-making tools, cloud computing is another area where digital solutions have proven useful in addressing the workforce shortage problem.

By using virtualization technologies such as

  • Infrastructure as a Service (IaaS)
  • and Platform as a Service (PaaS),

organizations can access computing power without the need for physical servers or on-premises hardware, reducing reliance on additional staff.

Additionally, they benefit from scalability options that allow them to adapt their services to market demand without affecting staff requirements. Cloud computing also allows businesses to access state-of-the-art software applications at minimal cost and provides full control over access rights, which is not always possible with traditional on-site solutions.

employee retraining and AI


Society-wide pressure for carbon neutrality in the manufacturing industry is gaining momentum, and businesses are playing an increasingly important role. Industrial companies support the development of new technologies and processes, which result in

  • reducing emissions,
  • increasing energy efficiency
  • and the use of renewable energy sources.

Digitalization and automation play an irreplaceable role in achieving carbon neutrality.

Digitization enables companies to collect data on all circumstances and aspects of their operations, including data related to emissions, from production lines to supply chains. This data can be used by businesses to identify areas where emissions can be reduced, as well as to evaluate potential solutions to reduce them.

Automation helps ensure processes run more efficiently by eliminating energy-intensive processes. Automated management systems such as MES, WES, or advanced OEE can also be used to monitor all types of data such as

  • energy consumption,
  • emission level
  • and gaining real-time insight into operational performance.

In addition to increased efficiency, digitization and automation help reduce costs associated with achieving carbon neutrality goals by

  • streamlining operations
  • and eliminating waste in production processes.

Predictive maintenance also helps reduce emissions, as it prevents breakdowns on production lines caused by mechanical failures leading to waste

  • material
  • as well as energy sources.

One of the ways in which industrial enterprises move production towards carbon neutrality is the development of intelligent systems. These often use advanced analytics algorithms and machine learning (ML) to forecast energy needs and demand patterns to better manage the use of renewable resources such as

  • solar
  • or wind energy.

By anticipating fluctuations in demand, smart systems allow manufacturing companies to not only reduce their impact on the environment but also save costs associated with purchasing more electricity when it is most expensive during peak times.

In addition, advanced sensors deployed within the Industrial Internet of Things allow businesses to monitor how efficiently resources are used. Companies can then adequately

  • adapt their use,
  • thus improving the overall efficiency of handling energy resources
  • and reduce negative impacts on the environment.

Ultimately, efforts to reduce waste production and excess energy consumption will be one of the key trends. The low-carbon economy should begin to be practiced in all sectors of our society, and at the same time, it is also related to the overall sustainability of production operations.

carbon neutrality in industry


Industrial enterprises are increasingly vulnerable to cyber attacks that cause downtime and information leaks.

As dependence on technology continues to grow, businesses find themselves in a precarious situation as their systems and data become more vulnerable to attacks and cyber-extortion.

Businesses face a number of threats including

  • malware,
  • phishing attacks,
  • ransomware,
  • DDos attacks
  • and other malicious activities aimed at stealing intellectual property or disrupting operations.

Cyber attacks primarily threaten critical operations on assembly lines and supply chains.

Information leaks are another consequence of a cyber-attack in which sensitive corporate secrets such as prototype designs or trade secrets are stolen and disclosed. This not only affects the company's reputation but also puts it at a competitive disadvantage.

Additionally, there is an increased risk that attackers will use sophisticated techniques, such as "zero-day exploits", which take advantage of previously unknown software flaws. This results in businesses being particularly vulnerable while waiting for new updates that may not be available immediately.

With cybercrime on the rise across all industries, it is imperative that businesses invest in robust security measures to reduce their exposure to these threats. This includes implementing a comprehensive set of cyber security solutions such as

  • firewalls,
  • antivirus programs,
  • intrusion prevention systems (IPS)
  • as well as ensuring proper staff training in safe internet practices.

It is imperative for industrial enterprises to stay informed of any new developments in cyber threats so that they can remain prepared for potential attacks.

cybersecurity in industry and manufacturing


Energy management is becoming an increasingly discussed topic even in connection with digital transformation. In addition to the strategy of operational sustainability and the effort to achieve carbon neutrality, it is a hot topic especially in the case of fluctuations in energy prices. Digitization enables businesses to use smart technologies to monitor, manage and optimize energy consumption on their devices.

Part of the energy management initiative is a detailed analysis of already existing infrastructure and processes. Businesses need to consider what equipment needs replacing or upgrading and how energy is currently being used throughout the operation.

Businesses should then use this data to identify opportunities for deciding what investments are needed to increase efficiency. For example, they might consider adding sensors and switches that detect device inactivity and turn it off.

Energy-saving solutions also include predictive maintenance options. These make it possible to adjust settings on production equipment based on real-time data information to save energy without reducing performance.

Automated measurement systems that monitor the electricity consumption of each device connected to the network enable better decisions about the load of individual devices, which leads to more efficient use of corporate resources.

By using these tools and solutions appropriately, companies can achieve significant cost savings while reducing their environmental footprint without losing their competitiveness.

energy management in manufacturing


After material supply shortages in previous years, manufacturing companies must be able to quickly adapt their supply and supply chain management processes. Above all, this means the ability to track material orders in real time and ensure that stocks are always up-to-date and occurence of

  • delays
  • or shortages

do not happen at the moment when the relevant materials, parts or components are recalled for production or assembly.

Intelligent logistics solutions such as

  • predictive analytics
  • and digital twins,

can help streamline supply operations while reducing costs and labor associated with transportation, handling, and storage.

Logistics and supply chain are gradually becoming an organic part of production and assembly processes. The streamlining of operational processes and digital automation contribute to the integration of production and logistics through intelligent process management systems such as

  • MES systems,
  • WMS systems
  • or WES systems.

integrated logistics and supply chain in industry and manufacturing