The manufacturing industry has been the backbone of Singapore’s economy, and this is set to continue. Last year, the government announced that it plans to increase the manufacturing industry by 50% in the next decade so that the sector contributes to about a fifth of the economic output over the medium-term.
Achieving that calls for manufacturers in Singapore to look beyond cost competitiveness and digitally transform to deliver new innovations. Coupling that with changing consumer patterns and supply chain disruptions during the Covid-19 pandemic, most manufacturers are already exploring the use of various digital technologies to improve the flexibility, adaptability and resiliency of their operations.
Manufacturers that have started their transformation journey earlier are progressing to the next level of integrating their digitised processes, according to the 2022 edition of the Manufacturing Transformation Insights Report by the Singapore Economic Development Board (EDB) in partnership with the World Economic Forum.
HP Inc (HP) is one of the digitally mature companies that have digitalised its entire production line in its manufacturing plants in Singapore even before the pandemic. “[Our digital transformation] focuses on four areas of the fourth industrial revolution (4IR) technologies, each aimed at enabling us to move, sense, build and think better throughout the manufacturing lines,” Vivian Chua, MD of HP Singapore, tells DigitalEdge Singapore.
She explains that in terms of move, the company is leveraging Autonomous Intelligent Vehicles to move heavy goods across the factory floor. Collaborative robots are also being used for repetitive processes, such as tearing protective film off cartridge moulds before circuitry and rotating parts on the line to complete the assembling of ink cartridges.
To sense better, HP relies on Industrial IoT (IIoT) technologies. Chua says: “We have built a platform that connects and collects data, and dynamically visualise and manage factory performance in real-time. This is central to HP’s digital journey. Our teams have connected off-the-shelf analogue devices using a standardised data transportation protocol, so now we can collect essential data across all types of devices, digitising manual data entry, and eliminating paper usage by 90%.”
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She goes on to share that IIoT is also used to manage human traffic on HP’s factory floor. “[Our Project SafeEye solution] analyses real-time camera feed and video display using edge computing to determine if people within its line of sight are keeping safe social distances and trigger audio reminders if they fail to do so.”
HP is also embracing additive manufacturing through use of HP MultiJet Fusion 3D printers to add more flexibility in its operations and build better. By replacing original pallets for transportation on conveyor belts with 3D printed pallets and machine parts that are cheaper and faster to produce, HP saw improvements in the efficiency and productivity of its operators while avoiding costly downtime. To illustrate this, she explains: “The design of critical machine parts is streamlined, for example, from nine different parts to one, reducing its production time from five days to 24 hours.”
Chua adds that HP leverages advanced analytics and machine learning models too, to achieve the goal of thinking better. Real-time algorithms, for instance, are used to automatically detect and alert any machine problems and process the lines’ health issues. Meanwhile, predictive models are being used in place of traditional “destructive testing” (which is a testing method that analyses the point at which the product fails) to reduce waste and enable HP to meet unique product specifications more accurately. Additionally, machine learning helps diagnose and recommend the right setup for tools and manufacturing lines, reducing downtime, and increasing precision.
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By transforming its labour-intensive and reactive processes to highly digitised, automated, AI-driven processes, Chua says that the company managed to reduce its manufacturing costs by 20%, shorten issue resolution time by 90%, and improve productivity and quality by 70%.
Augmenting work with AR
With various 4IR technologies available today, it can be daunting for manufacturers – especially those not as digitally ready as HP – to decide which technology to experiment with or adopt for their digital transformation journey.
One technology that is gaining popularity is augmented reality (AR), which superimposes an image onto a user’s view of the real world. The technology is commonly used in games such as Pokémon Go and by retailers like Ikea to let customers use their phones to preview how a certain product looks like in their homes before they buy.
However, AR can also provide value to manufacturers, such as combatting staff shortage, which is a common issue for manufacturers in Asia.
When it’s difficult to find new qualified employees, using AR workflows and step-by-step instructions can help with the training of existing or less qualified people, and AR-based remote support can leverage experts’ knowledge from afar. This is extremely time-efficient and improves the manufacturer’s productivity.- Sojung Lee, president for Asia Pacific at TeamViewer
She continues: “In industrial contexts, AR solutions run on smart glasses and are seamlessly integrated with manufacturers’ ERP (enterprise resource planning) and backend systems. Use cases span from picking in warehouses to repair and maintenance work in field service to quality control, training and onboarding.”
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Coca-Cola Hellenic Bottling Company, for example, uses TeamViewer’s remote support solution Frontline xAssist to help on-site operators solve everyday technical problems on a production line. Through a shared camera stream and AR annotations, a remote colleague guides the on-site worker through complex processes and supports with expert knowledge. This has reduced downtime of production lines by up to 50%, Lee adds.
Digital twins
Digital twins is another area that manufacturers should look at. A digital twin is a virtual double of a product, machine, process or complete production facility. Since it contains data and simulation models relevant to the original, a digital twin can help optimise the maintenance of manufacturing utilities and reduce overall downtime.
[Manufacturers can use digital twins] to optimise, manage, and predict various failures and problems for their machines, production, and overall factory plants- Bas Kuper, senior vice president and managing director of Asia Pacific at Siemens Digital Industries Software.
Digital twins, he adds, can also enable virtual commissioning, wherein proposed changes and upgrades are tested in the simulated model of a manufacturing plant before they are implemented to the actual plant.
To fully benefit from digital twins, manufacturers need to provide digital twins with data from the entire value chain. “Following this is a chain of related considerations, like investing in parallel aggregation, consolidating data in shared repositories, and redesigning organisational structures. The cooperation of ecosystem partners and suppliers to collaborate dynamically is also necessary,” says Kuper.
Skills to support factory of the future
Realising a factory of the future – one that can address today’s and tomorrow’s challenges – requires more than just adopting 4IR technologies. Employees must have the right skill sets to support the transformation efforts too.
“Workforce transformation goes hand-in-hand with digital transformation. [This is why] we continuously invest into our workforce through a range of internal and external training initiatives to reskill employees in anticipation for skills they will need in future, and as needs evolve,” says Chua. She adds that some of the skills that will be key to manufacturers in future include data science, data analytics, and additive manufacturing.
Agreeing with her, Kuper says: “Manufacturers need to prioritise aligning the staffs’ digital skills to match the required proficiency for digital twins to fully benefit [from the technology].”
He goes on to share that there are three aspects to digital twins — product, production, and performance — and the skills required depend on the focus areas.
He explains: “Validation of product performance is crucial when digital twins are used to design new products efficiently. At the same time, a good understanding of manufacturing processes on shop floors to production lines are crucial for integrating digital twins into manufacturing and production planning.”
“When using digital twins for performance to capture, analyse, and act on operational data, skills needed include analysing and synthesising massive amounts of data from smart products and smart plants — which help companies gain insight into ways virtual models, product and system efficiency can be improved. Business-oriented digital twin experts could also come in handy when developing the company’s overall digital skills and domain knowledge.”
Faced with a fast-changing, volatile and dynamic global situation, manufacturers can no longer afford to delay digital transformation to remain competitive. “Manufacturers that are increasingly willing to invest in digital solutions [and skills will not only] solve today’s problems [but also] equip their businesses with a structural solution for tomorrow,” says Kuper.
Photo: HP Inc
