<h2 id="isPasted">Compute Scaling Has Exposed a New Bottleneck</h2>For decades, system-on-chip (SoC) design has been driven by improvements in compute performance. Advances in transistor scaling enabled higher clock speeds, greater parallelism, and increasingly specialized processing units. As a result, architectural priorities focused on maximizing compute throughput.That paradigm is now shifting. As SoCs grow in complexity—driven by AI workloads, heterogeneous integration, and evolving system-level requirements—performance is no longer determined solely by compute capability. Instead, it is increasingly limited by the efficiency with which data moves across the system.This reflects a broader transition: modern SoCs are becoming data-movement-bound rather than compute-bound. Delivering data with the required bandwidth, latency, and energy efficiency has become a central design challenge. In many cases, adding more compute resources does not translate into higher performance if those resources cannot be fed with data efficiently.This shift has been observed across multiple generations of SoC design, particularly by companies focused on on-chip connectivity, such as <a href="https://www.arteris.com/" target="_blank" rel="noopener noreferrer">Arteris</a>, where evolving system requirements have increasingly exposed data movement as a limiting factor.<h2>What Changed Inside Modern SoCs</h2>Modern SoCs are highly heterogeneous systems, integrating CPUs, GPUs, NPUs, DSPs, and domain-specific accelerators. Each of these blocks has distinct compute characteristics and data access patterns, increasing coordination complexity across the chip.This complexity is further amplified by the adoption of chiplet-based and multi-die architectures. Instead of a single monolithic die, functionality is often distributed across multiple dies within a package. While this approach improves scalability, yield, and design flexibility, it also introduces additional communication layers—both on-chip and inter-die—making data movement more complex and resource-intensive.At the same time, memory is becoming more distributed and physically distant from compute. Data may traverse multiple interconnect layers, including on-chip networks, inter-die links, and off-chip memory interfaces, before reaching processing elements. Each step adds latency and energy overhead.As a result, workloads increasingly stall waiting for data rather than executing instructions. This trend is particularly evident in AI systems, where performance is strongly influenced by memory access patterns, bandwidth availability, and data reuse efficiency [1]. In such systems, the ability to move data efficiently can matter as much as compute capability itself.<h2>The Real Cost of Moving Data</h2>The cost of moving data is now a dominant factor in system design, both in terms of energy and performance.Accessing data from memory can consume significantly more energy than performing arithmetic operations on that data [2] [3]. As system complexity increases, this imbalance becomes more pronounced, making data movement a primary contributor to overall power consumption.This leads to several interconnected system-level challenges:<ul><li>Energy consumption: Data movement can account for a large share of total power usage, particularly in data-intensive workloads</li><li>Latency: Delays in data delivery reduce effective compute utilization and increase idle cycles</li><li>Throughput limitations: Bandwidth contention between multiple agents constrains overall system performance</li></ul>Traditional interconnect approaches, such as shared buses or simple point-to-point links, do not scale effectively under these conditions. As the number of components grows, these approaches introduce contention, congestion, and inefficiencies that limit performance gains.Industry discussions increasingly frame this as a “data movement problem,” where optimizing compute alone is insufficient. Instead, improving how data flows through the system becomes essential for achieving performance, efficiency, and scalability [4].<h1>Network-on-Chip as System Infrastructure</h1>To address these challenges, modern SoCs rely on network-on-chip (NoC) architectures. A NoC provides structured communication between components through routing, arbitration, and flow control mechanisms.Rather than serving as simple wiring, the NoC functions as core system infrastructure—much like a biological circulatory system distributes resources within an organism. It enables data to move efficiently between distributed compute and memory elements while managing contention and prioritization.The design of the NoC directly affects:<ul><li>End-to-end latency and quality of service</li><li>Achievable bandwidth and throughput</li><li>Power and energy efficiency of communication</li><li>Scalability as system complexity increases</li></ul>Because of this, NoC design is increasingly treated as an early architectural decision rather than a late-stage integration task. Early consideration allows designers to align compute placement, memory hierarchy, and communication topology more effectively.Companies specializing in interconnect IP, such as Arteris, have highlighted this shift across multiple SoC generations, emphasizing that NoC design is foundational to achieving performance, power, and scalability targets in complex systems [5]. <h2>Why This Matters Across Markets</h2>The constraints imposed by data movement are not theoretical—they translate directly into measurable system-level trade-offs across industries, affecting cost, performance, and efficiency:<ul><li>AI systems: Performance is frequently limited by memory bandwidth and data reuse efficiency. Even highly optimized accelerators can experience reduced utilization when data cannot be delivered efficiently, leading to underused compute resources [6].</li><li>Automotive systems: In addition to latency and isolation requirements, systems must comply with functional safety standards such as ISO 26262, including Automotive Safety Integrity Levels (ASIL). These requirements impose strict constraints on communication predictability, determinism, and fault isolation, making reliable data movement critical [7].</li><li>Edge and mobile devices: Tight power and thermal budgets mean inefficient data movement directly impacts battery life, thermal limits, and system responsiveness.</li><li>Data centres: Energy efficiency and total cost of ownership are increasingly influenced by how effectively data is moved and managed, rather than by raw compute scaling alone.</li></ul>Across these domains, inefficient communication infrastructure leads to higher costs, reduced throughput, and underutilized compute resources. Conversely, architectures that optimize data movement enable better system performance, improved energy efficiency, and more predictable behaviour. This is where specialized interconnect solutions, such as those developed by Arteris, help teams manage complexity, optimize data flow, and meet performance and efficiency targets.<h2>Takeaway: Data Movement Is Now an Architectural Concern</h2>The transition from compute-centric to data-movement-centric design represents a fundamental shift in SoC architecture.Data movement is no longer a secondary concern—it is a primary determinant of system performance, efficiency, and scalability. As compute resources continue to scale and diversify, the ability to deliver data efficiently has become just as important as the ability to process it.This makes interconnect design, and particularly network-on-chip architecture, a strategic decision that must be addressed early in the design process. Choices made at this stage influence not only performance and power, but also system flexibility, scalability, and long-term design viability.In this context, effective data movement becomes a key enabler and competitive differentiator for SoC teams, enabling them to better utilize compute resources, meet performance targets, and manage power and system complexity. Systems that can efficiently connect distributed compute and memory resources are better positioned to meet the demands of modern workloads across AI, automotive, edge, and data center applications.As SoCs continue to scale in complexity, the ability to design for <a href="https://explore.arteris.com/white-paper-flexgen" target="_blank" rel="noopener noreferrer">efficient data movement</a> will play a central role in defining next-generation system architectures.<hr /><h2>References</h2><ol><li>Hennessy, J. L., &amp; Patterson, D. A. (2019). Computer Architecture: A Quantitative Approach (6th ed.). Morgan Kaufmann.</li><li>Horowitz, M. (2014). Computing’s energy problem (and what we can do about it). IEEE ISSCC.</li><li>NVIDIA, “NVIDIA Hopper Architecture In-Depth,” NVIDIA, Mar. 22, 2022. [Online]. Available: <a href="https://resources.nvidia.com/en-us-hpc-ai/nvidia-hopper-architecture">https://resources.nvidia.com/en-us-hpc-ai/nvidia-hopper-architecture</a></li><li>EE Times Asia. The Data Dilemma: Cracking the Code of Data Movement for the Next Wave of Semiconductor Innovation.</li><li>Arteris. Data Movement in SoCs: NoC Performance, Power &amp; Scalability.</li><li>Jouppi, N. P., et al. (2017). In-Datacenter Performance Analysis of a Tensor Processing Unit. ISCA. <a href="https://doi.org/10.1145/3079856.3080246">https://doi.org/10.1145/3079856.3080246</a></li><li>ISO 26262. (2018). Road vehicles – Functional safety. International Organization for Standardization.</li></ol>

Why Data Movement, Not Compute, Is Now the Limiting Factor in Modern System-on-Chip (SoC) Design

Limiting Factor in Modern System-on-Chip (SoC) Design

<h2 id="isPasted">Abstract</h2>High-speed, high-fidelity optical communication is essential to modern data infrastructure. Hamamatsu Photonics advances this field through precision-engineered components such as high-sensitivity InGaAs photodiodes and wavelength-stabilised semiconductor lasers. These technologies enable robust, low-latency data transmission across optical fibre and free-space links, supporting critical applications in telecommunications, industrial automation, and next-generation IoT networks. By advancing technology in spectral sensitivity, noise reduction, and integration flexibility, Hamamatsu empowers industries to manage escalating data demands with scalable, energy-efficient systems.<h2>Introduction</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1776716235484-1776716235484.jpeg" width="602" height="337" class="fr-fic fr-dii" />Image Source: StockCakeGlobal internet traffic continues to grow exponentially, driven by cloud computing, video streaming, and smart device integration. To support this demand, optical fibre networks transmit an estimated 90% of global data [1], often at speeds exceeding hundreds of terabits per second. This infrastructure depends on optoelectronic components that convert electrical signals to light and vice versa. Since the first proposals for glass-fibre communication in the 1960s, transmission speeds have advanced dramatically, with laboratory tests now achieving rates up to 301 terabits per second [2].Subsequently, businesses and consumers have come to rely heavily on high-speed connectivity to support growing digital demands. Optical communication technologies significantly increase data transmission speed and reliability. Hamamatsu Photonics supports optical communication with products such as ultra-sensitive photodetectors. These photodetectors offer high responsivity and low noise in the near-infrared range, enabling faster signal detection and reduced bit error rates in optical communication systems. One remarkable technology is their<a href="https://www.hamamatsu.com/jp/en/applications/optical-communication/glass-optical-fiber-communications.html"> </a><a href="https://www.hamamatsu.com/eu/en/applications/optical-communication/glass-optical-fiber-communications.html">InGaAs photodiodes</a> [3], known for high-speed response and sensitivity. These photodiodes effectively manage signals over an extensive fiber-optic network, as their high sensitivity reduces data errors, enabling accurate and swift communication.<h2>Hamamatsu's Advancements in Optical Technologies</h2>At the core of Hamamatsu’s portfolio are their high-speed photodetectors, featuring a broad spectral response from 0.5 μm to 2.6 μm. This wide detection range allows efficient capture of near-infrared wavelengths typically used in high-speed optical communication. Spectral response is critical because different wavelengths are used to optimise data throughput, reduce interference, and extend transmission distances. By fine-tuning detector sensitivity across this range, Hamamatsu ensures minimal signal degradation and maintains the fidelity of high-bandwidth communication.In parallel, Hamamatsu has developed optical transceivers capable of achieving data transmission speeds up to 1.25 Gbps over distances of up to 100 meters. These devices support a variety of data transmission types, including plastic optical fibres (POF), hard plastic clad fibres (HPCF), and large-diameter glass optical fibres. The use of different fibre types enables tailored solutions for specific environments: POFs offer flexibility and cost-effectiveness for short-range links, HPCFs provide better durability in industrial settings, and glass fibres are ideal for long-distance, high-performance transmission. Hamamatsu’s compatibility across these media ensures adaptable, scalable infrastructure for modern data networks [4].Another key development from Hamamatsu is their advanced<a href="https://www.hamamatsu.com/eu/en/product/lasers.html"> semiconductor lasers</a> [5]. These lasers offer excellent wavelength stability and high output power, crucial for network performance. Precise wavelength control allows denser data packing in fiber optics. This density enhances bandwidth efficiency and significantly increases network capacity [6]. Hamamatsu’s laser technologies thus enable reliable, high-capacity, high-speed optical networks. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1776716314986-1776716314986.png" width="602" height="337" class="fr-fic fr-dii" style="width:803px" />Image Source: Adobe Stock<h2>Applications in Next-Generation Connectivity</h2>Emerging communication architectures like 5G and massive-scale IoT systems demand high-speed, low-latency optical links. Components must support dense deployment and maintain performance in electrically noisy or environmentally variable settings.5G in particular depends on optoelectronic components that can support gigabit-per-second speeds while maintaining signal integrity across dense, distributed networks. For instance, Hamamatsu’s optical transceiver <a href="https://www.hamamatsu.com/eu/en/product/optical-sensors/photo-ic/photo-ic-for-optical-link/P16671-01AS.html">P16671-01AS</a> delivers data rates up to 1.25 Gbps, making it ideal for short-range, high-speed communication in 5G base stations and edge devices [7]. This performance helps address 5G requirements such as ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB), both critical for advanced business and consumer services [8].<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1776717711782-AdobeStock_989263373.jpg" style="width:100%px" class="fr-fic fr-dib" />Image Source: Adobe StockIn complex IoT deployments, ranging from smart cities and autonomous vehicles to industrial automation and remote sensing, robust optical communication ensures accurate, real-time data exchange across numerous nodes. These networks often operate in electromagnetically noisy or physically constrained environments. Hamamatsu’s photodetectors and laser diodes are engineered for high signal-to-noise ratios, stable output, and resilience to environmental variability, making them ideal for maintaining performance under such conditions. In industrial applications, their components support time-sensitive networking and closed-loop control systems, enabling faster decision-making and improved operational efficiency. As IoT systems continue to scale, Hamamatsu’s optical solutions provide the foundational communication layer required to ensure seamless, high-integrity connectivity.<h2>Impact on Industry Standards</h2>Hamamatsu’s adherence to and influence on international standards have helped shape modern optoelectronic design criteria. Their components comply with ISO 9001-certified quality frameworks and are widely adopted in fibre-to-the-x (FTTx), industrial Ethernet, and automotive optical bus systems [9].By contributing to free-space optical communication (FSO) capabilities with specialised transceivers and detectors, Hamamatsu also supports niche applications such as optical slip rings and machine vision [10]. Their technologies are referenced in emerging standards that define mechanical and optical tolerances for embedded communication systems. Ongoing collaborations with universities and research institutes allow Hamamatsu to adapt its technologies to meet evolving demands in secure, high-capacity communication.The company's commitment to continuous improvement is evident in its extensive research and development. Hamamatsu collaborates with global research institutes and industry leaders to maintain its technological edge. Its proactive approach to innovation ensures that its solutions effectively meet future communication needs.<h2>Challenges in Implementation and Future Outlook</h2>As with many different technological successes, Hamamatsu is aware of the implementation challenges in making sure these innovative solutions have real impact. Integrating advanced optical components into existing infrastructure can be complex and costly. Compatibility issues and technical integration require significant investment and coordination with network providers. Hamamatsu tackles these challenges through strategic partnerships and ongoing research to simplify integration. Collaborating closely with clients and industry partners helps streamline the adoption of their technologies. This strategic approach ensures seamless implementation of advanced optical solutions.Looking ahead, Hamamatsu is actively exploring new markets and opportunities. Quantum communication and space-based communication systems represent significant growth areas. Hamamatsu provides advanced photonic devices such as detectors and modulators essential for quantum communication. These technologies promise secure, ultra-fast communication networks resistant to traditional security threats. Similarly, space-based communication systems require highly reliable and robust optical components. Hamamatsu’s ongoing research targets these advanced applications, ensuring their technology remains pivotal in future communication innovations. Their involvement positions them strategically for these emerging markets.For an in-depth discussion of quantum communication technologies, see Integrated Photonics for Quantum Communications from APS Physics [11].<h2>Conclusion</h2>Through consistent development, Hamamatsu Photonics remains at the forefront of optical communication technology. Their advanced photodetectors, lasers, and transceivers significantly enhance data transmission speed and reliability. Hamamatsu’s contributions drive the development of global standards, influencing the industry's direction. As the demand for high-speed, reliable communication grows, Hamamatsu's solutions become increasingly important. Their continuous investment in research and partnerships ensures their technologies remain ahead of evolving market demands. Hamamatsu’s commitment ensures robust, efficient, and future-proof optical communication networks worldwide.<h2> </h2>Visit <a href="https://www.hamamatsu.com/jp/en.html">Hamamatsu's official website</a> to stay informed about its technologies. Engaging with its ongoing research and developments helps you stay ahead in optical communications. Whether you are involved in telecommunications, IoT, or emerging technology sectors, Hamamatsu provides essential tools for future success.<hr /><h2>References</h2><ol><li>ResearchGate. (2022). Single-channel 1.61 Tb/s Optical Coherent Transmission Enabled by Neural Network-Based Digital Pre-Distortion. Retrieved from <a href="https://www.researchgate.net/publication/346950927_Single-channel_161_Tbs_Optical_Coherent_Transmission_Enabled_by_Neural_Network-Based_Digital_Pre-Distortion">ResearchGate Website</a>.</li><li>LiveScience. (2023). Fiber-optic data transfer speeds hit a rapid 301 Tbps. Retrieved from <a href="https://www.livescience.com/technology/communications/fiber-optic-data-transfer-speeds-hit-a-rapid-301-tbps-12-million-times-faster-than-your-home-broadband-connection">LiveScience Website</a>.</li><li>Hamamatsu Photonics. (n.d.). InGaAs Photodiodes. Retrieved from<a href="https://www.hamamatsu.com/jp/en/applications/optical-communication/glass-optical-fiber-communications.html"> Hamamatsu Website</a>.</li><li>Hamamatsu Photonics. (2023). Creating Connections: High-speed Optical Transceiver Solutions. Retrieved from <a href="https://www.hamamatsu.com/content/dam/hamamatsu-photonics/sites/documents/21_HPE/featured-products-and-technologies/creating-connections.pdf">Hamamatsu Website</a>.</li><li>Hamamatsu Photonics. (n.d.). Semiconductor Lasers. Retrieved from<a href="https://www.hamamatsu.com/eu/en/product/lasers.html"> Hamamatsu Website</a></li><li>RP Photonics. (n.d.). Semiconductor Lasers. Retrieved from<a href="https://www.rp-photonics.com/semiconductor_lasers.html"> RP Photonics Website</a> </li><li>Hamamatsu Photonics. (2023). Optical Transceiver P16671-01AS. Retrieved from<a href="https://www.hamamatsu.com/jp/en/news/products-and-technologies/2023/20230208000000.html"> Hamamatsu Website</a></li><li>ResearchGate. (2017). ResearchGate. (2022). Single-channel 1.61 Tb/s Optical Coherent Transmission Enabled by Neural Network-Based Digital Pre-Distortion. Retrieved from <a href="https://www.researchgate.net/profile/Hyoungju-Ji/publication/316269999_Introduction_to_Ultra_Reliable_and_Low_Latency_Communications_in_5G/links/58f94a714585152edecb1bff/Introduction-to-Ultra-Reliable-and-Low-Latency-Communications-in-5G.pdf">ResearchGate Website</a>.</li><li>Hamamatsu Photonics. (n.d.). Quality Control and Standards. Retrieved from <a href="https://www.hamamatsu.com/eu/en/our-company/sustainability/quality-control.html">Hamamatsu Website</a>.</li><li>Hamamatsu Photonics. (n.d.). Optical Communication Applications. Retrieved from <a href="https://www.hamamatsu.com/eu/en/applications/optical-communication.html">Hamamatsu Website</a>.</li><li>APS Physics. (2021). Integrated Photonics for Quantum Communications and Metrology. Retrieved from<a href="https://link.aps.org/doi/10.1103/PRXQuantum.5.010101"> APS Physics</a>.</li></ol>

A technical exploration of the photodetectors, lasers, and optical transceivers enabling scalable, low-latency data transmission

Redefining Optical Communication: Innovations for High-Speed Data Transmission

In the procurement process, material selection is among the most important considerations. As most will know, choosing a material with the right mechanical, thermal, and chemical properties can mean the difference between a successful application and part failure. In today’s world of rising supply chain volatility and material scarcity, however, you can’t always rely on your first choice material being available. Let alone in a way that conforms with lead times and budgets. Material substitution is therefore an increasingly critical part of a resilient supply chain strategy. One that enables manufacturers to overcome bottlenecks caused by material shortages and adapt to a changing raw material landscape while maintaining production consistency. Smart material substitution, in particular, is supporting suppliers as they transition from reactive procurement to more sustainable, agile production. In this article, we’ll look at how material scarcity and material shortages can cause significant supply chain challenges and how smart material substitution is a strategic solution. By turning to intelligent online manufacturing services like FACTUREE, procurement specialists and manufacturers can now exploit the benefits of smart material substitution and rely on consistent, high-quality production. <h2>When materials become a bottleneck</h2>Every manufacturer’s goal is to establish a reliable, resilient supply chain. However, with this goal dependent on many factors (such as access to labor and machines, efficient logistics, and degree of material scarcity) a completely invulnerable supply chain is practically impossible to achieve. Materials alone can create a variety of bottlenecks in production chains, ranging from short-term delays to more significant long-term issues that can disrupt manufacturing and destabilize supply chains. Short-term production bottlenecks can be caused by simple delays in material shipments due to weather, geopolitical dynamics, and infrastructure issues. For example, in 2021, when an Evergreen containership blocked the Suez Canal for six days, an estimated $9.6 billion worth of goods was delayed each day. [1] Another reason for short-term bottlenecks is materials not meeting quality standards when they are delivered, making them unsuitable for use.  More impactful long-term bottlenecks caused by material shortages can be traced to several root issues. These include reliance on single-source or scarce materials, regionally constrained raw materials, long qualification cycles, and demand outpacing supply. Such is the case with molybdenum, a refractory metallic element commonly alloyed with steel for energy and automotive applications. With demand growing for the element, production has failed to keep up — one reason being the difficulty in obtaining new mining permits in China. As a consequence, prices for the material have surged, rising 34% between 2022 and 2023 in the U.S. market. [2] Recent geopolitical instability, notably between China and the United States, has also led to significant global supply chain disruptions in the form of export restrictions, sanctions, and tariffs.It goes without saying that challenges in securing a steady material supply have wide-reaching impacts on the production chain, including: <ul><li>Production continuity</li><li>Quality and compliance</li><li>Cost and lead time commitments </li></ul>Overall, material-driven production bottlenecks can cause severe supply chain disruptions, making manual or reactive procurement strategies ineffective. Smart material substitution is therefore becoming a strategic necessity that can not only help overcome material shortages but can anticipate them and fill material sourcing gaps before they impact production schedules. <h2>What is material substitution?</h2>Before going any further, let’s break down what constitutes material substitution. In simple terms, material substitution is a resilient supply chain strategy that enables the transition from a scarce material — or a bottleneck-prone material — to a functionally equivalent alternative. For example, there are broad-scale efforts to transition away from using rare materials to more Earth-abundant materials. We see this in the photovoltaics sector, where research is advancing towards substituting aluminum and copper for silver, a more critically raw material. [3] The primary considerations in material substitution relate to functional material properties. In other words, the substituting material should meet the mechanical, thermal, electrical, and chemical requirements of the application in question. If you are manufacturing a part for the maritime sector that requires a combination of strength, durability, and extreme corrosion resistance, the substitute material should deliver on all fronts or could fail under the specific stresses of the maritime environment. Other important considerations when selecting a substitute material are related to the following:<ul><li>Manufacturability and process compatibility (i.e. can the replacement material be processed using the same production technique and parameters as the first-choice material) </li><li>Regulatory and certification constraints (i.e. is the material validated for the sector/application area in question)</li><li>Availability on the global market </li></ul>In the best cases, the substituting material will not only meet all functional and regulatory requirements, it will also be easier to source, more sustainable, and more cost-efficient than the first-choice material.<h2>Why use smart material substitution</h2>When we talk about smart material substitution, we are not simply referring to substituting like-for-like materials. Rather, smart material substitution is a strategic approach that uses algorithm-driven software to identify optimal material options. This intelligent approach can be built into procurement and manufacturing workflows and takes the legwork and guesswork out of material substitution by generating rapid solutions based on reliable data. This data is derived from various sources, such as certification documentation, material property databases, historical performance reports, life cycle assessments, and cost, availability, and lead-time signals.This algorithm-based approach to material substitution is more powerful, responsive, and scalable than manual processes, which are highly dependent on individual expertise and tend to be more reactive in nature. This expanded capability is owed to software’s ability to simultaneously evaluate a multitude of variables, from mechanical properties and manufacturing processes to cost and global availability. This multidimensional optimization enables manufacturers to make the best choice based on not one but all factors. Moreover, smart material substitution can use different types of algorithms, including rule-based filtering, optimization models, and machine-learning similarity and performance prediction. By integrating this multifaceted model into production workflows, suitable material substitutes can be rapidly screened. Moreover, top alternatives can be backed up by insights that illuminate the similarities and trade-offs between different material options. <h2>The benefits of smart material substitution</h2>For manufacturers and procurement teams alike there are many things to gain from integrating a smart material substitution strategy. In addition to the central benefit of being able to rapidly assess a wider variety of materials based on an enormous amount of data in a truly scalable way, we see other advantages related to productivity, sustainability, and overall supply chain resilience. These benefits include: <ul><li>Reduced production stoppages and downtime caused by specific material shortages.</li><li>Improved cost control in volatile conditions (and in some cases lower material costs). </li><li>More standardized material selection processes within an organization, even across different projects and teams.</li><li>Increased sustainability through the use of LCAs in the algorithmic model, which can factor in a material’s carbon footprint.</li><li>More proactive risk analysis that uses real-time data (such as availability, cost, geopolitical signals) to anticipate material bottlenecks and pre-plan substitutions.</li><li>Increased agility and future-proofing, resulting in shored up supply chains that are ready for expected and unexpected hurdles. </li></ul><h2>Material substitution made easy with FACTUREE</h2>Online manufacturing services and networks are facilitating access to smart material substitution. Manufacturers like FACTUREE, which operates an AI-driven platform that matches procurement inquiries for custom parts with qualified manufacturers in its 2,000-strong network. FACTUREE’s intelligent solution effectively matches client requests with manufacturers based on criteria like design requirements, tolerances, production method, and material availability.If a primary material for a custom part is unavailable or is impacted by an unstable supply, the company is able to provide the client suitable alternatives based on material properties, manufacturability, cost and inventory. Thanks to the AI that analyzes and qualifies requests with the help of real time people who have a final look at every single inquiry coming in.The AI that FACTUREE uses was trained since 2017 with real-world data on material properties, manufacturability, price and inventory of the supplier network. The continuously growing dataset, which now includes over 600,000 data points, currently represents almost the entire manufacturing market, eliminating the need to inquire about individual supplier manufacturability. So, for example, if a customer wants to order parts made from aluminum but the price of aluminum is unstable FACTUREE is able to suggest — on customer request — a functionally equivalent metal or even polymer to ensure production continuity is maintained. Moreover, FACTUREE can advise customers on beneficial material substitutions even when material shortages are not an issue. For instance, high-performance thermoplastics such as PEEK are increasingly being adopted as a cheaper, more lightweight alternative to metal in industrial applications that require low weight, electrical insulation, and chemical resistance. Smart guidance on material substitutions can therefore not only alleviate supply chain challenges, but can enhance part performance and help improve bottom lines. Not only is the FACTUREE supplier matching system accessing the trained AI, but also the new domain-based AI agent FACTUREE Navigator that was launched in late 2025. Anyone who procures or designs components is often faced with the same questions: Which material is best suited? Which surface treatment suits the process? Such decisions require specialist knowledge and cost time. The <a href="https://www.facturee.de/en/facturee-navigator/ki-agent-explains/" target="_blank">FACTUREE Navigator, a free-to-use tool without a login</a>, closes this knowledge gap. The new AI-supported agent answers technical questions about materials, manufacturing processes and surface treatments in a matter of seconds. It makes complex manufacturing knowledge available to everyone for the first time. With responses informed by a wide range of proprietary data, Navigator can help FACTUREE customers find material substitutes while also benefiting from lead time improvements and lower costs, all without sacrificing quality or performance.<h2>Conclusion</h2>Ultimately, as manufacturers and procurement professionals seek to establish more resilient supply chains, smart material substitution has a central role to play. Intelligent algorithms, as demonstrated by the platform capabilities of FACTUREE, can harness vast quantities of material data and enable manufacturers to choose suitable material alternatives when primary raw materials are scarce. This approach can establish greater stability in an increasingly volatile raw materials market and ensure that parts meet all requirements in terms of production scales, schedules, and budgets, as well as performance and quality.<h2>References</h2>[1] Harper, Justin. Suez blockage is holding up $9.6bn of goods a day. BBC News, March 26, 2021. <a href="https://www.bbc.co.uk/news/business-56533250" target="_blank">https://www.bbc.co.uk/news/business-56533250</a> [2] Mineral Commodity Summaries 2024. U.S. Geological Survey, January 31, 2024. <a href="https://pubs.usgs.gov/publication/mcs2024" target="_blank">https://pubs.usgs.gov/publication/mcs2024</a> [3] Mertens, J., Dewulf, J., Breyer, C. et al. From emissions to resources: mitigating the critical raw material supply chain vulnerability of renewable energy technologies. Miner Econ 37, 669–676 (2024). <a href="https://doi.org/10.1007/s13563-024-00425-2" target="_blank">https://doi.org/10.1007/s13563-024-00425-2</a>

How data-driven material decisions keep production moving amid supply chain disruption and material scarcity

Reinforcing the Supply Chain with Smart Material Substitution

Kickboxing rehab is becoming measurable as Saxion University of Applied Sciences combines Xsens motion capture with pressure sensor data to quantify recovery and support better return-to-training decisions.Challenge:Kickboxing rehab is difficult to track with traditional, manual methods, and common tools do not capture punch and kick performance in a sport-specific way.Solution:Using the Xsens Link suit and pressure sensors on pads, Saxion records full-body movement and strike output during structured sessions to generate objective recovery metrics like left-right symmetry.Key takeaways:<ul><li>Built for real training environments: Inertial motion capture requires no studio, making consistent weekly measurements practical.</li><li>Movement plus output: Xsens provides full-body context while pressure sensors quantify strike impact, connecting technique to results.</li><li>Clear progress signals: Metrics like symmetry and repeatable best-effort punch analysis help physiotherapists track improvement over time and guide return-to-sport decisions.</li></ul>Kickboxing is an unsurprisingly dangerous sport. While exciting to watch, throwing uppercuts, jabs, and roundhouse kicks can easily lead to injuries for athletes. To better understand and improve rehabilitation in this demanding field, researchers at <a href="https://www.saxion.nl/" target="_blank" rel="noopener noreferrer">Saxion University of Applied Sciences</a> are exploring new methods of monitoring recovery.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770814514683-Saxion+UFC+Figther+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Closing the gap in kickboxing rehab research“There isn’t much research around kickboxing rehab, especially concerning the use of technology for monitoring rehabilitation,” says Katrien Fischer, researcher and human movement scientist. “Traditional analysis methods are quite manual, making them difficult to quantify and analyze, as these challenges aren’t sport-specific.”Athletes are typically assessed with ground reaction force plates, which are highly effective in sports like running, football, or long jump. However, these tools fall short when applied to combat sports, where punches and kicks are crucial. This gap highlights the need for more specialized approaches tailored to the unique demands of kickboxing.“It’s also important to consider the culture of rehab in boxing and kickboxing,” adds researcher and physiotherapist Remco Kuipers. “Often, not much is done. Fighters tend to push through pain and focus on getting ready for their next match.” This combination of minimal rehabilitation and limited technology has historically made it difficult to measure recovery in combat sports – something the Saxion team aims to change.Full-body kinematics for punches and kicks with inertial motion captureTo tackle this challenge, the researchers turned to Xsens motion capture technology. “We knew Xsens was the right choice because we’ve worked with the system in the past,” explains Katrien. “We opted for the Link suit because of its low latency and ability to pick up on every nuance. Now, we’re using it every week.”The Xsens Link suit is a full-body system with inbuilt sensors that track joint rotation, angles, and velocity. Unlike camera-based setups, it requires no dedicated studio space, making it easy to use anywhere. For athletes with busy training schedules, this convenience makes rehab sessions more accessible and less time-consuming.Inertial motion capture also allows rehabilitation to take place in flexible locations, without the need for specialized labs. Researchers and physiotherapists can bring the technology directly to the athlete, enabling efficient and high-quality analysis on the spot.“We’ve developed a detailed, structured motion capture process to keep data collection consistent,” says Remco. “It involves a warm-up of shadowboxing and pads with a professional trainer. Then we measured eight sessions of kickboxing with a one-minute break between each one. We asked the subject to hit with maximum voluntary contraction, then take the five strongest jabs, crosses, hooks, and uppercuts for analysis.”From subjective feedback to objective rehab decision-makingBy combining motion capture data with pressure sensor measurements, researchers can generate quantifiable insights into performance. One approach they are exploring is the limb symmetry index (LSI), which compares the performance of one arm or punch against the other. Using pressure sensors embedded on pads, this method provides a precise way to measure strength and coordination in combat-specific movements.This kind of objective data has the potential to transform rehabilitation in combat sports. Instead of relying primarily on subjective feelings, physiotherapists could base recovery programs on measurable progress, leading to better outcomes for athletes.“Using Xsens for this project will bring new findings to both us at Saxion and the physiotherapy sector as a whole,” concludes Remco. “We look forward to gathering data that shows improvements in speed, force output, grip strength, and endurance – all essential elements in combat sports performance.”

With Xsens MVN Link

From pain to progress: Bringing data to kickboxing rehabilitation

TenCate Grass is pushing the boundaries of what an artificial pitch can be, using Xsens motion capture to turn every step, cut, and sprint into actionable insight. By grounding their turf innovation in real athlete data, TenCate is creating sustainable next-generation surfaces that feel like natural grass.Challenge:TenCate needs to create a new, sustainable way to manufacture artificial turf – and it needs to perform just as well as the real thing.Solution:Using Xsens, the TenCate research team can test athletes on different surfaces, validating the new turf material.Key takeaways:<ul><li>From lab to pitch: Tencate tested artificial turf in various locations and conditions.</li><li>Combining camera and mocap: Recording athletes with cameras allows for analysis of one part of the body. Xsens supports this with the full context, demonstrating how each surface affects performance.</li><li>Visual indicator of performance: Showing motion capture data from two surfaces, side by side, helps researchers determine which material to prioritize.</li></ul><a href="https://www.tencategrass.com/" target="_blank" rel="noopener noreferrer">TenCate Grass </a>is the world’s leading producer of artificial turf, supplying surfaces for professional sport, community clubs, and municipalities worldwide. Beyond manufacturing, the company invests heavily in R&amp;D at its Center for Turf Innovation in the Netherlands, where its mission is to create turf that feels and performs as close to natural grass as possible.With over 3000 square meters indoor lab – plus access to full-size natural grass and artificial pitches – TenCate works closely with professional athletes and clubs such as PSV Eindhoven to define what makes the perfect grass for each sport, team, and environment. But simply observing players wasn’t enough. To truly understand how surfaces influence performance, TenCate turned to Movella’s Xsens motion capture technology.“We wanted a system that could tell us exactly how athletes move on different surfaces,” says Tom Wills, Manager of the Center for Turf Innovation at TenCate Grass. “Xsens gives us biomechanical data we can’t capture with cameras alone – things like stride length, joint angles, and acceleration patterns.”Sustainable alternativesTraditionally, artificial turf relies on recycled rubber tyre crumb as infill. However, with the EU’s upcoming 2031 ban on microplastics, that material is being phased out. Which, for TenCate, is something of an opportunity.The R&amp;D team is now testing alternatives – including wood chips, cork, and olive stones – as well as developing non-infill turf systems. And to validate these new designs, biomechanics is essential. By capturing data directly from athletes on the pitch, TenCate can compare movements on new prototypes versus natural grass.“People adapt their movement patterns depending on the surface,” explains Tom. “With Xsens, we’ve seen that our non-infill systems are beginning to replicate natural grass performance, which is exactly where we want to be.”Testing in real environmentsUnlike camera-based systems that are limited to the lab or small test zones, Xsens’ portable IMU-based system allows TenCate to run studies on real fields, under real playing conditions.At their innovation center and at partner sites such as PSV Eindhoven’s training ground, TenCate researchers observe athletes performing drills, from sprint starts to sharp 180° turns. The Xsens system records movement seamlessly across multiple pitches, with only quick recalibration needed between surfaces. Sessions typically last up to two hours, limited not by the equipment but by player fatigue. Data is then cross-referenced with high-speed video for detailed surface interaction insights.“The combination of cameras and Xsens gives us the full picture,” says Tom. “We can zoom in on foot-to-surface contact with cameras, and then use Xsens to understand whole-body motion leading to that movement. It’s a level of insight we simply couldn’t get otherwise.”Beyond the raw data, Xsens also provides powerful visualization tools. Coaches, physiotherapists, and decision-makers can view 3D avatars that compare movement patterns across different surfaces – making complex biomechanics easy to understand.“Not everyone can interpret a graph of hip flexion angles,” Tom laughs. “But when you show them two avatars side by side – one running on natural grass, one on an alternative turf – it clicks. People understand. That visual impact is hugely valuable.”Long-term innovationTenCate has been using Xsens since 2021, and the technology has become central to its product development cycle. From early-stage lab tests to large-scale field trials, motion capture data ensures every innovation is backed by hard evidence.For athletes, the system is comfortable and, crucially, not an obstruction once play begins. For researchers, it delivers reliable, repeatable data. And for the wider sports industry, it means safer, higher-performing, and more sustainable pitches.“Xsens has given us the ability to move beyond opinion and perception, and into measurable, repeatable performance data,” concludes Tom. “That’s critical as we redefine what artificial turf can be.”

Data Movement

ORGANIZATIONS. SHAPING THE INDUSTRY.

Latest Posts

Limiting Factor in Modern System-on-Chip (SoC) Design

Redefining Optical Communication: Innovations for High-Speed Data Transmission

Reinforcing the Supply Chain with Smart Material Substitution

From pain to progress: Bringing data to kickboxing rehabilitation

Designing the next generation of playing surfaces