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The state of digital manufacturing in 2022

Dmitri Koteshov
Dmitri Koteshov

Senior Digital Content and PR executive

October 21, 2021


The state of digital manufacturing in 2022

The state of digital manufacturing in 2022

Dmitri Koteshov
Dmitri Koteshov

Senior Digital Content and PR executive

October 21, 2021


The state of digital manufacturing in 2022
In simple terms, digital manufacturing is the process of leveraging digital technologies to benefit operations at an industrial enterprise. The concept helps organizations of all sizes optimize the entire manufacturing process and services with data-driven computer systems.

The Difference and Key Features

Speaking of technology, it’s worth saying that digital manufacturing differs from automated production consisting of siloes connected by integrators. The main difference lies in seamless integration and standardized data formats throughout a product’s entire life cycle. 

Another important difference is the speed and convenience of work. Smart enterprises use flexible tooling solutions that are highly adaptable to meet various business needs. While all workers have tablets or smartphones connected to a unified information system, they can easily interact and manage internal processes. For instance, they can receive shift-daily tasks, see reports on their implementation, or communicate with other departments.

Let’s observe the key features of digital manufacturing, shall we?   

  • Manufacturing processes such as assembly, machining, casting, stamping, etc., are digitally simulated; 
  • Design errors are detected before goods go into production;
  • Quality is improved due to data transparency and real-time exchange between all participants in production chains. 

When talking about the biggest benefits of Industry 4.0, industry professionals indicate reduced time and costs associated with developing new products, lean manufacturing, less waste, and moderate energy consumption. What’s more, digitalization allows manufacturers to diversify their offerings with custom products available in small batches.

Cost of performance

Current Challenges

Nowadays, digital manufacturing and corresponding ecosystems are still at their formative stage in many countries worldwide. The most common issues on the path towards definitive adoption include insufficient project financing, outdated infrastructure, and the lack of qualified specialists. The latter point is especially painful as the sector suffers from a shortage of IT experts with industrial expertise. 

Another issue is that high-level executives can’t fully grasp the idea that the digital transition won’t happen overnight. Instead, the process of digitization requires a complex set of measures, time, and patience. More often than not, decision-makers neglect prototyping, modeling, and testing managerial hypotheses before making investments.

The thing is, when a company wastes time creating concepts and reports, instead of prototyping products and modeling business processes, one can’t expect good results. With that being said, let’s observe the most important pillars of digital manufacturing. 

Machine Data Collection

Industry 4.0 is all about creating a single information space so that all automated enterprise management systems and industrial equipment can quickly exchange information. This way, the key step towards the digital transformation of manufacturing is machine data collection. The use of MDC (Machine Data Collection) and MDA (Machine Data Acquisition) systems allows operators to collect data on production facilities (equipment, employee workplaces, service departments, etc.) for production management purposes.

Equipment Insight

Speaking of increasing production efficiency, manufacturers place big bets on the Industrial Internet of Things, or IIoT. Industry analytics expect that IIoT will help digitize the entire product chain, create intelligent manufacturing and significantly increase its efficiency.

The Industry 4.0 concept doesn’t imply that machines should operate without humans. Instead, it’s about people and machines interacting as a single organism. In this regard, MDC/MDA class systems allow improving modern production without significant investments, increase its efficiency and simultaneously solve many related problems. 

With machine data collection solutions, manufacturers have a reliable way of capturing and transforming their production data. They can also make precise data-based decisions, drive automation on their factory floors, and dominate the market with an unprecedented competitive advantage.

Digital Twin

A digital twin is a physical device's software analog that simulates a real object's internal processes, technical characteristics, and behavior under various conditions. Digital twin technology allows creating digital copies of market-ready objects and factory prototypes.

This technology is a real game-changer for the industry. As Chris O’Connor from IBM put it: “It's more than a blueprint, it's more than a schematic. It's a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on a factory floor, and much, much more”. Before launching a new production line or product, you can digitally prototype its work, calculate possible risks, and adjust the manufacturing process if necessary. For example, in the automotive industry, this technology significantly reduces the time of each stage of design and production.

The creation of digital twins is integral to introducing modern PLM technology (Product Lifecycle Management). In turn, both IIoT and PLM are crucial attributes of a smart factory. The technology's characteristic feature is forming and using a digital model of material flows. In other words, the technology is no longer a separate product but a production system. While the traditional industry largely depends on numerous full-scale, time-consuming, and costly tests, modern enterprises conduct tests using a digital twin and save both time and resources.

The digital twin of the product includes:

  • Geometric and structural model of the object;
  • A set of calculated data for parts, assemblies, and the product as a whole;
  • Mathematical models that describe all physical processes occurring in the product;
  • Information about the technological processes of manufacturing and assembly of individual elements and the product as a whole;
  • Product lifecycle management system.


As of today, it’s evident that the next five years will see widespread cloud expansion and further adoption by enterprises of all sizes. After all, artificial intelligence (and the use of AI systems will simplify the analysis of data stored in the cloud), 3D printing, sensor technology, and other technologies used at a smart factory correlate with the cloud. Therefore, cloud adoption is integral when speaking about the digital transformation of manufacturing businesses.

While it’s true that the migration process is expensive in itself, the report by Synergy Research Group claims that cloud spendings are up. These numbers are logical. Sure enough, you have to spend a little fortune, but the transition to the cloud helps industrial manufacturers economize without bid-budget investments in IT infrastructure, software, licenses, and high-paid employees. 

Fair enough, cloud migration challenges exist. Again, the biggest challenge is the lack of proper infrastructure. According to a report by Oracle, as much as 60% of businesses don’t have the proper environment to start innovating. However, the transition to the cloud shouldn’t be seen as a tribute to fancy trends. Instead, it is a market necessity for any organization that embarks on the path towards Industry 4.0. 

Cloud is omnipresent. For example, I mean big data processing solutions, model-oriented approaches, widespread use of cyber-physical systems that independently transmit information to the Internet of Things, and cyber security systems. 

Final Words

Digital manufacturing describes an industrial enterprise driven by processes that are centered around the use of digital solutions at every stage of the production chain. However, let’s face it: going fully digital requires money, effort, and, most importantly, expertise. No wonder that most enterprises resort to digital transformation consulting services to implement their strategy successfully. 

First of all, manufacturers need to realize the need for change and evaluate their digital maturity in collaboration with experts. Industrial companies must follow the global digitalization trend: nowadays, fast and flexible companies are right behind large competitors burdened by regulations and rules. Here at Akveo, we invite you to transform your business processes and reimagine production with Industry 4.0 technologies and Industrial Internet of Things (IIoT) consulting and development services. Contact us today to learn how we can bring connectivity to your enterprise and fulfill your clients’ requests faster.

Things you need to know about digital manufacturing in 2022.
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