Uncertainty looms over the global economic landscape of the 21st century. With wide-ranging disruptions—from an unprecedented pandemic to the ongoing political conflict in Ukraine—already rippling through international supply chains, and a far-reaching recession on the horizon, manufacturers around the world are facing added pressures in their efforts to deliver reliable products into the hands of clients and consumers.
Almost three years after COVID-19 first hit headlines worldwide, delivery lead times for many products remain extremely long compared to pre-pandemic schedules; for some businesses, deliveries can’t be guaranteed at all if critical upstream parts, such as microchips and semiconductors, remain scarce from a shortage of raw materials.
In Singapore, the manufacturing industry accounted for an estimated 22 percent of the city-state’s total gross domestic product (GDP) in 2021, as reported by the Singapore Department of Statistics (DOS). With manufacturing being so integral to the nation’s economic output as well as that of its international trading partners, futureproofing the industry is vital.
“It is essential for Singapore’s manufacturing industry to become more agile and resilient in adapting to the challenges ahead so that we remain an important and relevant node in the global manufacturing supply chain,” explained Keng Hui Lim, Assistant Chief Executive of the Science and Engineering Research Council (SERC) at A*STAR. “The convergence of digitalisation and sustainability has also presented significant opportunities for Singapore-based companies to build new capabilities and position themselves for the future.”
To that end, A*STAR has worked closely with industry partners across the board to help create highly digitalised, interconnected, autonomous and sustainable manufacturing systems. With innovative efforts that range from integrated artificial intelligence (AI) and machine learning in production processes, to wireless networks of smart tools and devices on factory floors; and from product hyper-personalisation for dynamic consumer demands, to sustainability training for businesses; A*STAR is pushing the boundaries that define the future of manufacturing.
MERGING THE DIGITAL AND PHYSICAL
One immediate challenge for manufacturers remains: the supply issue. As shown by the COVID-19 pandemic, in today’s highly globalised economy, disruptions in a single logistical route can have far-reaching effects on consumers and producers. With air and sea travel schedules no longer as predictable as before, many businesses, be they large multinational corporations or small local enterprises, have felt the pinch of stock shortages for production lines.
“Businesses are finding it increasingly difficult to keep production going as lead time and availability of materials cannot be guaranteed,” said Puay Siew Tan, Research Division Director of the Digital Manufacturing Division (DMD) at the Singapore Institute of Manufacturing Technology (SIMTech). Shipping delays and sudden shortages mean that businesses face increasing production costs which could cascade down to consumers, Tan added.
Faced with these prospects, researchers at SIMTech have begun looking at ways of mitigating or even eliminating these uncertainties for businesses through digitalisation. The Model Factory @SIMTech is a platform that serves as both a testbed and co-creative training centre that helps A*STAR’s industry partners in Singapore kickstart the digital transition of their current manufacturing processes.
These transition efforts are part of the agency’s support for the nation’s larger goal of moving towards Industry 4.0—what experts describe as a new era of the Industrial Revolution, defined by a heavy emphasis on interconnectivity, automation, AI, machine learning and real-time data utilisation.
At the Model Factory @SIMTech, Tan and her team have used AI, machine learning and data analytics to create a suite of advanced manufacturing technologies, such as the Cyber-Physical Production System (CPPS), which connect computing elements with live factory environments. This allows them to autonomously ‘Sense, Think, Adapt and Respond’ to changes throughout the manufacturing process.
From there, SIMTech engineers developed the Manufacturing Control Tower™ (MCT™) platform, a cloud-enabled microservices platform to host those technologies. “The MCT™ concept is needed to enable seamless collaboration between the different applications. Through AI-enhanced algorithms and machine learning, they also provide users with real-time decision-making support,” said Tan.
For example, inventory management is a crucial element in the current age of just-in-time manufacturing. While there must be sufficient materials on hand for production to continue, excess stock is undesirable as this promotes inefficiencies that ultimately increase costs.
With the aid of the MCT™ and its technology suite, inventory stock can be measured, monitored and reported in real time to various departments such as purchasing and operations. Using AI-centric algorithms to guide policies, bottlenecks and disruptions can be identified and even predicted, with alternative recommendations where possible.
Armed with the relevant data and analyses, these teams are able to make swift decisions to immediately correct any detected issues and thus optimise production. This could mean the dynamic adjustment of materials purchasing, or the speed of onsite manufacturing processes according to material availability, to create more resilient and efficient factory floors.
Currently, a fully autonomous factory environment remains a far-future prospect due to cost and technical limitations, says Tan. However, she added that while building a fully autonomous system is difficult, SIMTech is already taking steps towards that goal. Other systems developed at the Model Factory @SIMTech have already been adopted by A*STAR partners from industries ranging from electronic appliances to aerospace engineering. To date, SIMTech has worked to implement over 1,600 digital systems into the manufacturing processes of various local and multinational companies.
In addition to one day achieving fully autonomous manufacturing, Tan said that the team also hopes to explore the concept of ‘Manufacturing 2.0’ through networked, urban microfactories, rather than single centralised ones to create a distributed value chain.
A WEB OF SMART MACHINES
For any manufacturing system, communication between departments is key to ensuring smooth operations. A rapid flow of information between client-facing teams, such as sales and customer service, and backend ones, such as purchasing and quality assurance, allows businesses to quickly adapt their production outputs to changes in demand and supply.
One new tool being used to enhance these communications is the Internet of Things (IoT). You may be familiar with IoT through ‘smart’ gadgets or appliances—speakers, air conditioning, lights, doorbells—that can, through online connections, ‘talk’ with each other to create a highly integrated home ecosystem, helping users monitor goings-on and automate tasks at home.
The same concept is also being brought into factories, connecting various sensors, machinery and tools to communicate and share data through highly secure, wireless communication networks. Called the Industrial Internet of Things (IIoT), such connectivity features are being explored by A*STAR to move Singapore’s manufacturing industry towards highly digitalised, agile and autonomous systems.
“IIoT is the fundamental enabler of an autonomous manufacturing system,” explains Sumei Sun, Deputy Executive Director (Research) and Head of the Communications and Networks Department at A*STAR’s Institute for Infocomm Research (I2R). “IIoT systems exploit real-time information from a range of sources to monitor, incorporate smart data analytics and AI for actionable real-time insights; and to control the operating conditions of its constituent systems within and between departments, as well as between [production] sites.”
An effective IIoT setup relies on collecting large amounts of timely data, processing it in real time, automating decisions and relaying instructions to actuators. Within closed-loop wireless networks at the Model Factory @SIMTech, SIMTech and I2R researchers collaborate on the design, testing and implementation of various IIoT subsystems—such as communications, data analytics, control and management, and cybersecurity—to allow the team to model their interplay and optimise their performance-cost balance.
“The solutions we’ve developed are integrated into an IIoT Edge Platform (IEP), which complies with standards set by the Industrial Internet Consortium (IIC) to ensure broad industry adoption,” said Sun. “The IEP supports multiple secure wired and wireless industrial communication protocols, edge AI computing, joint communication and computing co-optimisation as well as self-learning, self-adapting intelligence built in for optimal performance.”
Sun describes how various use cases for IIoT such as predictive maintenance, dynamic process scheduling, asset tracking, network anomaly detection and recovery have successfully been developed, validated and showcased to manufacturers keen to bring IIoT into their facilities.
“Many IIoT solutions and technologies we’ve developed have been deployed by our industry partners,” Sun said, citing examples such as wireless communications for smart cranes in a local large enterprise (LLE) company; real-time track-and-trace solutions for personnel and assets in a marine engineering company; advanced anomaly detectors for a multinational semiconductor producer; and automated cargo allocators for a shipping company.
With IIoT deployed more widely in future, businesses of various sizes could make full use of its potential to create a single integrated network of smart machines, leading to more robust and efficient production lines.
HYPER-PERSONALISING PRODUCT LINES
In an age of social media and viral marketing, microtrends in clothing, food and other fast-moving consumer goods (FMCG) fade in and out at a dizzying pace, creating a class of customers constantly seeking new products. For businesses, especially small and medium enterprises (SMEs), this volatility has been increasingly challenging to address.
At A*STAR’s Advanced Remanufacturing and Technology Centre (ARTC), a suite of advanced manufacturing technologies could transform the way established companies and growing SMEs in FMCG rapidly finetune and adapt products to suit consumer demands, opening the doors to hyper-personalisation.
Meet the ARTC’s Next Generation Hyper-Personalisation Line Programme (NGHPL). The programme focuses on developing various methods of finetuned product filling and order customisation through manufacturing plants or inhouse distribution centres equipped with digital connectivity capabilities.
Through smart filling and dispensing solutions, the NGHPL gives manufacturers the ability to adjust ingredient amounts and formulations in real time based on customer demands.
Flexible enough to accommodate a wide range of wet and dry products with low production volume, the NGHPL can also help prototype solutions in a controlled environment before implementing them in larger-scale manufacturing processes.
Since the NGHPL’s inception, the programme has initiated collaborations with many A*STAR industry partners, such as global consultants McKinsey & Company, to develop industrial processes that bring more personalized products to consumers.
“The NGHPL is an engine of support for test-bedding hyper-personalisation manufacturing technologies,” said Shan Qi, Digital Capability Centre Development Manager at McKinsey & Company. “Through NGHPL, we were exposed to new FMCG industry-applicable technologies such as laser surface treatments. We look forward to many years of future collaboration through the NGHPL platform.”
The programme aims to develop more collaborations with industry partners and deploy new concepts commercially. “With continuous trials and industry projects, we can expect more agile and robust manufacturing lines that can respond swiftly to ever-evolving customer demands,” said ARTC representatives.
TOWARDS GREENER FACTORIES
Robustness and efficiency aren’t the only features of future manufacturing—with the increasing impacts of resource use on the environment, factory operations must also be sustainable. To that end, SIMTech has established the Net Zero Manufacturing initiative, a more holistic and sustainable approach to manufacturing that puts minimising greenhouse gas emissions (GHG) at the forefront of the process.
“In the manufacturing context, a company is said to have achieved ‘net zero manufacturing’ when all GHG emissions along its entire value chain have been mitigated,” explained Jonathan S.C. Low, Coordinating Director (Research) at SIMTech.
According to Low, companies can work towards that goal by implementing various measures to reduce direct and indirect GHG emissions. Such measures include deploying technologies that support carbon capture, utilisation and storage (CCUS) and the electrification of currently fossil fuel-dependent processes; increasing the energy efficiency of factory operations; and reducing resource waste through sourcing, design, low-carbon materials and a circular economy.
Digitalisation and autonomous systems would also be key enablers for sustainable factories as AI would “enable smarter optimisation of their systems to reduce energy, water and material consumption, as well as waste generation,” said Low.
To date, SIMTech collaborations with industry partners have led to the implementation of such measures in real manufacturing lines. One partnership saw improvements in energy efficiency at wooden pallet manufacturing company LHT Holdings through the deployment of SIMTech’s Energy Efficiency Monitoring and Analysis System E²MAS and the design of reusable pallets that incorporated recycled materials.
SIMTech has also worked with Alpha Biofuels, a company that converts waste cooking oil into biodiesel, to improve their resource efficiency and circularity through Waste-to-Resource Reverse Logistics, which help optimize used cooking oil collection by the company.
Apart from Net Zero Manufacturing, SIMTech also supports businesses on all steps towards sustainability through Green Compass, a sustainability and strategic roadmapping tool which SIMTech provides training in.
“A company’s sustainability journey starts with the need to understand what sustainability means for them, where they are at in the journey, where they need to go and what they need to do to get there,” said Low. “Green Compass can help companies understand their sustainability readiness and then build a suitable roadmap that gets them to their destination.”
According to Low, once a company gets started with Green Compass, they can then be introduced to science-based tools such as Life Cycle Assessment (LCA) to measure and track their environmental impacts, as well as Life Cycle Costing (LCC) to assess the cost-benefits of mitigation measures they might use to address those issues.
“Based on our experience working with the manufacturing industry over the past 15 years, the most effective approach to help companies adopt new tools and technologies is to couple it with knowledge transfer, or in other words, training,” Low said, adding that Green Compass and LCA training are available to companies through government-subsidised courses under SkillsFuture Singapore (SSG).
A FUTURE OF RESILIENCE
The last industrial revolution saw the automation of factory processes, reducing the manual labour required; the next will focus on connecting those processes with AI and big data, providing manufacturers with new insights and adaptive solutions to face global uncertainties.
Through collaborations with industry stakeholders, A*STAR will continue to support the nation’s efforts to futureproof its factories, enabling them to rise to the challenges of the globalised century ahead.
