Digital transformation in manufacturing: a strategic guide — Part 1

Improve profitability and maximise return on capital across the operations and asset lifecyles to enhance competitiveness and cut the hype.

Changing market conditions and shifting technology landscapes put pressure on industrial businesses. Fluctuating commodity prices and oversupply contribute to capital expenditure challenges, while increased competition and consolidation force businesses to compress construction, engineering and design cycles. Environmental, quality and safety regulations are becoming ever more rigorous, and the workforce is evolving, as a tech-savvy, yet less experienced generation moves into roles once held by industry veterans, who are looking to pass on their knowledge and experience before leaving the workforce. Meanwhile, geopolitical uncertainties make it difficult for businesses to know where to invest. Market norms have been rewritten, affecting profitability in some segments and forging tremendous opportunity in others. In parallel to these societal and economic pressures, digital transformation is enabling flexible, agile solutions that companies can implement to overcome and prosper from these challenges.

Undergoing a digital transformation can enable companies to enhance their capabilities, increase their reach and maximise returns across their asset and operations value chains. Pivotal technologies like cloud computing, the industrial Internet of things (IIoT), artificial intelligence, and augmented and virtual reality, are transforming traditional industrial operations. These innovations represent unprecedented potential growth opportunities for businesses, but they also create new risks to the modern enterprise in the areas of cybersecurity and data privacy. These factors introduce new uncertainty into the industrial business environment.

Digital transformation

How can your business identify where to invest in such a rapidly evolving marketplace? What new opportunities does digital transformation offer your business? How can you manage your enterprise’s risk exposure? These questions can be overwhelming at first glance. But as shown in Figure 1, digital transformation is a key imperative for leading industrial businesses to master.

To be successful, your company needs to improve profitability and maximise return on capital across both assets and operations. In the context of capital asset lifecycle management this includes everything from how an asset is designed and engineered, to how it’s operated and maintained for optimum availability and uptime. At the same time, every minute of the operations lifecycle must be optimised to ensure that you stay ahead of the pack. From operations planning to real-time operations management, you need to balance production against the constraints of operational efficiency to maximise your return on asset investment.

Figure 1: A world in constant change. For a larger image click here.

Unique user experiences — not IIoT hype

We’ve all experienced the hype around the IIoT. Vendors in almost every industry claim their implementation of augmented and virtual reality (AR/VR), mobility, cloud and artificial intelligence will disrupt modern industry. But beyond all the hype and buzzwords, a radical change is occurring. That change is focused on delivering unique and exceptional user experiences, through digital technology. And it’s impacting almost every industry today.

The cable television industry has been significantly impacted by new competitors that leverage an almost entirely online distribution model. Encyclopaedias and newspapers have been replaced with digital content, distributed through mobile devices and social media. And Netflix and Amazon have replaced the neighbourhood video and book store. This change has been driven by digital challengers offering a better customer experience, enabled through transformed business models. To succeed in the digital economy, businesses must embrace and integrate this new technology. Digital transformation represents both a significant opportunity and a threat to every industrial enterprise.

Backed by the wealth of information the internet and digital technologies deliver, an unrestrainable shift in how businesses and industries function is occurring. From the plant floor to the C-suite, digital technology is helping to identify and execute on new competitive advantages. From the oil and gas industry to power generation, chemical production, food and beverage and consumer packaging, ongoing digital transformation is a key objective of the most successful businesses in the world.

To address the challenges and opportunities ahead, you need to find innovative ways to fuse digital technology with your existing people, processes and assets to ultimately drive new insights that:

• enable continual process improvement
• help your teams to manage rapid change
• deliver outstanding and differentiated customer experiences
• empower the workforce while creating an environment that attracts and develops top talent.

New data, new insights

Digital technology can help you to design, manufacture, deliver, support and maintain products faster, more efficiently and at lower costs. By bringing together previously inaccessible data streams, enhancing live visibility and analysis of your operations, and driving actionable insights based on better information, you can improve enterprise performance by:

• reducing unscheduled downtime
• improving regulatory compliance and safety
• integrating supply chain logistics with customer operations
• optimising maintenance strategies
• enhancing situational awareness throughout the enterprise
• reducing waste
• increasing overall equipment effectiveness (OEE).
   

Key to achieving these benefits is creating a seamless and continual stream of process and production data that is integrated with historic operations information and then contextualised into new insights on your overall enterprise. Data may already exist within the organisation stored in historian software or 3D models of plants and assets, but new digital tools can tap into these existing data stores and synthesise them with operational data. This process generates improved insights on how to maximise value creation across asset and operations lifecycles. Digital transformation empowers your people to take insightful and information-driven action to identify and solve problems at their source, before they compound into critical failure points that cascade into further problems.

For this amalgamation of knowledge to occur, digital tools and processes need to tap into both operations technology and information technology. In this way, the best technology can establish a bridge between the physical world where value creation takes place through production and delivery, and the digital world where enterprise planning and forecasting occur. Digital transformation is the process of building a digital value chain that drives closed-loop operational excellence and unique customer experiences throughout the enterprise.

The digital transformation journey

Digital transformation merges the latest innovative tools and processes with your in-house domain expertise. This enables not only the contextualisation of new and existing data but also delivers actionable insights and information. The organisation can then execute upon these new insights and close the loop towards continual process improvement. This takes time and often involves adopting many diverse technologies and processes to continually build momentum towards sustained operational excellence. For this to occur, every digital transformation journey needs to begin with the critical understanding that information and data have become a priceless and strategic asset to the enterprise.

The faster your team can collect, visualise and analyse data, the faster it is empowered to take insightful action that will benefit your operations and your customers. The overall tactical objective in achieving digital transformation is to create a real-time operational control loop that accurately and efficiently manages your enterprise, based on information and analytics.

Real-time operational information

Real-time operational information is used to understand what is happening in real time and enables the condition management of asset and operations lifecycles. For example, a dashboard displaying vibration frequency of a rotating asset such as a turbine during operation provides real-time understanding of the asset’s operational behaviour and state.

Historical operational information

Historical operational information helps you to understand what has happened in the past to create intelligence around the operational behaviour of assets. Through operational trends, display of KPIs and dashboards, you can create abstracted views of operational states. For example, a graph may be displayed on a dashboard showing the turbine’s past vibration frequency during operation.

This can be compared to the real-time vibration frequency, creating intelligence on the asset’s long-term operational trends.

Predictive analytics

Predictive analytics is used for what-if type modelling. Integrating up real-time and historical data enables your team to assess potential outcomes of operational states and behaviours, even accounting for tertiary variables. Deterministic or non-deterministic models can then be applied for open-loop simulation and predictive analytics. For example, given the turbine’s current maintenance state, you can now estimate how long it can run before it fails.

Prescriptive analytics

Prescriptive analytics describes what’s needed to optimise asset and operations lifecycles. Scenario-based guidance is created and delivered through learning elements and closed-loop algorithms to enable your team to calibrate planning and scheduling across the entire enterprise value chain. For example, using a unified supply chain model, scenario-based calculations can be used to optimise maintenance schedules and performance, minimising impact to your operations.

But to be effective, data and information must be captured and turned into actionable insight through three key processes:

1. Strategise: First, define key performance and scorecard indicators for the business. Then leverage digital technology to connect people, processes and assets in real time creating a complete digital value loop that collects and contextualises enterprise data.
2. Analyse: Convert raw data into actionable insight, using machine learning and advanced pattern recognition to drive predictive insights on process and operations optimisation so that your team can identify value ‘leaks’ and expose new market opportunities.
3. Maintain: Implement digital toolsets that reduce unscheduled downtime, optimise asset management and maintenance, increase overall equipment effectiveness and drive unique and better customer experiences.

The three steps above are helping leading companies to create so-called digital twins of enterprise operations and asset lifecycles. Using digital twins of operations processes, assets and even entire industrial plants is helping leading companies to model and optimise individual asset performance and even full-scale plant operations.

Lifecycle management through digital twins

A digital twin is a representation of the physical object in terms of data and information; like a pump, motor, turbine, even an entire industrial plant or a fleet of plants. Digital twins enable full lifecycle management of physical assets and processes. This starts with unified engineering, where process design, modelling and simulation are combined with overall plant design to create an integrated engineering environment and collaboration workflow.

Unified engineering facilitates the use of common engineering tools and streamlines the handover and revision process. Each plant can draw upon its own digital data ‘lake’ supported by a common artefact repository that spans integrated process design. These resources streamline engineering effort and make it easier for global teams to collaborate, thereby lowering the total cost of engineering. During the design phase, digital models allow your teams to analyse processes, equipment and operations through multiple simulations to define the optimum approach for safety, reliability and profitability. At the concept phase, your teams can analyse asset and process design alternatives swiftly, with continuous iteration through variable specifications. This allows your team to create integrated asset models of interacting but separate systems. Each iteration provides a more complete dataset, which in turn feeds into agile software development.

As assets are deployed and plants commissioned, the digital twin is continually updated with ongoing operational and process data such as maintenance and performance records and IIoT sensor information. During operational stages, variations from optimal process and asset design are captured during runtime, and the digital twin is automatically updated with this information. Knowing the current state of an asset, the digital model can use predictive learning technology to proactively identify potential asset failures before they occur and even suggest ways to prevent those failures. In other words, the digital twin can predict when its physical counterpart will break, well before that happens.

The digital twin also uses artificial intelligence with advanced process control, control strategy design and process optimisation. These tools incorporate necessary variations from process and asset design into the engineering asset or plant data, enabling a complete and efficient digital value loop and unified lifecycle management.

As you scale up to a digital twin of the enterprise operating model, inefficiencies and opportunities in your ongoing operations can be identified and executed upon in real time.

Bringing together feedstock data management, planning, scheduling and envelope optimisation activities, unified supply chain management provides increased granularity on your enterprise operations. The impact of uncertainties and data changes can be viewed, analysed and understood in real time, to generate realistic operations plans supported by feasible production schedules. Simulation of plant-wide activities helps your team to make informed decisions about everything from asset to enterprise level operations in real time.

Assets designed and shipped today typically have digital communication and connectivity built in. This means they can easily share the data they generate with other systems. For assets and facilities built and deployed before widespread digital connectivity, digital tools like smartphones, tablets and sensor technology can help to realise the benefits of digital twin technology quickly and affordably, while offering substantial improvement in workflow efficiency. With today’s tech-savvy workforce, it is quicker to train your operators. And new tools such as augmented and virtual reality technology further accelerate this process.

In Part 2

Part 2 of this article will describe the many technical benefits that a digital transformation can bring to your organisation, and introduce the steps to getting there.

*Matt Newton is Senior Technical Marketing Manager for AVEVA’s Asset Performance Management portfolio. With over 15 years’ experience planning, developing and implementing diverse batch and process automation applications, he has extensive experience designing and implementing IIoT and machine-to-machine applications from the network edge to the enterprise cloud.

Top image: ©stock.adobe.com/au/ipopba