Shaping the future of manufacturing in 2024

The manufacturing industry is undergoing a major transformation as it adapts to the challenges and opportunities of the post-pandemic world. Some of the key trends that will shape the future of manufacturing in 2024 are digital transformation, sustainability, supply chain resilience, and human-AI collaboration. These trends will enable manufacturers to enhance their efficiency, quality, innovation, and competitiveness in the global market. In this report, International Metalworking News for Asia presents views from industry experts in different fields, we asked them how these trends are impacting the manufacturing sector and what strategies manufacturers can adopt to thrive in 2024 and beyond.

Manny Valenza, Sales Cluster Manager for South East Asia at metal cutting specialist, Sandvik Coromant.

Firstly, the shift from internal combustion engines to electric vehicles (EVs) is taking prominence in South East Asia. However, in 2022, Chinese automakers dominated South East Asia's fast-growing electric vehicle market by selling three out of every four EVs in the first quarter. To ensure more prominence for local manufacturers, Thailand has offered incentives to consumers and subsidies to automakers to build more EVs locally. That has attracted a wave of investment by Chinese carmakers in local manufacturing, resulting in over US$1 billion of investment in setting up production facilities in Thailand. To cope with this influx, metalworking companies will be vital in suppling parts for electric vehicle production, specifically in Thailand. Additionally, focus remains on making parts out of lighter materials, not just for automotive, but also for aerospace. In the aerospace industry there is persistent drive to lower air travel’s carbon footprint, which leans on making planes lighter in order to save on fuel. For instance, titanium is 30% stronger than steel and almost 50% lighter. However, machining titanium poses its own set of challenges due to its high hardness and low thermal conductivity. To overcome these machining challenges and contribute towards making planes lighter, manufacturers must make the most of the latest developments in precision cutting tools.

Market demands change and the ability to adapt your production to current and future demands in a flexible way is crucial for surviving in today’s economy. The most recent cases of 2023 include the energy crisis, global competition and changing customer demands to meet developing trends. Machine tool and cutting tool development is rapidly progressing and staying competitive can involve considerable investments in time, capital, and somewhat secure predictions for future demands. If the market and business forecasts are unsure, major investments might not be an option. In the instance where the primary goal is to reduce costs and to handle a temporary market downturn, the first strategy manufacturers should consider is investigating the current workshop set up. For example, machine utilisation is measured in the percentage of time that the machine is producing components. Increasing active machining time by only a few percent makes a big difference. To complement this, quick change tooling solutions reduce time spent on measuring, set-up, and tool change, allowing for drastically improved machine utilisation and lower overhead costs. This also supports energy and sustainability goals as manufacturers require less new machinery and tools, preventing scrap products from being disposed and consequentially, reducing their footprint. Lastly, where budget allows, investments are a must. Increasing machine utilisation with existing machine tool set-up is a good strategy to optimise processes without making large investments in an unsure market situation. But investing in new machines and cutting-edge technology can be the most favourable approach to gain an edge over competition, as well as improve the efficiency of processes. With potential order increases, strategic investment will ensure a successful outcome in today’s increasingly competitive global environment, while future proofing the workshop for what’s yet to come.

With the implementation of generative AI, metalworking can revolutionise product design by generating multiple prototypes and selecting the most efficient and effective designs, resulting in reduced time and cost during the product development process. In addition, AI will also be key in optimising manufacturing processes by identifying areas where efficiency can be improved and automating repetitive tasks, ultimately increasing productivity and minimising human error. The potential of AI in metalworking was demonstrated in April 2023, when Sandvik Coromant, partnered with Sandvik Group, launched the Impossible Statue. Our engineers were tasked with creating an AI-generated, stainless-steel structure combining some of the world’s most famous works of art. While their metal cutting expertise was put to the ultimate test, AI ensured this was achievable. The statue, weighing 500 kilograms and 150 cm tall, was made using AI modelling and cutting-edge manufacturing solutions. Specifically, Sandvik used in depth estimators to build the 3D model, human pose-estimators to refine the body, videogame algorithms to generate realistic fabric and specialised AI to re-introduce fine details that were lost in previous steps.

Simon Ng, Partner Sales Director, Strategic Engagement, Asia Pacific South, Dassault Systèmes

South East Asia’s main economic business drivers in 2024 amidst global uncertainties will be dependent on the following; Rising labour cost in China, coupled with continuous trade and political tensions. This is projected to result in the shift of manufacturing from China to various South East Asian nations in the long term; Many countries in South East Asia i.e. Singapore, Malaysia, Vietnam are extensions of the high tech and electronics industry ecosystem that will continue to boost the region’s growth in industrial manufacturing; Other factors driving growth for industrial manufacturing in South East Asia are energy-related, construction industry boom in countries like Indonesia and Philippines. Expansion of Electric Vehicle (EV) supply chain in Thailand, Indonesia, Singapore, Vietnam, and Malaysia; The region is also home to a population of more than 600M and with a combined GDP of over US$4T, forms the largest economic bloc after USA, China, Japan, and EU.

The challenges that economies face in South East Asia includes: Uncertainty in global economies, downward pressure on demand from advanced economies where South East Asian nations typically export to. This has a direct impact on manufacturing activities; South East Asian nations are well-known to be contract manufacturing bases. Classified as middle-income countries (except for Singapore and Brunei), they are extensions of advanced economies and only form part of the ecosystem with lower labour cost, abundance of raw materials. As shown in the diagram below, the main activities that take place in these countries are related to ‘manufacturing’ or ‘production’ instead of the higher value-added design or product development activities in the electronics industry. South East Asian economies are overly focused on low-cost production of selected industry sub-segment’s electronics systems, as opposed to evolving into a knowledge-based economy centred on research and development of advance industry segments such as IoT. The diagram below illustrates the region’s capabilities in selected industry segments and value-added production activities.

Some of the best practices or strategies for South East Asian industrial manufacturing companies include: To improve value proposition of contract manufacturers to become ODMs (Original Design Manufacturer) or even OEMs (Original Equipment Manufacturer) in the future. Instead of investing in the bare minimum for production, South East Asian companies should adopt ‘Kaizen’ and continuously improve its existing processes towards best-in-class. Take on additional value-added activities such as product substitution i.e. Japanese or Chinese manufacturing companies in the last decades. To do the above, South East Asian companies need to continue expansion towards higher value-added activities of the entire industry value chain. E.g. adopt enterprise technology solutions, upskilling of workers, expand R&D capabilities. The diagram below depicts the typical technology adoption of manufacturing companies. Adopt best-in-class enterprise solutions of the OEMs in Product Lifecycle Management, Enterprise Resource Planning, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Generative AI in various application levels from ideation, validation, process automation, and reporting and customer interactions e.g. chatbots, big data for machine learning of customer behaviours, generative design to explore various options of design or weight saving/cost saving. The diagram below shows various industry segment requirements, their business models and business tiers.

AI, ML, DL and Generative AI technologies are continuously being researched and added to various cloud-based technologies to improve the entire product lifecycle process. Refer to the diagram below for a typical product lifecycle process and Gartner’s 2024 Hypercycle of emerging technologies with Generative AI at the peak of inflated expectations; Ideation: Conceptual design to create, review and to evaluate before embarking on the entire design to manufacturing process with various technologies such as cloud, free form, generative design to determine function before form. Design: Utilising 3D modelling approaches, from top-down design to capture design intent, to generative design to reduce weight, explore design options and alternate manufacturing processes. E.g., latticing, alternate materials, additive manufacturing. Modelling Simulation (MODSIM) concepts for early insights of product performances and to reduce prototyping with the use of machine learning and various mathematical models. E.g., finite element analysis (FEA), computational fluid dynamics (CFD). Development: Explore Virtual Twin concepts, improve production and simulate system commissioning to optimise processes.  Prototyping: Use of various machine learning and deep learning technologies for fabrication process, from additive manufacturing technologies with 3D printing and further improve subtractive manufacturing technology of generating high-speed or smarter toolpaths for various Computerised Numerical Control machines processes. Validation: Generative AI technology to assist in making various product and manufacturing decisions. E.g. front–end loading concepts for the execution of details engineering, procurement and construction for accurate project costing. Assembly: Use of Augmented Reality (AR) and Virtual Reality (VR) Technology for sales configurators to expand sales online or in global dealerships and improve assembly instructions in the shop floor to improve cycle time. Test: Utilisation of AI in total quality control (TQC) processes; for measurement, validation, documentation, and reporting to the connected enterprise system for product lifecycle and release management. Shipping: Complete logistics applications of connected enterprise resource planning and supply chain management solution to ensure seamless process integration and customer experience.

Scott Huang, Techman Robot, COO

South East Asia is currently experiencing a robust economic upturn, leading to a heightened demand for metal products in various sectors, including construction, automotive, and manufacturing. Notably, the metalworking industry is witnessing a surge in the adoption of advanced technologies such as artificial intelligence (AI) and automation, which offer significant potential for improving productivity and efficiency.

To enhance productivity, several strategies are being employed: Automation: Collaborative robots with AI capabilities excel at performing repetitive, labour-intensive tasks with remarkable precision. This results in a substantial increase in production rates and consistency. Predictive Maintenance: AI-powered predictive maintenance solutions are crucial in preventing unplanned downtime, ensuring optimal equipment and machinery utilisation. Quality Control: AI-driven vision systems are effective in real-time quality assessments, reducing defects and minimising the need for rework. Quality Enhancement: Precision and Defect Detection are key components. Advanced AI algorithms can elevate the precision of metalworking processes, leading to higher-quality end products. AI can also quickly identify even the smallest defects, reducing the number of substandard products reaching the market.

Techman Robot stands out as the premier automation solution for smart manufacturing in South East Asia, offering a substantial boost to productivity through its advanced AI features. As a pioneering leader in the field of collaborative robotics, Techman Robot has redefined the next generation of such cobots with its innovative TM AI Cobot. The standout feature of this robot is its integrated intelligent vision and AI capabilities, facilitating precise object recognition and defect detection.

The TM AI Cobot operates on the core principles of intelligence, simplicity, and safety. By integrating visual processing into its robotic arm, this AI Cobot demonstrates exceptional speed and precision across a wide range of applications, including pick-and-place tasks, AMR, palletisation, welding, semiconductor manufacturing, product assembly, AOI inspections, and food service preparation. Its AI-Vision capabilities offer a significant boost to efficiency in these areas. Particularly, it promises valuable support to the metalworking industry in South East Asia.

Marcelo Tarkieltaub, South East Asia Regional Director, Rockwell Automation

By 2030, the manufacturing industry in South East Asia could generate up to US$600 billion a year. Manufacturing is one of the most significant contributors to South East Asia's economy and is undergoing rapid transformation. Some key factors that can influence the manufacturing sector's outlook include technological advancements, sustainability and environmental regulation, and economic growth. Yet, challenges such as inflation, supply chain disruptions, and workforce shortages persist. By implementing advanced automation and data-driven solutions, companies can enhance operational efficiency, reduce downtime, and optimise resource utilisation, thus embracing digital transformation.

Rockwell Automation’s 8^th Annual State of Smart Manufacturing Report finds that 29% manufacturers believe that smart manufacturing has already helped them to keep pace with market transformations and to mitigate the lingering impact of the pandemic. The streamlined processes help reduce human errors and boost overall output. Cost savings are another advantage, stemming from reduced labor costs and optimised resource utilisation. Furthermore, automation services drive more consistent product quality due to standardised production processes. Other considerations are cybersecurity, system integrations, and regulation.  Cybersecurity becomes paramount to safeguard interconnected systems against potential threats. Integration complexities between new and existing systems require resolution. Navigating evolving regulations and compliance standards is essential.

However, the biggest barriers to adopting smart manufacturing for APAC manufacturers are employee resistance to technology adoption and change, a lack of skill sets to manage smart manufacturing implementation, and a lack of a clear definition of the value/ROI of smart manufacturing. According to the report, 48% of businesses report a lack of skills to manage smart manufacturing initiatives as the biggest barrier to adoption, while 46% report employee resistance to new technologies as the biggest barrier. Change management is therefore a key component of successful technology.

Adoption also remains a challenge as shown by the 26% of automotive manufacturers that cite technology paralysis – an inability to decide between solutions – as one of their main obstacles to overcome. To address challenges related to employee resistance to technology adoption, manufacturers should empower their employees with the necessary skills to adapt to evolving roles and collaborate effectively with AI systems. Providing education and upskilling opportunities to enhance digital capabilities is crucial. AI and Augmented Reality (AR) tools can be highly effective in this regard, creating virtual environments for experiential learning and knowledge-sharing.

It is important to note that smart manufacturing equips manufacturers with the information and insights to optimise productivity, quality, risk management, and sustainability. Smart manufacturing also provides them with the flexibility to address manufacturing issues quickly and efficiently while reducing downtime and risks to their workers, assets, and reputation.

For example, in a food and beverage packaging plant, automated Operational Technology (OT) data capture allows for correlating production parameters with batch numbers, documenting details like pressure, temperature, and container thickness.

Looking ahead, the future of manufacturing in South East Asia holds immense potential, marked by notable trends and challenges. Manufacturers should look into investing in automation, robotics, AI, and IoT to improve efficiency, reduce costs, and stay competitive.