Hyundai Motor Company will establish a Hyundai Mobility Global Innovation Center in Singapore (HMGICs) to accelerate its innovation efforts and transformation into a smart mobility solution provider. With support from the Singapore Economic Development Board (EDB), the new 28,000 sqm innovative lab will be located in Singapore’s Jurong Innovation District and is set to be completed in the second half of 2022.
The lab will explore business ideas and technologies to revolutionise a value chain encompassing R&D, business and production for future mobility solutions and eventual expansion into global markets. Combining Hyundai’s open innovations efforts with Singapore’s fertile atmosphere, HMGICs will validate concepts including multi-modal mobility service.
The lab will also spearhead efforts to reach new markets and customers with cutting-edge technologies that will transform automotive R&D, production and sales. Combining AI, Internet of Things (IoT) and other advanced technologies, the lab will create a human-centred smart manufacturing platform that will be validated through a small pilot EV production facility.
In conjunction with the platform, an innovative product development process and on-demand production system will be tested and proven. Hyundai also aims to study new methods of vehicle development conducive to smart manufacturing while further increasing use of virtual reality (VR) technology in the vehicle development process.
Furthermore, HMGICs will facilitate collaboration opportunities with competitive local partners and educational institutions such as the Nanyang Technological University by conducting joint projects to pursue open innovation.
“The Hyundai Mobility Global Innovation Centre is an exciting addition to Singapore’s growing Mobility ecosystem. Its focus on innovative business concepts and the development of a smart manufacturing platform, leverages the research and innovation capabilities, and the value that Singapore provides to companies that want to develop, testbed and create new solutions for the world,” said Mr Tan Kong Hwee, Assistant Managing Director, EDB.
As part of its Smart Nation initiative to drive the adoption of digital innovation across industries, Singapore is actively fostering the use of digital technologies such as AI, digitalisation, and smart urban mobility. With a strong track record for open innovation, Singapore is an ideal location for Hyundai to test its innovative ideas such as HMGICs.
Solutions for suppliers seeking ways to meet new productivity challenges, including increasing demand and shorter lead times. Article by Michael Palmieri, Makino.
Aerospace and defence (A&D) suppliers are feeling the heat.
Over the next five years, original equipment manufacturers (OEMs) are expected to increase commercial aircraft production by 21 percent. The ramp-up means suppliers face unprecedented challenges. They must find ways to satisfy demand for more components while OEMs place more pressure on them to decrease lead times and prices.
Industry 4.0 technologies, including the Internet of Things (IoT), automation and advanced machine-tool capabilities, such as 5-axis machining centres, could become more common on A&D shop floors as suppliers seek ways to keep pace with OEM demands.
These technologies can help the A&D suppliers respond to market needs faster without expanding their workforce. This white paper will explore some of these trends and the solutions that A&D suppliers need to remain competitive.
Enable Faster Throughput for Complex Designs
Modern aircraft designs are forcing suppliers to rethink their current production capabilities. Older machine tools may not be equipped to manage lighter-weight, heat-resistant materials, such as titanium. Modern machining centres that are purpose-built for aerospace applications can reduce set-up times, increase accuracy and improve throughput on less-conventional designs.
Titanium vs. Aluminium Considerations
Aluminium makes up about half of the aerospace materials market by volume. But titanium use is increasing as manufacturers seek ways to reduce weight for components in next-generation planes. Titanium is lighter than structural steels historically used and almost as strong. Aluminium and titanium present different challenges that manufacturers must take into consideration when selecting machine-tooling solutions. Aluminium requires more horsepower and high rpm while titanium requires high torque at low rpm.
Suppliers need access to a variety of machine tools that can perform fast removal rates on a wide range of materials, including aluminium, stainless steel and titanium. Several key advancements in machine tooling are helping A&D suppliers address different material requirements. Some of the key technologies developed to increase productivity for titanium machining include:
Autonomic spindles that protect the spindle from excessive forces damaging the bearings. This can reduce unplanned downtime related to machine damage—which, in turn, optimizes productivity.
High-pressure, high-flow coolant systems deliver large volumes of coolant directly to the cutting zone for faster chip evacuation, increased production, and tool life.
Vibration damping systems that adjust frictional forces based on low-frequency vibration sensing, avoiding chatter and cutter damage from structure resonance in real time. Vibration damping enhances depth of cuts, which results in higher removal rates.
Developments in aluminium machining are also helping A&D suppliers increase productivity. This includes greater spindle power to improve processing speeds, improvements to acceleration and cutting feed rates, and large-capacity automatic tool changers that are capable of holding more than 100 tools and automatic pallet changer—which can reduce changeover and set-up times significantly.
In both aluminium and titanium, 5-axis capability is a key advantage by providing an efficient way to produce typical, complex, A&D part geometries. In addition, large-capacity tool changers and pallet changing automation can allow for unattended machining, which means less operator labour cost per part. These system features reduce machine downtime between parts and part handling between set-ups, which also lowers labour costs. The ability to reduce handling time, including moving parts from machine to machine or resetting them on new fixtures, also helps increase throughput and shrink production lead times to enable faster deliveries.
Maximise Productivity to Avoid Costly Delays
Many A&D suppliers are struggling to meet demand. For instance, in November 2018 Boeing reported decreases in 737 deliveries due to supplier delays. The lead time in A&D manufacturing is already longer compared to other industries, which means suppliers can’t afford machine failures or any other issues that could result in downtime. Suppliers may need to place a greater emphasis on predictive maintenance and automation to maximise productivity.
Why Reliability Matters
On-time delivery issues are urgent enough that Boeing and Airbus are working with suppliers to ensure they’re equipped to meet expectations. In addition, unplanned downtime costs manufacturers about $50 billion annually, and equipment failure is the cause of downtime 42 percent of the time.
Manufacturers are implementing automation and Industry 4.0 technologies to gain visibility into machine performance issues before they lead to major repairs or failures. In the A&D sector, Industry 4.0 is bringing predictive insights to operators and technicians in several ways, including:
The ability to access charts that display alarm events, so operators and technicians can observe trends and implement corrective measures.
Access to spindle and axis monitoring technologies that record and display axis forces, loads and speeds. This data can then be used to fine-tune processes for faster cutting speeds and greater depths of cut. In addition, manufacturers can monitor critical tool data for multiple machines from one centralised location. Operators can use this data to make adjustments for enhanced tool performance and lifespan.
Camera monitoring capabilities that capture an internal view of a machine’s work zone, making it easier to solve processing errors before they impact part quality. Technicians also can receive email and text notifications of alarms, including images of the work zone. This helps service staff immediately address maintenance issues before they become costly problems.
According to Deloitte, manufacturers that implement predictive maintenance technologies typically experience operations and MRO material cost savings of 5 percent to 10 percent, reduced inventory carrying costs, equipment uptime and availability increases of 10 percent to 20 percent, reduced maintenance planning time of 20 percent to 50 percent and overall maintenance cost reductions of five percent to ten percent.
A&D suppliers also are realising enhanced performance through automated machining solutions, such as pallet-stacking systems. The Makino Machining Complex (MMC2) is an automated material handling system that links Makino horizontal machining centres, pallet loaders and operators. The system provides a constant flow of parts to the machining centres, so it can operate for extended periods unattended, including overnight and on weekends. The ability to automate manual processes reduces the need for time-consuming manual tasks and increases flexibility to meet OEM demands.
Bridging the Workforce Skills Gap
As machine tools become more technologically advanced, the A&D industry must confront another persistent challenge: the lack of skilled workers. In a recent industry workforce survey, 75 percent of respondents said they are concerned with the availability of key skills. “The need for talent will become even more critical in the next few years, as the baby boom generation moves beyond traditional retirement age – and the unavoidable loss at some point of their expertise and knowledge,” according to Aviation Week’s “2018 Workforce Report.” Machines that are equipped with IoT, artificial intelligence (AI) and other smart capabilities can enhance productivity for existing employees and minimise the learning curve for new hires.
The Case for a Connected Workforce
Voice-assistant technology common in the consumer world, such as Alexa and Siri, are now making their way into modern machine tools. In fact, more than 80 percent of A&D industry executives say they expect their workforce to be directly impacted by an AI-based decision within the next three years, according to an Accenture report. Voice-activated commands reduce manual interaction with the machine and helps operators translate and analyse big data. These digital assistants typically work through the use of headsets. Operators speak commands into the headsets, such as “turn the machine’s lights on,” “change tools,” or “show set-up instructions.” These voice-actuated capabilities simplify machine operation by reducing the time operators spend searching for information or performing manual tasks.
AI also serves as a coach for operators who may not be familiar with various operating procedures, such as how to perform different maintenance tasks. For example, a worker can ask the voice assistant how to change a filter. In many cases, these intelligent machines are not replacing operators but helping the existing workforce perform their tasks more efficiently.
They’re also allowing workers to move easily from one type of machine to another without a significant learning curve because they’re not reliant on an unfamiliar machine interface. These intelligent machines may help A&D manufacturers identify and onboard skilled workers with greater ease because they require less training and experience than more traditional technology.
Looking Ahead: What’s Next for A&D Machining
High-tech machining solutions are advancing at a rapid pace. The availability of new technologies comes at a critical point for the A&D industry. Suppliers must continue to improve productivity and reduce costs amid a constantly changing environment. In addition to OEM demands, the industry faces new competitive challenges, including potential price increases for materials. For instance, A&D manufacturers are still uncertain how U.S. tariffs on aluminium and steel imports could impact prices. The potential for higher material prices puts additional pressure on suppliers as they try to meet increasing demands for lower costs per part and delivery.
Suppliers need equipment that can reduce downtime, increase productivity and minimise labour costs. Manufacturers should consider machine-tool providers with a broad portfolio of equipment built specifically for the aerospace industry. The latest machining centres can perform high-precision tasks faster than ever. Vendors with experience in the aerospace industry can help A&D suppliers evaluate their needs and select a solution that is appropriate for specific applications. Makino is continuously updating its machines with the latest technologies, including automation and IoT capabilities, to help the industry produce accurate structural and turbo machinery parts faster with less variability and at the lowest cost.
How ATEP Slashes Titanium Machining Costs
Arconic Titanium & Engineered Products (ATEP) in Laval, Quebec, Canada, needed titanium-machining solutions to meet customer demands to lower costs and shrink delivery times. ATEP specializes in assembly and precision machining of various titanium aircraft components, including wing attachments, seat tracks and doorframes. Standard machine platforms couldn’t provide the rigidity, flexibility or control the company needed to meet its customer requirements. The company decided to install several Makino T-Series 5-axis horizontal titanium machining centres. Research engineers from ATEP determined the machines could help the company perform certain production processes three times faster than previous methods. It eventually led to a 60 percent reduction in cycle times and 30 percent reduction of tool costs.
The company also has realized benefits related to quality improvements. ATEP is a fully integrated supplier of titanium and other specialty metals products. ATEP is receiving additional business from customers who are asking the company to correct quality issues from other suppliers, according to a company executive.
Step-by-step networking for in-house manufacturing, involving suppliers and customers and efficiently using data together – the digital services provided by c-Com, a member of MAPAL Group, make it all possible. However, the start-up isn’t just developing its own applications. It’s also generating added value for customers by working closely with cooperation partners.
Cooperation with MARPOSS: reduced setup times and maximum tool service life
The optimal and longest-possible use of tools represents a vital cost factor for machining companies. But compromises are often necessary – particularly in series production and as part of automated processes. Tools with a defined tool life are replaced as soon as the specified tool life has come to an end. In many cases, though, the tool has not truly reached the end of its tool life and replacement is not yet necessary. However, companies play it safe to avoid quality issues and the risk of producing items that later need to be rejected.
This is one of the elements addressed by the ARTIS GENIOR MODULAR module by MARPOSS. The fully automatic tool- and process-monitoring system has been an established feature of the market for many years. It works by recording various measurements and assessing them on the basis of several criteria.
MARPOSS recently launched a collaboration with c-Com GmbH and its c-Com open cloud platform to provide module users with additional value: the ARTIS GENIOR MODULAR module and c-Com are set to exchange data. Once the defined tool limits have been reached, the staff member responsible receives a notification on their mobile terminal – which is made possible by the cooperation with c-Com. As a result, operators can react more quickly and boost the efficiency of their manufacturing processes.
Cooperation with Oerlikon Balzers: transparency and sustainability thanks to digital processing for coating
Many tools are re-sharpened and re-coated to make production as cost-efficient as possible and to use raw materials sustainably. This procedure is very complex for everyone involved – from the machine operators to the staff members carrying out the re-sharpening and coating. If a staff member responsible for re-sharpening sends a tool for coating, this staff member is often not aware of corresponding order status. This results in frequent queries. In some cases, the number of re-sharpening processes is simply marked on the tool shank. Overall, the total benefit is reduced by the very high investment of time and effort required.
In cooperation with Oerlikon Balzers, c-Com has developed an application that enables significantly more effective and transparent order processing. The prototype was showcased at EMO Hannover. The only prerequisite to benefitting from the advantages of digital processing for coating is identifying all tools with a unique ID.
The c-Com application exchanges data with the myBalzers customer portal run by Oerlikon Balzers. This way, the entire order process is digitalised, and all receipts are available online. It is easy to share documents such as delivery slips, invoices or order confirmations, and the status of each coating order can be viewed in real time. There is no longer a need to ask for order updates – a quick glance at the application provides the user with all the information they need. On top of this, machine operators have access to all the important information about their tool at all times. Thanks to the collaborative approach by c-Com, they can access all data via the cloud.
The c-Com wear detection app: a technical advisor in your pocket
c-Com has developed a wear detection application to provide answers to these questions. The prototype for the application was presented at EMO Hannover. The application is very simple to use: first, the worn blade is documented using a smartphone and a conventional auxiliary lens for zooming in. The app then identifies the type of wear and suggests corresponding recommended actions. This allows users to prevent this type of wear in future.
The application is based on machine learning, a sub-category of artificial intelligence. This means that the application uses datasets to learn. Together with tool specialists at MAPAL, c-Com has compiled and categorized hundreds of images. Effectively, the algorithm was trained by being shown what different types of wear look like, allowing it to assess whether or not a blade is in good order.
Manufacturers are now adopting artificial intelligence (AI) to further create value for the customers. But how would AI be applied to sheet metal bending? In this article, Melvin Tham, Regional Technology Expert – Bending, for TRUMPF, explains.
Using conventional press brakes to achieve high accuracy for sheet metal is challenging due mainly to the property of the material, where its elasticity varies according to its composition and grain direction. Therefore, the process would usually take a longer time as it requires more knowledge and skill in order to achieve higher accuracy.
In today’s industrial environment, machines are loaded with functions to ensure that the manufactured parts are precise and consistent with minimal human/operator intervention, and manufacturers are now adopting artificial intelligence (AI) to further create value for the customers. But how would AI be applied to sheet metal bending?
Automatic Set Up
Given the current high-mix, low-volume market demand, the system must be easily set up within minutes to cater for a job change over. Therefore, a self-centring tooling system would be most ideal. With an automatic tool changer, there is no longer a need for alignment as the tools are automatically placed in position and integrated into the machine. It has three to four times more storage capacity than the machine’s bending length, all just to ensure a quick changeover and without the hassle of tool shortage.
Positioning and Angle Accuracy of Part
Since the bending process is now automatic, the quality of the parts has to be checked automatically as well. Such system would require high dynamic functions such as the backgauge. The backgauge with an axis tolerance of ±0.02 mm and the angle sensor tool with tolerance at ±0.5 deg are required to ensure that the part is placed accurately in position and angle tolerance is achieved by an angle checking device.
Sensors of the backagauge are necessary for the identification of the part in position. Without this, the part would not be able to achieve its desired flange length.
An automatic detection of the angle needs to be equipped to determine the correct angle to be achieved for each bend. With Automatic Controlled Bending (ACB), the total completion time to bend, calculate and adjust will take less than a second!
Identification of Parts and Positioning Compensation
The system must be able to detect the correct part to pick up and automatically determine the datum point to compensate positioning error. It is important to define the datum point so that all bending sequence and positioning accuracy can be referenced.
Although a structured stand that pre-fixed the part datum point can be achieved, the best possible solution will be with a high-resolution and precise camera profile detection that is flexible and automatic. This camera device could detect the sheet stack, height and fine profile of the part for single sheet without the need to specifically prepare sheet in a fixed position. With such function, a lot of time is saved from the preparation for defining, picking and loading of parts.
The grippers picking up the parts are of critical importance as well. Our grippers are designed with the concept of holding the parts as firmly as a human hand would. The gripper can be used for multiple parts and the suction cups can be pneumatically turned on or off to cater to different profiles and gripping area.
CAM-assisted Offline Programming
Software plays a very important role in automation. It should be able to strategically control all movement offline with intuitive graphical teaching.
In the past, robot movements are codings that are entered line by line in order to perfect a smooth travel path. With advanced software like TruTops Bend Automation, not only are we are able to graphically teach the movement from one point to another, we can also teach the robot to flip, load and unload the part. The software enables us to run a simulation prior to the actual process.
Robotic Movement and Payload
There are many robotic equipment in the market, with some having more than eight axis of movement and payload of more than 1,000 kg! So how do we know which is suitable?
In bending, it is always the working area within the press brake and robotic system. The bigger the working capacity means there is a better flexibility on the type of profile that can be bent.
The longer the trackway of the robot arm, the more parts can be prepared for loading and unloading. This is to ensure that the machine is always filled with part for continuous production and not idling or waiting for parts. There are also possibilities that the finish part can be stacked in cage or drop box.
The higher the payload means a bigger robot arm would be required. When the arm gets too big, there is a minimum distance of limitation due to the kinetic movement, therefore small parts cannot be picked up. Hence, it is important to define the size of the product before the selection of the automatic bending cell. This will make it easier to select the type of press brake and robotic arm for the job.
With all the necessary functions that are in place to ensure the output quality of the parts, the production is all ready for artificial intelligence bending!
The aerospace industry is growing at an exponential rate. In fact, by 2028 it is predicted that upwards of 38,000 aircraft will be in service, a vast increase from the 26,000 being used today. As a result, digitalisation is increasing the reliability and efficiency of aerospace systems across the world. Here, John Young, APAC director at automation parts supplier, EU Automation, explains how digitalisation is transforming the aerospace sector in the Asia-Pacific region.
Like many other industries, digitalisation is transforming the aerospace sector. Currently, there is already an uninterrupted flow of real-time information coming from aircrafts updating ground operations and the pilots on the status of systems, equipment and weather conditions. However, this is simply the beginning of what is possible with the integration of digital technology across the sector.
Across maintenance departments in the industry, data is being monitored and analysed by artificial intelligence (AI) and machine learning systems. In fact, airlines in Asia have already begun implementing AI tools for simulation and data modelling of aircraft.
This information can then be used to decide precisely when an aircraft’s components should be replaced or repaired and when other maintenance is required. This integration has helped to ensure that the lifespan and function of individual parts are fully optimised, and the overall aircraft systems are kept safe.
By using AI to monitor and predict requirements, it is possible to ensure that all required maintenance equipment and parts are ready for when the time is right.
In recent years, Virtual Reality (VR) alongside big data has pushed the boundaries of predictive maintenance. Since 2016, the aerospace company Airbus has been making use of this technology to help boost Asia’s maintenance, repair and overhaul (MRO) sector inside its Hangar of the Future initiative in Singapore.
VR and augmented reality (AR) technologies are disrupting traditional techniques of aerospace maintenance by allowing engineers to see maintenance activities from new and unexplored angles. This means that new data can be captured, and advanced simulations can be created to train maintenance teams for future procedures, as well as allowing personnel and pilots to view and test virtual replicas of the aircraft equipment before physically handling them.
One of the downfalls of rapid uptake in digitalisation is the risk of data security and breach of privacy. This uncertainty applies to the aerospace sector especially, where the increasing connectivity of systems is also putting aircraft at risk of hacking and attack from cybercriminals.
Countries in the Asia-Pacific region have been reported to be 80 percent more likely to be victims of cyber theft as a result of their lack of awareness. Leading suppliers, however, can offer cybersecurity services and build a safe environment of data security and trust, while also helping organisations to avoid and recover quickly from cyber-attacks.
There is no shortage of digital technologies being used in the aerospace sector. These new and rising innovations are disrupting traditional methods of maintenance, operations and repair by providing experts with more intel about vital parts and the mechanical needs of aircraft. However, much of the vast quantities of data that technology such as AR and VR are producing still need to be kept secure. Only then can the digitalisation of aerospace fully flourish and continue to grow.
Artificial intelligence (AI) is rapidly entering a new phase within the enterprise market, with an increasing number of businesses leveraging AI to turn the massive amounts of process, operational, and transactional data being collected into actionable insights that can improve the way they run their businesses as well as improve customer interactions, according to a new report from Tractica.
Based on the number and variety of pilot programs, proof-of-concept (PoC) demonstrations, and commercial deployments of AI technology already being publicised by enterprise customers around the globe, it is clear that AI is not a fad, but a key part of the technology landscape of today and tomorrow. Tractica forecasts that annual revenue for enterprise applications of AI will increase from $7.6 billion worldwide in 2018 to $107.3 billion in 2025.
“No longer is the discussion of AI limited to science fiction, autonomous vehicles, or Siri; AI is being deployed across a multitude of industries and use cases with enterprises leading the way,” says principal analyst Keith Kirkpatrick. “Thanks to the use of template-driven AI platforms, even a small pilot program can demonstrate real-world benefits. As enterprises are realising, the benefits of AI are even greater when the technology is scaled across the entire organisation.”
Tractica’s report, “Artificial Intelligence for Enterprise Applications”, examines the practical application of AI within commercial enterprises, providing a comprehensive analysis of use cases, business models, market drivers and barriers, technology issues, and the evolving market ecosystem.
Preventing unscheduled downtime is one of the most effective cost reduction measures in any production environment. Mitsubishi Electric is offering practical solutions for both machine tools and robots.
Mitsubishi Electric and its [email protected] Alliance partner Lenord + Bauer have developed an advanced condition monitoring system for machine tools. It utilises smart encoders and a direct communication interface within Mitsubishi Electric machine controllers, such as CNCs, for accurate status information that is easy to access.
Operating hours are recorded and monitored along with temperature, speed and position by the Lenord + Bauer MiniCODER range. These parameters are then used to help schedule maintenance activities by providing an early warning message when component servicing or replacement are required. The ferromagnetic measuring gear and scanning unit can record speeds of up to 100,000 revolutions per minute, making the system ideal for feedback on machine tool spindles and positioning systems.
The second solution on the stand uses AI to increase the effectiveness of predictive maintenance. The cloud-based solution using the AI platform within IBM Watson analyses operational data and can optimise maintenance regimes based on actual usage and wear characteristics. It can be applied to robots and other equipment such as machine tools. Both smart solutions demonstrate how predictive maintenance for machine tools and robots can reduce operational costs, increase asset productivity and improve process efficiency.
According to Tractica, global revenue for digital twins will increase to $9.4 billion in 2025, up from $2.4 billion in 2018. A digital twin is a digital representation that provides the elements and dynamics of how a device or ecosystem operates and lives throughout its life cycle. Digital twins are useful for simulating the capabilities of machine tools in a safe and cost-effective way, as well as identifying the root causes of problems occurring in physical tools or infrastructure.
The digitisation of nearly every industry type is helping to fuel the demand for twinning platforms, as is the desire to monitor, control, and model the future behaviour of real-world equipment, systems, and environments. Manufacturing, aerospace, connected vehicles, smart cities, retail, healthcare, and industrial IoT are key sectors for digital twins market adoption. Asia Pacific is one of the largest geographic regions for digital twins, forecasted to generate $11.2 billion in cumulative revenue.
“Like any technology, digital twins must be understood and accepted by several different stakeholders, from the operations workers up to the C-suite,” said Principal Analyst Keith Kirkpatrick.
“Vendors are highlighting their expertise in analytics and demonstrating domain expertise with specific industry verticals. Some are also spotlighting their experience with incorporating artificial intelligence (AI) and machine learning (ML) technologies, which can provide the ability to model future behaviour via digital twins. These technologies are anticipated to drive the functionality of digital twins beyond simply being enhanced analytics tools,” he added.
Gripping systems and clamping technology provider Schunk is investing around €85 million in expanding its production facilities in Brackenheim-Hausen, Mengen, and St. Georgen in Germany, and in Morrisville, North Carolina, in the United States.
Around 42,000sqm of total production and administration space is being created, starting with the US plant, where the new buildings were officially handed over recently. In addition to the production area expansion, Schunk Intec USA created a 4,000sqm administrative building, which features a Customer Centre, where users can experience Schunk’s components live and receive additional know-how in technology forums and workshops. The new building was inaugurated in early May with an official ceremony followed by a Family Day. Schunk has invested a total of almost €10 million in the expansion of the site.
Meanwhile, €40 million are being put into the Competence Centre for Gripping Systems in Brackenheim-Hausen, Germany. The extension covers an area of 22,000sqm and represents a doubling of the existing production area.
Schunk is investing another €30 million in the Competence Centre for Lathe Chuck Technology and Stationary Clamping Systems in Mengen, in the district of Sigmaringen, Germany. Here, 12,000sqm are to be added for production and R&D.
Around €5 million were invested at the St. Georgen site in Black Forest, where the production area was doubled with an increase of 4,200sqm.
“In the coming years, we will experience a boom in automation and digitisation worldwide, and we’ll only be able to handle this by having the right capacities,” said CEO Henrik A. Schunk.
For several years, the company has been successfully focusing on these two trends and concentrating its resources and know-how. Schunk expects high growth rates, especially for mechatronic and increasingly intelligent clamping devices and gripping systems.
The company also recently announced its cooperation with AnotherBrain, one of the world’s leading specialists in artificial intelligence (AI).
The industrial robotics market was valued at US$18.05 billion in 2018 and is expected to reach US$37.75 billion by 2024, at a compound annual growth rate (CAGR) of 12.15 percent over the forecast period (2019–2024), according to market analyst Mordor Intelligence. The market has been witnessing a huge demand over the past decade, owing to the rising adoption of smart factory systems, of which these robots play a vital part. The global smart factory market is expected to reach US$388.68 billion by 2024, which provides insights on the scope of the adoption of industrial robots for automation across end-user industries.
In particular, Industry 4.0, the newest industrial revolution, has fuelled the development of new technologies, like collaborative robots and AI-enabled robots, to name a few, and have enabled industries to use robots to streamline many processes, increase efficiency, and eliminate errors. Increased workplace safety and improved production capabilities have further driven industries to invest in robotic systems.
Rising Demand from Automotive Industry
The growing adoption of automation in the automotive manufacturing process and involvement of digitisation and AI are the primary factors driving the demand for industrial robots in the automotive sector.
In 2017, more than 170,000 robots took part in the production process in the European automotive industry. The growing presence of robots and automation in the European automotive industry is expected to fuel the market for industrial robots in the region.
Meanwhile, China has also become both the world’s largest car market and the world’s largest production site for cars, including electric cars, with much growth potential. In Malaysia, there are 27 automotive manufacturing and assembly plants. Overall, the growing automotive industry in Asia is also creating a massive opportunity for the global industrial robotics market.