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Shifting Industry 4.0 into higher gear

Nurdianah Md Nur
Nurdianah Md Nur • 12 min read
Shifting Industry 4.0 into higher gear
Industry 4.0 is crucial in helping regional manufacturers secure their future and advance economically. Photo: Shutterstock
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According to the World Bank, manufacturing is a crucial pil­lar of the global economy, con­tributing approximately 17% to the global GDP. Due to its interconnectedness with various industries, the manufacturing sector generates significant economic multiplier effects.

Industry 4.0 is crucial for manufacturers to secure their future and contribute to economic progress. Also known as smart manufacturing, it merges the physical and digital realms by utilising technol­ogies like cloud computing, automation solutions, AI and the Internet of Things (IoT) to build interconnected systems. This gives manufacturers real-time data and advanced analytics, enabling quick, informed decisions and fostering highly efficient and flexible operations.

“Manufacturers in Asia Pacific (Apac) are looking at transforming their business with Industry 4.0 to optimise their operations and reduce costs. But their goal is not about cutting manpower. Instead, the focus is on empowering workers to be more productive as well as increase the efficiency and accuracy of their processes through the use of automation, AI [and other technologies related to Industry 4.0],” Peter Moore, senior vice president and head of enterprise cloud for Asia Pacific and Japan at tech giant SAP tells DigitalEdge.

Still, the adoption of Industry 4.0 varies throughout the region, influenced by factors such as infrastructure, logis­tics and supply chain systems, digital engineering abilities, talent, technology accessibility, and regulatory backing, says Vivid Gong, director analyst at Gartner.

“Advanced economies like Japan, Korea and Singapore are at the forefront of adoption due to their developed infra­structure, strong manufacturing sectors, and government initiatives. They’re already implementing technologies like IoT, AI and robotics in their manufacturing processes to improve efficiency and competitiveness. Countries like Thailand, Malaysia, Indonesia, and Vi­etnam are still making progress in smart manufacturing,” he adds.

Legacy systems running silos also prevent manufacturers from accelerat­ing their Industry 4.0 journey. “Many Apac manufacturers still rely on legacy on-premises applications. While mod­ernising these systems is imperative, part of that is also about removing silos. Disconnected ecosystems — such as fragmented tools, applications, and data — hinder a manufacturer’s ability to focus on strategic initiatives as more time is spent on maintenance instead of innovation,” says David Irecki, director of solutions consulting for Asia Pacific and Japan at Boomi, a cloud-based integration platform as a service (iPaaS) provider.

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He continues: “Factories [will also] deploy more production machines, wire­less connectivity, and sensors to oversee production lines and execute decisions autonomously [in the future]. So, ensuring these systems can converse with each other will be key to efficient output… [and for better] inventory management, delivery tracking transparency and co­ordination.”

Building blocks

Cloud computing is fundamental in enabling manufacturers to accelerate their Industry 4.0 journey. Moore explains: “Cloud adoption in Apac’s manufacturing industry is now further forward than years ago. So, manufacturers can use advanced technologies like AI and IoT to create digital twins (which are vir­tual replicas of a physical object or sys­tem to simulate and measure a process) and connected warehouses that can help automate the factory floor, refine manufacturing processes, better manage ener­gy consumption to reduce carbon emis­sions and more.”

See also: Fighting climate change with passive building design and digital construction technology

Although manufacturing companies globally see the need to invest in Industry 4.0 to improve their supply chain resiliency, two-thirds are stuck at the piloting stage, according to a 2023 SAP-commissioned global supply chain survey.

To help manufacturers embrace Industry 4.0 at scale, SAP offers solutions that can transform end-to-end operations — from the core systems, back-office IT, supply chain and front office for customer engagement. The solution portfolio consists of SAP S/4HANA as the business backbone, integrated with the SAP Business Technology Platform, with cloud business applications that extend the core with innovative Industry 4.0 scenarios and connectivity to devices in the factory.


We’re helping manufacturing customers in four key areas, namely en­abling intelligent products, intelligent factories and logistics, intelligent assets and empowering people.

Peter Moore, SVP and head of enterprise cloud, Asia Pacific and Japan, SAP


He adds that intelligent products are designed to meet customer needs. In discrete manufacturing, these products can share usage information through built-in sensors, providing real-time data on performance. By monitoring products during use, manufacturers can adopt a new business model to own and maintain the asset with service agreements and charge customers based on usage, uptime or other measurable metrics.

As for intelligent factories, SAP enables manufacturers to utilise real-time data and AI for autonomous and flexi­ble operations, enhancing efficiency. It also aids manufacturers in establishing uniformity and smart features across their global factories, granting them predictive and prescriptive abilities to optimise production.

For example, Smart Press Shop, a collaboration between Porsche and Schuler, employs the SAP Digital Manufacturing Cloud solution and the SAP S/4HANA Cloud software to automate tool setup when new orders for automotive body parts are in line for production. This quick product line configuration without manual interference enables Smart Press Shop to produce small component batches more efficiently than traditional plants.

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Smart factories depend on the high operational performance of their machines and equipment. These intelligent assets are integrated into every process and undergo dynamic maintenance. They can implement predictive maintenance strategies using IoT sensor data, predic­tive analytics, simulation, and machine learning. This automatically triggers timely maintenance suggestions, reducing the risk of unnecessary downtime and ensuring a robust supply chain.

Moreover, empowering employees with the right tools and timely, accurate information is crucial to ensure effective task performance. By integrating corporate data with live sensor data (such as usage data from assets) for machine learning analysis, operators can minimise delays, respond faster and swiftly identify root causes.

The need for integration

Data must be highly available, accurate and actionable for Industry 4.0 to deliver value. “However, organisations often have a myriad of random connectors and a variety of applications that lead to a complex and bloated tech stack. Business­es, therefore, need to frame and prioritise digital objectives, or they will struggle to create valuable, frictionless experiences for stakeholders. Many Apac manufacturers also have blind spots when it comes to data, which hinders their ability to identify what they are integrat­ing and if it is, in fact, the right data,” says Irecki.

Manufacturers can overcome those challenges by using an integration plat­form to bridge those disparate systems and give manufacturers real-time visibility and transparency into their operations. This can be beneficial in many ways, including spotting production errors and promptly informing suppliers.

An integration platform, Irecki adds, enables automation to result in increased productivity, too. “Organisations may integrate their back-office systems with the supply chain, enabling seamless invoice order processing interconnected with sensors and IoT devices. Moreover, bringing together disparate systems will make data more accessible. This, in turn, enables democratisation of integration and process automation, which empowers users to innovate and create value for the business like never before.”

Global eyewear company EssilorLux­ottica, for example, implemented Boomi’s iPaaS to transform and speed up order processing significantly. Since the platform enabled EssilorLuxottica to simplify and easily integrate internal applications and customer orders from various channels in real-time, the company increased its operational efficiency by four-fold. Boomi’s round-the-clock support also enabled EssilorLuxottica to identify and remedy performance degradation factors, ultimately processing orders from end to end in 30 seconds.

How generative AI can help

A robust IT foundation facilitates the adoption of new technologies, such as gener­ative AI, for Apac manufacturers. Gong suggests that manufacturing companies can utilise generative AI to enhance op­erational efficiency by leveraging it for:

  • Product innovation, where genera­tive AI can suggest alternatives to in­gredients, raw materials and packing based on user sentiment and aggre­gating trends and shopping patterns.
  • Ensuring operations uptime by lever­aging generative AI to continuously diagnose, order parts, complete pro­grammable maintenance, and sched­ule the recommended service needs for zero unplanned downtime.
  • Improved time to market by using gen­erative AI to explore manufactur­ing-ready outcomes earlier in the development process and design, op­timised for cost, materials and man­ufacturing technique.

Tech companies increasingly provide generative AI solutions to aid manufacturers in embracing this trend. SAP has integrated a generative AI copilot named Joule across its entire cloud enterprise lineup to provide proactive, context-based insights. Employees can ask Joule questions or present issues in everyday language and obtain intelligent responses from pertinent business data across SAP and third-party sources.

A manufacturer can ask Joule to analyse the company’s sales performance. Joule can pinpoint underperforming regions, link to additional datasets highlighting supply chain problems, and automatically connect to the supply chain system to propose potential solutions for the manufacturer to consider.

“[We believe] generative AI can make users more productive. But [we also understand the risks of AI, so we] have guiding principles wherein AI needs to be relevant, reliable and responsible by design. Our global development teams focus on large language models that focus on enterprise resource planning [which our solutions fall under] so that Joule can understand business processes and provide context-aware answers. We also ensure the content generated from generative AI is governed and can be trusted. That way, users can confidently rely on that content/data to make decisions and drive business growth,” says Moore.

Boomi recently introduced Boomi GPT, leveraging generative AI to provide user-friendly, conversational interactions on the company’s platform.


Boomi GPT could be used to rapidly prototype integra­tions and automation for the factory floor, even by citizen developers (who may not have coding or technical skills), further democratising innovation and accelerating business outcomes.

David Irecki, director of solutions consulting, Asia Pacific and Japan, Boomi


Boomi GPT is a component of the Boomi AI suite. It utilises the knowledge derived from the metadata, patterns, and best practices of the 200 million integrations conducted by Boomi’s 20,000 customers to train its AI engine. “Collecting this anonymised data over time allows us to see emergent patterns of how customers use the platform, connect endpoints, and transform their data. This ensures high-quality integrations across various business processes and applications, such as data management, customer experience optimisation, or supply chain processes. Boomi AI also controls model drift (or the degradation of the model’s performance) through recalibration, as we introduce new features into our data sets and retrain our models based on those particular features.”

He further explains that Boomi’s AI algorithms are trained to prevent biases, follow ethical best practices, and meet regulatory standards. Regarding privacy, Boomi AI does not collect any data passing through customer integrations and data services. “We are only concerned with the anonymised metadata we create about how customers design their workflows, integrations, and automation. Customer privacy is preserved as we do not collect the data flowing through customer pipes. Instead, we are focusing only on our own rich set of metadata from our data mod­els. Additionally, customers have control over the placement of their deployed runtime engines, which empowers them to preserve the security of the data they possess,” adds Irecki.

AR in manufacturing

Adopting augmented reality (AR) can also help manufacturers accelerate their shift towards Industry 4.0. For instance, inte­grating TeamViewer Frontline, an AR plat­form, with SAP’s Digital Manufacturing solution allows for hands-free work. En­gineers and production line workers will be able to view all relevant information displayed in the workers’ field of view, resulting in fewer errors, less downtime, increased safety, and faster onboarding.

“[The good news is that] manufacturers in Apac are further along in this journey than in some other regions. Given the importance of the industry to the region, manufacturers are always receptive to inno­vations like AR/the industrial metaverse to stay competitive and improve operational performance. They can also leapfrog as [they are held back by] fewer legacy IT issues,” says Peter Turner, chief commercial officer of TeamViewer, a connectivity and workplace digitalisation solutions provider.

The Hyundai Motor Group Innovation Center in Singapore (HMGICS) is among those leveraging TeamViewer Frontline to digitalise its manufacturing processes. Turner adds: “TeamViewer Frontline will be used in various areas across production automation, such as product inspection, in-factory logistics, facility maintenance, and worker training. This will help Hyundai develop an intelligent manufacturing plat­form and enhance productivity, accuracy, and worker safety in a smart factory.”

When asked how manufacturers can successfully implement and benefit from AR, Turner first highlights the need to engage employees to implement the technology as early as possible. They should emphasise that AR will augment — instead of replace — the workforce and address concerns around the use of the technology before deploying the technology and redesigning workflows accordingly. This will help employees to be more willing to embrace AR.

He also advises manufacturers to ensure the AR solution can integrate seamlessly into existing IT environments.


When an AR solution is integrated into existing infrastructure, data can be fed directly into the AR-based workflows shown to the worker. This creates a real, holistic digital transformation of several business units simultaneously. [Additionally,] manufacturers should select an AR software solution that is device agnostic and flexible enough to fit the user and the process.

Peter Turner, chief commercial officer, TeamViewer


Moving towards hyperautomation

Gartner’s Gong suggests that manufacturers increasingly consider hyperautoma­tion to modernise their production processes, technologies and culture.


Over the next five years, manufacturing processes and activities are expected to shift increasingly toward hyperautomation to fulfil smart factory initiatives such as autonomous production scheduling and end-to-end order processing.

Vivid Gong, director analyst, Gartner


This is why Gartner forecasts that configuration life cycle management will transform 40% of manufacturers by 2026, reducing the customer-specific engineering required to deliver products. “Manufacturers are striving to maximise market coverage and customer engage­ment with products that take optimal advantage of the R&D investments they make,” says Gong.

He adds that digital design-to-produc­tion simulation will be another growing trend among manufacturers. “Gartner predicts that by 2025, spending on de­sign-to-production simulation technolo­gies will increase 30% from 2022. This eliminates iterations of physical prototype testing that can be enormously expensive.

“These are just a few examples of the many trends that will impact the manufacturing industry but will have a significant impact on optimising processes, digitalising products and making the best of limited resources.”

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