The role of automation in the future of manufacturing

The idea of ​​autonomous operations for manufacturing facilities has been on the agenda for several decades but, with the maturation of Industry 4.0 technologies, what was once an ambitious ideology has become very tangible, especially more than companies develop post-pandemic recovery strategies. In this article, The Manufacturer interviews Uwe Kueppers, Manager Consulting Services at Kalypso (a Rockwell Automation company) and Chairman of the EMEA Board of Directors of MESA.

How has the emergence of digital technologies accelerated the adoption of automation?

Rapidly growing digital technologies have made it easier and more widespread for businesses to adopt automation than ever before. For example, the move from LAN and Wi-Fi to 5G enables a greater variety of data exchange and connectivity capabilities for different devices and applications, which in turn enables rapid data access and automation. processes for different requirements within manufacturing.

The digital thread is the continuous flow of data that connects business processes, systems, products, and equipment across the value chain to drive business growth, operational excellence, and innovation. risk mitigation. To enable the digital thread, digital technology, such as equipment such as 3D printers, as well as state-of-the-art equipment and digital consumer products are needed. Automation provides data and its context for each process and equipment. Automation has therefore become a growing demand.

What impact has the COVID pandemic had on automation adoption?

COVID has accelerated the adoption of automation in many businesses as it has led to:

  • The rise of remote work. With fewer people allowed in the factory, expertise had to be provided remotely. The ability to access, support and control equipment remotely in collaboration with people on site has also become essential.
  • More flexible manufacturing. Companies needed to develop processes to react to things like disruptions, unforeseen stresses, supply chain issues, and product changes. This requires rapid reaction involving the use of digital thread strategy and seamless automated process integration.
  • Change in B2C behavior: Consumers and customers have rapidly changed their B2C behavior in favor of direct ordering and delivery models. Organizations needed to understand new customer behavior and react faster to gain market advantage and a larger customer base.

In summary, during the pandemic, companies quickly identified where their processes were broken and where systems and seamless data flow were unavailable. This has led to an increased demand for investment in automation to ensure business continuity or even just to survive as a business.

How critical is data to the successful deployment of automation technology?

Data management is one of the most important components of a successful deployment of automation technology. Validating all master data throughout the entire product life cycle requires a clear structure and a transparent data flow throughout the process, as more and more digital devices will create data and that data will need to be aligned throughout the different processes, applications and equipment.

The diagram below shows the many different data sources that need to be seamlessly integrated to ensure a validated quality data set.

What is the key to automation for post-pandemic recovery strategies?

Automation has empowered many businesses based on the constraints imposed during the pandemic as described above and will enable them to continue after the pandemic as new potential has been recognized and enables businesses to now take the next step as a control tower strategy and moving towards the ambition of becoming a stand-alone factory.

The road to autonomy is not fast. This requires a structured and time-planned approach. The key elements of an autonomous factory are:

  • Automation of manufacturing processes and equipment securing an automated function of equipment and processes with little or no interaction between people and the operator and obtaining all relevant data and information for further other automation activities, e.g. analytics, continuous improvement and business intelligence
  • Using advanced analytics and machine learning algorithms to enable prediction of unintended outcomes and then prescription of solutions through open or closed loop control.
  • Organizational Change Management (OCM) …Organizations need a holistic approach that leverages digital technology, revises processes, and facilitates the creation of new business models with customers. So the implementation of automation and the digital thread could change processes and the way people work. Therefore, it is necessary to understand what will change for people and what will be the benefits for them and for the organization. Defining people readiness and ensuring smooth adoption and transparent communication and training of people are just a few aspects of the change management approach. Leadership commitment and achievement of expected value along with program governance model, primary user-centric design and a change agent strategy are also an important part of CMO.

A stand-alone factory allows manufacturers more flexibility in local production, supply chain, and regional go-to-market strategies. By creating autonomous and automated manufacturing solutions, it is possible to significantly reduce the labor cost element in manufacturing, allowing higher labor cost regions to bring manufacturing back to the House. This is extremely timely given most countries’ desire to use manufacturing as part of their post-pandemic recovery strategy.

Are more manufacturers reaping the benefits of automation?

Many companies have seen high-value benefits by using the automation layer and moving to a predictive and prescriptive (AI/ML) controlled environment where part of the manufacturing process is self-optimized and regulated in open or closed loop Machine Learning Control (MLC).

Manually identifying bottlenecks consistently is time consuming and difficult. A strong appeal of automation for factories is the digitization of a company’s continuous improvement process and the clear definition of bottlenecks and their influence on productivity. Digitizing every action and tracking progress and directly measuring its results along with immediate impact and feedback to the operation enables companies to turn data into vital information. Automation also helps digitize a company’s continuous improvement (CI) strategy and enables direct feedback from CI to operations on the time and value that can be achieved by the clearly defined task and action identified and digitized of the CI process.

Are there manufacturers where automation would still be prohibitively expensive?

Automation initiatives are on a cost scale and often do not require large investments in new hardware. Most manufacturers can quickly realize benefits from data or software or projects at relatively low cost.

Can you explain the digital thread as the foundation of the autonomous factory?

The idea of ​​autonomous operations for manufacturing facilities has been on the agenda for several decades, but with the maturation of Industry 4.0 technologies, it is within reach of many organizations.

There are two foundations on the path to autonomy: digital wire and legacy automation. The digital thread creates a closed loop between the physical and digital worlds, transforming the way products are designed, engineered, manufactured and serviced. It aims to create simple universal access to data by tracking a single set of related data as it traverses various business processes, equipment, and functions.

Establishing the autonomous digital ecosystem will require customers, customers, and supply chain partners to have well-managed automated manufacturing (physical) and business (process) systems in place. Only by doing this can a company evolve to a state where the integrated ecosystem can begin to function. in an autonomous way.

With much of this technology already available, autonomy can be structured into five levels:

  • Level 0 – No operator assistance system. The operator is fully responsible and performs all tasks to operate the manufacturing equipment.
  • Level 1 – The system can perform equipment operation task. The operator can delegate an individual task to the system.
  • Level 2 – The system can perform several equipment operation tasks. The operator can delegate several tasks but must constantly monitor the system.
  • Level 3 – The system can operate autonomously on certain defined routines. The operator can divert attention from the equipment but must always be prepared to take full control.
  • Level 4 – The system can perform all equipment operation tasks. The operator can transfer full control to the system but can take control at any time if desired.
  • Level 5 – The system controls the equipment autonomously in all conditions – no operator is needed.

Thus, understanding the maturity of each business and its process and automation layer helps define a clear value baseline strategy and roadmap that allows management to communicate and secure the required change management and get faster results.

At Kalypso, a Rockwell Automation company, we are focused on digital transformation of the value chain, from product to factory to end user. It means leveraging digital technologies and capabilities to fundamentally change the way companies discover, create, manufacture and sell new products. We help our customers accelerate digital transformation with the digital thread and accompany them on their journey to an autonomous factory.

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