7 Tech Trends in Smart Manufacturing and Digital Transformation for 2021


7 Tech Trends in Smart Manufacturing and Digital Transformation for 2021

Strategic innovations, consolidation of manufacturing processes, and adaptation of operating models and processes to the new post-COVID-19 standard are the key priorities for 2021.

The year 2020 was marked by the COVID-19 global pandemic that significantly affected not only the economic sector, but also reshaped the way manufacturing enterprises and factories operate. The whole manufacturing sector and supply chains had to respond immediately to the unexpected challenges of the pandemic.


However, the crisis caused by COVID-19 did not fundamentally alter the manufacturing industry trends begun in 2019 of digital transformation and intelligent automation. In fact, the radical changes imposed on the workforce, including the massive migration of employees to remote work and the greater share of services shifting towards the cloud, have contributed to a global acceleration of the digital transformation across industries and enterprises. Prior to the pandemic, digital enterprise initiatives and innovations already proved to be essential tools for the sustainability of operational processes.

Trends from the previous period remain relevant. However, the priorities of their roll-out are changing. The pace of implementation of advanced digital technologies is gradually increasing. The same goes for the scaling up of previously implemented digital and smart solutions.

Manufacturing and processing organizations, as well as a variety of other industries, will progress to the smart factory (digital enterprise) concept faster. Some surveys have found that the COVID-19 crisis has accelerated digitalization by 3-5 years, and advanced digital products by up to 7 years.

Manufacturing businesses had to resort to temporary solutions and emergency measures to ensure the sustainability of their operational processes during the pandemic. An important insight for many businesses and organizations during the crisis was that innovation of their processes and procedures can happen more rapidly than they originally thought possible. This knowledge has led to strategic changes in the short- and medium-term plans for the investment into innovation and deployment of digitalization projects.

Development plans focused on digital technologies have now been integrated as an organic part of the business strategy. Keeping up with the trends through planning and re-prioritizing is key, not only to overcome the crisis, but also to successfully function in the new post-COVID-19 world. It is already clear that manufacturing businesses and processing industries will become more digital than before the pandemic outbreak.


"44% of manufacturing and distribution leaders named changing the business model to adapt to COVID-19 as the top priority challenge"

2021 will ideally be the year of convalescence. Swiftly following the end of emergency procedures, businesses will be expected to have completed most of their recovery work. COVID-19 recovery includes stabilizing the critical points and mitigating the negative impacts of the pandemic on operational processes.

However, the goal of the upcoming period of restoration will not be to return to the pre-COVID point. 2021 will be the year of the transition to "a new normal" – to new standards for operating models and strategies.

The path to the economic and operational rehabilitation of manufacturing businesses will lead through numerous in-house projects of digital transformation. The continuous deployment of advanced digital technologies into processes on the shop floor and at production lines will be among the top priorities.

Surveys among enterprises have shown that the biggest changes introduced by organizations to mitigate the effects of COVID-19 will remain integrated in standard operations even after the pandemic. Besides, among "new normal" measures is also the standardization of a continuous home-office mode and the formalization of remote (virtual) cooperation between partner companies and suppliers.


"Facing different business challenges, smaller companies shifted the most to adopt new use cases for their data in response to the crisis. They lead larger enterprises in the use of analytics across every department with 68% of small businesses using analytics in Operations, 56% in Finance, 50% in Sales, and 45% in Product"

Shop floors, manufacturing operations, and assembly processes cannot be effectively managed without access to correct and current data, and this becomes even more important during crisis management.

However, some businesses found out that they do not have sufficient data available to properly handle the pandemic situation. As a result, they were unable to make correct, qualified, and most importantly quick decisions under the pressure. Therefore, they did not manage to diminish the negative impacts soon enough.

On the contrary, businesses with sufficient access to real-time data were able to respond swiftly. Some companies also changed the planning of production shifts or started monitoring the availability of their workforce more effectively to ensure the necessary sustainability for manufacturing processes.

Data transparency in crucial manufacturing processes is key for efficient production planning and agile scheduling of tasks to optimally meet demand. This is especially important when customer requirements or priorities shift quickly.

Increasing the interconnection of workplaces, facilities on the shop floor, and beyond through enterprise Internet of Things (IoT) will enable businesses to monitor the development of manufacturing tasks more precisely in real-time. As a result, they will gain a comprehensive overview of all relevant ongoing processes and will be able to further optimize their shop floor operations.

At the same time, extending the framework of manufacturing and enterprise data collection will enable the company to work more efficiently. This will translate into improved Business Intelligence, which will help speed up qualified decision-making processes, even during periods of crisis.

The growing demand for more detailed data analytics will lead to the expansion of the enterprise Internet of Things (IoT) network. The scaling up of IoT networks throughout shop floors will make measuring equipment effectiveness (OEE) and the interconnection of manufacturing resources a common practice in the industry.

Smart industry solutions and cyber-physical platforms for operational manufacturing management are helping to connect enterprise resources and to automate their management in order to synchronize and optimize shop floor operations and business processes.

The growth in the available data and the scaling up of the industrial IoT paves the way for further improvement in production potential and supply process optimization, especially for:

  • expansion of the total production capacity during a work shift
  • increasing throughput on a shop floor (workplaces and assembly lines)
  • shortening production cycles (improving production lead-time)

The implementation of advanced technologies is necessary to fulfill the potential for improvement. Most notably the technology of digital twins, which is already integrated into modern smart industry systems.

Data availability, migration to cloud applications, and a complex IT infrastructure will facilitate the deployment of intelligent manufacturing solutions during the scaling up of Smart industry systems. This will also be reflected in a reduction of initial investment into digital twin technology in order to prioritize automating the management of manufacturing and logistics operations.


"By 2022, 70% of enterprises will integrate cloud management — across their public and private clouds — by deploying unified hybrid/multi-cloud technologies, management tools, and processes"

Scaling up the in-plant Industrial Internet of Things (IIoT) network will increase the demands on the sustainability of digitalized production processes. The vision of a smart factory will be increasingly realized through the employment of cloud services and "cloud-ready" applications.

The COVID-19 outbreak boosted the migration wave towards the cloud. This trend will continue in the post-pandemic world. In addition, the cloud will play an important role in the enterprise IT architecture in the upcoming period.

Businesses will gradually transform their IT networks and transition to a cloud-centric infrastructure. Furthermore, the launch of the fifth generation of mobile networks (5G) will accelerate this transformation. At the same time, the use of hybrid clouds - a combination of infrastructure located on premises, in private cloud services, and in the public cloud - will increase.

IDC estimates that up to 80% of businesses will take steps to move to a cloud-centric digital infrastructure by 2021. This change will help expand the adaptability and improve the flexibility of the enterprise's digital infrastructure. At the same time, more agile and resilient digital infrastructure will establish conditions for increased automation of:

  • enterprise IT
  • operating procedures
  • business operations

During the transformation of the IT structure of industrial and manufacturing enterprises, the large volumes of data and complex IoT network will also require increased cybersecurity. Most notably in:

  • industrial automation security
  • identity and access management
  • company readiness for complicated cyber threats and intensive cyber attacks

According to surveys, up to 55% of businesses plan to increase investment into cybersecurity in 2021.


"85% of firms believe predictive analytics is critical for operational excellence"

Machines, equipment, and tools can be monitored in real-time if they are connected to the enterprise Internet of Things (IoT). This will enable businesses to use their manufacturing data to obtain detailed performance analyzes and calculate accurate OEE [Overall Equipment Effectiveness] without delay.

The availability of data and analysis will accelerate the generational shift in maintenance management. Manufacturing enterprises will start to move from a preventive maintenance system to a predictive maintenance strategy. The new generation of asset management will allow the use of individual maintenance strategies [SAM, Strategic Asset Management] for manufacturing technologies and equipment.

Individual maintenance strategies will make it possible to precisely schedule maintenance interventions and to plan necessary shutdowns, thus reducing the frequency of accidental outages. Other benefits include:

  • preventing unplanned outages or failures
  • extending the lifespan of manufacturing technology and equipment
  • waste elimination
  • overall optimization of operational expenses

More advanced smart industry management systems already have predictive maintenance modules or can be fitted with this functionality on demand.


"69% of jobs in the manufacturing require specific digital skills"

One of the most radical changes in the way we worked in 2020 was the massive transfer of employees to home offices and the use of remote forms of cooperation. According to a Gartner survey, up to 88% of organizations allowed employees to work from home during the first wave of COVID-19. Up to 97% of companies canceled business trips. This new standard of work will become the norm in the post-pandemic world as well, including in the manufacturing industry.

The adoption of online cooperation tools across departments is expected to grow. Simultaneously, the deployment of artificial intelligence (AI) tools will increase. Some surveys estimate that the upcoming period will see a 35% increase in AI implementation in workplaces for "on-site" and "online" work.

Manufacturing companies and shop floors will become a place of technological transformation which will drive a socio-cultural shift. Artificial intelligence and machine learning will lead to the emergence of hybrid workplaces that utilize the tools of augmented intelligence - a combination of human and machine cognitive abilities.

As the pace of introducing digital tools into manufacturing accelerates, employees will need to expand their digital skills and competencies to adapt to the new operational processes.

According to studies, the skill gap may leave an estimated 2.4 million positions unfilled in the manufacturing industry between 2018 and 2028. It is vital that companies ensure the continuous growth of their employees’ digital skills and competencies. This is just another example of how these technologies will transform the way we work.

At the same time, hitherto non-existent positions will be emerging in the industry. It won´t be possible to fill these new positions without candidates who have advanced digital skills. Future manufacturing positions will include digital twin engineers, enterprise IoT network administrators, predictive supply analysts, smart factory operations managers, warehouse or maintenance drone fleet managers, and more.


"More than 53% of manufacturing firms anticipate a change in their operations due to the COVID-19 pandemic"

The COVID-19 pandemic caused a disruption in the market, which subsequently plunged companies into a state of continuous crisis management. Emergency measures are part of a reactive management strategy.

These emergency measures have a limited lifespan and require a lot of time and resources to prepare and deploy. Since they are most often prepared in reaction to specific circumstances, these measures and solutions are not directly applicable to future unknown situations.

More frequent and turbulent changes can be expected during the coming period in the market. These will be diverse in nature, ranging from geopolitical events to economic conflicts to climate change with few foreseeable consequences.

Businesses cannot prepare procedures for every possible crisis scenario. Furthermore, it is impossible to forecast every kind of emergency and then model adequate actions accordingly. The solution to ensuring the continuity and sustainability of manufacturing and supply operations is to shift to agile operational strategies.

Improvement of the resilience of manufacturing processes against outages can be achieved through increasing the flexibility of operational processes. This will allow manufacturing firms to dynamically adapt to new situations and adequately adjust manufacturing and logistics processes.

For manufacturing companies, the level of elasticity and adaptability to changes depends on the degree of digitalization. Advanced digitalization enables prompt consolidation of operations in the firm, which results in a boost to their competitive advantage, not solely during periods of crisis, but also during the standard regime.

Firms will be able to adapt to breakthrough changes, responding instantaneously to emerging business opportunities. At the same time, companies can invigorate the manufacturing and supply continuity of their operations.

Manufacturing companies and factories have already begun turning towards more flexible operating strategies. These are usually smaller solutions focused on one area or one functionality. For example, labor management at chosen workplaces, or a dynamic material supply at assembly lines. However, these limited solutions do not encapsulate a wider range of necessary activities in the chosen environment.

Businesses will need to start moving faster from pilot (proof-of-concept) projects to fully developed systematic scaling of digital solutions and intelligent automation. Manufacturing companies should begin to adopt, along the principles of lean manufacturing, a holistic approach towards digital transformation and process automation.

In manufacturing enterprises, a holistic approach means:

Reduction of changeover times, one of the procedures that increases the resilience and flexibility of manufacturing operations, will contribute to:

  • extending the production throughput
  • reducing the necessity for manual interventions
  • improving OEE [Overall Equipment Effectiveness] parameters

As a result of these manufacturing strategy adjustments, the company will be able to produce smaller batches of variable (and customized) products and respond more dynamically to variations in customer behavior patterns.

In addition, artificial intelligence and machine learning technologies will be implemented for the purpose of improving the assembly line performance, as well as being introduced into other related processes such as product quality control and energy management.

The automotive manufacturing, food and pharmaceutical industries are leading the way as early adopters of the new norm of agile operational processes and other smart manufacturing processes.


The concept of distributed manufacturing has surfaced in previous periods and is gradually becoming a viable option for emerging manufacturing facilities and businesses. Distributed (decentralized) manufacturing is also gaining relevance due to the current deceleration of globalization and the accompanying trend of regionalization following the pandemic.

The trends for 2021 listed above will provide convenient conditions for the wider establishment of a distributed manufacturing model, in particular:

  • by increasing transparency in operational and business processes
  • by providing a more agile IT infrastructure based on hybrid clouds
  • by facilitating remote cooperation between employees on-site and online
  • by creating a more organic and direct connection between the supply chain and shop floors
  • by increasing intelligent automation of manufacturing, logistics, and maintenance processes

The model of distributed manufacturing as a type of localized (decentralized) production relies on agile manufacturing processes, which allow the delivery of serially customized products according to the customers’ individual preferences.

The purpose of distributed manufacturing is to establish smaller factories, optimized assembly shop floors, and production finalization workshops in several locations (clusters) as close as possible to customers, and thus gain the opportunity to deliver products following the D2C "direct-to-consumer" distribution model.

This distribution strategy - from the manufacturer to the customer – is expected to grow in the forthcoming period. The D2C distribution is projected to have a 19.2% upsurge in 2021, and the consequences of the COVID-19 pandemic are likely to boost this trend. This is just one of the reasons why the concept of distributed manufacturing may be a suitable option not solely for emerging manufacturing startups in the near future.

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