Next steps for digital transformation for manufacturers

Digital Transformation Insights

• Digital transformation drivers will remain much the same within the process and manufacturing industries.
• The latest software platforms will unify people, data and systems to drive improved operational performance and plant efficiency through automated workflows, advanced analytics and enhanced decision support.
• Ethernet and removing data barriers will also improve digital transformation.

Julian Annison, digital transformation director at Emerson, believes the main drivers of digital transformation – such as achieving improved energy and emissions management, enhancing safety and increasing operational reliability – will remain much the same within the process and manufacturing industries. “There always needed to be a business purpose behind digitalization and that is still the case,” he said. “What is changing, however, is that organizations are now expected to achieve these business improvements while also having to meet tough environmental sustainability and decarbonization targets – both in the short term and up to 2050.”

Annison went on to point out that the increasing pressure and expectation from stakeholders has created a step-change in the way digital transformation is being perceived and is accelerating the need to not only implement the latest digital technologies but also to adapt work practices. “Whereas digital transformation was once merely regarded as a desirable objective, with organisations perhaps willing to trial small pilot projects, it is now often viewed as being fundamental to survival, with the need for much broader implementation acknowledged,” he said.

According to Annison, meeting environmental sustainability targets in the short term, up to 2030, is a challenge that can be tackled by implementing digital technologies that are already available. “Many plants have been designed to run with the minimum viable automation, so introducing digital solutions designed to improve safety and reliability, optimize production and meet sustainability targets is quickly achievable. However, meeting environmental sustainability targets up to 2040 or even 2050 will require a significant increase in the rate of digital transformation and a complete change in mindset on how digital technology should be used.”

Offering an example, he pointed to electrification and carbon capture, utilization and storage (CCUS) projects which have a vital role to play in reducing emissions, and which require new levels of inter-company collaboration and technological interoperability to manage process and operational data. Another important way to help meet longer-term environmental sustainability targets is through the use of new assets that are no longer just built to run, but are instead autonomous-ready, with digital technologies and the concept of digital transformation built in from the very outset. This will then enable them to evolve and adapt to meet changing regulatory requirements over the coming decades.

“In recent years, many organizations have equipped their plants with digital technologies that enable them to create and collect vital data in areas such as equipment health and emissions,” continued Annison. “However, data is only beneficial when meaningful outcomes can be generated from it. Data management is therefore a fundamental requirement and the next step on the digital transformation journey of many companies is to put in place technologies that enable data to be collected from multiple sources, visualized and analyzed, to create actionable insights.”

Ushering in a new era of data management capabilities, Annison believes the latest software platforms unify people, data and systems to drive improved operational performance and plant efficiency through automated workflows, advanced analytics and enhanced decision support. “These platforms provide a single location to manage, protect, and easily integrate operational technology (OT) data with information technology (IT) tools and cloud applications, enabling organizations to seamlessly connect people, processes and data. In this collaborative environment, operational data from disparate sources can be securely and efficiently collected, contextualized, and transformed into actionable information that can be delivered to all decision-makers via personalized content and dashboards.

“Organizations can also improve their business outcomes by moving from predictive to prescriptive maintenance practices,” continued Annison. “A variety of technologies can be used to provide predictive maintenance by monitoring the condition of plant assets and issuing an alert when there is an issue. However, this still requires manual intervention to carry out the recommended corrective action, which can sometimes lead to a break in the chain. The latest intelligent digital technologies can go a step further by enabling prescriptive maintenance. Because these technologies are capable of understanding problems and knowing what is causing them, they can not only identify and flag up issues but also automatically take actions to resolve them. This then creates a ‘closed loop’ application that can form part of an autonomous-ready plant.”

Welcome to the Metaverse

The process and manufacturing sectors are continuing to expand their digital footprint in order to improve operational efficiency, reduce waste, and enable intelligent control of sensors and actuators used at the edge of the factory floor. “As the full capabilities of the digital factory come to life, a new need has emerged to implement intelligence and seamless connectivity to ensure operational data is bi-directionally transferred between the edge equipment and the cloud,” points out Jeff DeAngelis, vice president Digital Factory, Industrial Automation at Analog Devices.

“In order to support the full capabilities of the digital factory performance, DeAngelis believes that the next big disruptor in industrial automation will be the ability to seamlessly move data between the Digital World (DW) and the Real World (RW) equipment on the factory floor. “This evolution of the digital factory allows the plant to self-regulate its performance and adjust its parameters to match the predicted performance of its digital twin to its RW performance at the edge on the factory floor. This future vision and capability to seamlessly move data between the DW and RW is sometimes referred to as the Industrial Metaverse.

It’s all about Ethernet

Benedikt Rauscher, head of global IoT projects and Industry 4.0 at Pepperl+Fuchs, believes that Ethernet will become the common basic communication technology for data from and to any field device in the process industry – in the same way that it already is in the manufacturing sector.

“Ethernet-APL is entering the market now. The first components are available and bring Ethernet-based protocols to the field level – in an intrinsically safe way,” he said. “The proven IT-technology is tailored for the specific needs of process plants such as intrinsic safety Ex-i and 2-wire installation for power and communication with terminal screws. In parallel, remote IO-systems are able to offer ways to connect conventional 4-20mA/HART devices to Ethernet infrastructures. The seamless usage of Ethernet in process automation is sure to speed up the digital transformation.”

Another consideration highlighted by Rauscher is the asset administration shell. “Its basic standardization is finalized and the concept is ready to use,” he said. “Now in nearly every automation domain, experts from all major manufacturers, academia and standardization bodies are working on definitions of specific submodels to open standardized ways to access properties, descriptions, documentations or live data from any asset – in a completely manufacturer-independent way. It will no longer be necessary to implement proprietary protocols or tools or to search for information manually,” continued Rauscher.

The concept of the asset administration shell will enable a completely digital information interchange from machine-to-machine what will simplify processes all over the life cycle of technical assets. “The submodel ‘digital nameplate,’ as a first example, demonstrates the potential of asset administration shells for the digital transformation. Identification data of assets from different manufacturers is provided digitally in a completely machine-readable format and can directly be used by digital services,” he concluded.

Barrier-free

According to Dr Frank Possel-Dölken, chief digital officer at Phoenix Contact, the next big disruptor will be seamless, barrier-free data logistics based on the International Data Transfer Agreement (IDTA) data container standards which drive marginal costs for new and additional data flows down towards zero.

“In the context of Industry 4.0, we often hear the statement that ‘data is the modern oil’. However, the ‘new oil boom’ has so far failed to materialise,” said Possel-Dölken. “Looking through economic statistics for evidence of the predicted efficiency / productivity potentials seems to be in vain.”

Explaining further, Possel-Dölken pointed out that the current processes for data transmission within one and between several companies are very time-consuming and costly; establishing new data connections requires more than generation costs of almost zero. “For data transmission from one system to another, the data needs to be unpacked, checked, reorganized, and packed again – in fact, before it is even sent and possibly also after it has been received. This process includes many activities and thus is extremely prone to errors. Consequently, comprehensive testing is necessary to ensure operability. This requires large amounts of time and money, and a lot of resources,” he said.

The situation in manufacturing companies plays a key role here: “Companies use a variety of IT systems to implement their business models. Large core applications are, for example, product lifecycle management (PLM), enterprise resource management (ERP) and customer relationship management (CRM) systems – digital heavyweights and highly integrated system environments! These are usually based on an individual and consistent central data model for which different functional modules are available that are often closely interlinked. Because a large number of business and work processes are managed end-to-end across several of these software applications, broad and complex interfaces usually exist between the core applications.

“Today, we find ourselves about 40 years after the beginning of the age of Computer-integrated Manufacturing (CIM) – and we are far from having seamless, barrier-free data logistics. In many cases, this fact currently prevents disruption in value creation processes and business models,” argues Possel-Dölken. “Developments in freight logistics – especially the introduction and establishment of the standardized ISO container – offer a good analogy for the current situation of data logistics. They should serve as an inspiration to us when it comes to Industry 4.0 – because they have allowed for the costs of global freight transportation to either decrease significantly or even become negligibly small. This holds true equally for the standardization of goods transport itself (in the form of containers, and load carriers) and for the many year’s process of developing the standards through the participation of various entities (such as ports, shipping companies, and freight forwarders).”

In conclusion, Possel-Dölken pointed out that close cooperation is needed between companies, organisations, industry associations, research & education, as well as politicians, to solve the current issues – all this on the basis of the successful evolution of the digital twin and the Asset Administration Shell.

Broadly classify the big digitalisation disruptors into two categories, Rajesh Ramachandran, chief digital officer at ABB Process Automation, believes that firstly it is the approach to digital transformation and realisation of business value and secondly it is the underlying digital technology disruptors. “In the first category, there are six key areas of major shifts in digital transformation space which are already disrupting, for the better, both process and manufacturing operations,” he said.

“The value realization of the Industrial Internet of Things (IIoT) and digital has drastically moved from technology and platforms to ‘Value Pillar applications.’ The six major value pillars we see taking prominence are sustainability, process performance management, asset performance management, operational excellence, OT/IT convergence security and extended automation and operational transformation.”

Deployment at scale

Ramachandran went on to explain that a major change already underway is deployment at scale – where pilots have matured to become programs. Organizations are realizing that digital solutions work best when deployed at scale either horizontally – as an example, implementing energy optimization across units, or vertically – implement many of the value pillars such as sustainability, asset performance management to a specific operational plant and then replicating this.

“Another change is the realization that benefits can be gained through the convergence of IIoT and industrial artificial intelligence (AI), particularly in the context of the scaled deployment. You need to bring the connected world, with AI and analytics, together to enable process and asset optimization. Where once these elements were seen as two different categories, they are, quite rightly, inextricable from one another,” continued Ramachandran.

The deployment of digital twin technology has become more value driven – today digital twins are being used for processes, not just assets. Operators are implementing process digital twins at scale – seeing value in this for optimizing not just 3D models of machinery or instrumentation.

“Greater adoption of hybrid cloud and edge computing is happening across industry – bringing the OT/IT integration closer to control systems and process automation technology,” said Ramachandran.

Finally, he believes that the biggest current change in the mindset around digital transformation is placing sustainability at the center of operations. “The top priority of digitalization has shifted from operational excellence to sustainability and asset performance management and it plays a key role in supporting energy management and optimization; emissions monitoring and controlling this predictably; preserving natural resources – for example, having solutions to monitor and control water usage; and optimizing processes so that we use less resources.”

So, what’s next on the underlying digital technology disruptors? According to Ramachandran it is the emergence of Edge AI – bringing more intelligence and Industrial AI to the edge to achieve and close loop optimisation and make autonomous operations a reality not just predictions and recommendations to human interpretations.

In addition, Ramachandran mentioned contextual data hubs that can unlock the value of industrial data. Today, more than 80% of data is not used for analytics but, through contextual data hubs, where the industrial domain context in the form of meta data, can be applied to the huge volume of IoT senior and operations data to achieve predictive and prescriptive analytics across the functions of process and the manufacturing sectors

“I believe we will soon enter virtual (VR) and augmented reality (AR) 2.0, where connected workers and technologies that enable this become a critical requirement and not simply a ‘nice to have’ part of modern industrial operations. Finally, 5G also has the potential to radically disrupt the industrial IoT landscape for the better with speed, connectivity and the power of remote operations transformed.”

– This originally appeared on Control Engineering Europe’s website. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

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