The role of automation in the future of manufacturing

Posted on 25 May 2022 by The Manufacturer

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 aspirational ideology has become very tangible, especially as companies form post-pandemic recovery strategies. In this article, The Manufacturer speaks with Uwe Kueppers, Manager Consulting Services at Kalypso (a Rockwell Automation Company), and EMEA board chairman of MESA.

How has the emergence of digital technologies accelerated the adoption of automation?Uwe Kueppers, Manager Consulting Services at Kalypso

Fast-growing digital technologies have enabled companies to adopt automation more readily and broadly than ever before. For example, moving from LAN and Wi-Fi to 5G enables a broader variety of data exchange and connectivity capabilities for different devices and applications which in turn allows for fast data access and process automation for different requirements within manufacturing.

The digital thread is the seamless flow of data that connects business processes, systems, products and equipment across the value chain to deliver business growth, operational excellence and risk mitigation. To enable the digital thread, digital technology, like equipment such as 3D printers, as well as advanced equipment and digital products for consumers are required. Automation is the enable for having the data and it´s context available for each process and equipment, therefore automation has become a growing demand.

How has the COVID pandemic impacted the adoption of automation?

COVID has accelerated the adoption of automation in many companies because it has led to:

  • The rise of remote work. With fewer people allowed in the plant, expertise had to be provided remotely. The ability to access, support and control equipment remotely in collaboration with people on-site also became essential
  • More flexible production. Companies needed to develop processes to react to things such as disturbances, unforeseen constraints, supply chain issues and product changes. This requires a fast reaction involving utilising the digital thread strategy and a seamless automated integration of processes.
  • Change in B2C behaviour: Consumers and customers rapidly changed their B2C behaviour in favour of direct ordering and delivery models. Organisations had to understand the new customer behaviour and react faster to gain market advantage and an increased customer base.

In summary, during the pandemic companies quickly identified where their processes were broken and where systems and seamless data flow were not available. This has led to an increased demand to invest in automation to secure business continuity or even to simply survive as a company.

 

How key is data to the successful roll-out of automation technology?

Data management is one of the most important elements of a successful roll-out of automation technology. Validating all master data through the complete product lifecycle requires a clear structure and seamless data flow throughout the process as more and more digital devices will create data and that data will need to be aligned throughout the various processes, applications and equipment.

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

How key is automation to post-pandemic recovery strategies?

Automation has enabled a lot of companies based on the constrains given during the pandemic as described above and will enable them further post pandemic as new potential has been recognised and let companies now go to the next step like a control tower strategy and move towards the ambition of becoming an autonomous factory.

The road to autonomy is not a fast one. It requires a structured and planned approach over time. Key elements to an autonomous factory are as follows:

  • The automation of manufacturing processes and equipment securing an automated function of equipment and processes with minor or no interaction of people and operator and getting all relevant data and information for further automation activities e.g analyses, continuous improvements and business intelligent
  • Utilisation of advanced analytics and machine learning algorithms to enable prediction of unforeseen outcomes and then prescription of solutions through open or closed loop control.
  • Organisational Change Management (OCM) …Organisations need a comprehensive approach that leverages digital technology, overhauls processes and facilitates creating new business models with customers. So implementing automation and the digital thread might change processes and the way people work. Therefore, the understanding what will change for people and what will be the benefit for them and the organisation. Define the readiness of people and secure a smooth adoption and a transparent communication as well as training people are just some aspects of the change management approach. The engagement of the leadership and the expected value realisation as well as the program governance model, lead user centred design and a change agent strategy are also an important part of the OCM

An autonomous factory enables manufacturers to have more flexibility in local production, supply chain and regional go-to-market strategies. By creating autonomous and automated manufacturing solutions, it is possible to substantially reduce the labour cost element in manufacturing, allowing higher labour cost regions to bring manufacturing home. This is extremely opportune given the desire of most nations to use manufacturing as part of their post-pandemic recovery strategy.

Are more manufacturers switching on to the benefits of automation?

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

Manually identifying bottlenecks in a consistent way is time-consuming and difficult. A strong draw of automation for factories is the digitalisation of a company’s continuous improvement process and the clear definition of bottlenecks and its influence in productivity. The digitalisation of each action and the tracking of progress and direct measuring of its results as well as the immediate impact and feedback provided to the operation enables companies to turn data into vital insights.  Automation allows also to digitalise the continuous improvement (CI) strategy of a company and enables direct feedback from CI to operations how much time and value can be achieved by the clear defined task and action been identified and digitalised CI process.

Are there some manufactures where automation would still be cost prohibitive?

Automation initiatives are on a cost spectrum and often do not require large investment in new hardware. Most manufacturers can realise benefit quickly from data or software or projects at relatively low cost.

Can you explain the digital thread as a foundation for 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 for many organisations.

There are two bedrocks on the road to autonomy – the digital thread and existing automation. The digital thread creates a closed-loop between physical and digital worlds, transforming how products are designed, engineered, manufactured and serviced. It seeks to create simple universal access to data by following a single set of related data as it traverses the various business processes, equipment and functions.

Establishing the self-driving digital ecosystem will require clients, customers and supply chain partners to have established well-run automated manufacturing (physical) and business (process) systems.  Only by doing this can a company move towards a state where the integrated ecosystem can begin to run autonomously.

With a lot of this technology already available, the autonomy can be structured in five levels:

  • Level 0 – No operator assistance systems. The operator is fully responsible and carries out all tasks to run manufacturing equipment.
  • Level 1 – The system can perform one equipment operating task. The operator can delegate an individual task to the system.
  • Level 2 – The system can perform several equipment operating tasks. The operator can delegate multiple tasks but must permanently monitor the system.
  • Level 3 – The system can run autonomously on certain defined routines. The operator can turn attention away from the equipment but must always be ready to take full control.
  • Level 4 – The system can perform all equipment operating tasks. The operator can transfer complete control to the system but can take control at any time if desired.
  • Level 5 – The system autonomously controls the equipment under all conditions – no operator needed.

So understanding the maturity of each company and it process and automation layer enables to define a clear value base strategy and roadmap that allows the management to communicate and secure the required change management and achieve a fast track result.

At Kalypso, a Rockwell Automation company, we focus on digital transformation of the value chain, from the product to the plant to the end user. This means leveraging digital technologies and capabilities to fundamentally change the way companies discover, create, make and sell new products. We help our clients accelerate digital transformation with the digital thread and support them on their way to an autonomous factory.

By Sarah Seavey
Sarah Seavey