Latest news with #Industry40
Forbes
2 days ago
- Business
- Forbes
Rethinking Inventory: Real-Time Data And Edge Tech In Industry 4.0
Amy Gu, CEO and Cofounder at Dynamsoft. Industry 4.0 is not just about automation. It's about smart systems that sense, adapt, predict and act in real time. One example is inventory control, which was once a centralized back-office function but has now become core to real-time operations. Both edge computing and smart data capture can play important roles in managing inventory decisions, so let's look at how these technologies work and where they fit in for realizing the promise of Industry 4.0. From Centralized Control To Real-Time Edge Insight Traditional cloud-based inventory systems were subject to network latency and limited by reliability and bandwidth. Edge computing, in contrast, brings processing close to the data source instead of relying on remote cloud servers. Smart factories, agile logistics and responsive retail all require low-latency, real-time decision making based on smart data capture. In the context of Industry 4.0, therefore, edge computing helps enable real-time decision making on the factory floor. A 2023 study by Accenture found that, while 83% of companies believe edge computing is essential to remaining competitive, only 65% are using it. Half of those who have adopted edge computing have deeply integrated it. AIDC: The Backbone Of Smart Data Capture Automatic identification and data capture (AIDC) is a technology that turns physical inventory into actionable digital data by automatically collecting information from barcodes, radio-frequency identification (RFID) and Internet of Things (IoT) sensors. For instance, barcode scanning and batch scanning provide visibility for receiving and inventory counts. Similarly, RFID provides passive tracking of high-movement inventory. Computer vision and optical character recognition (OCR) read structured data at speed, and IoT sensors monitor conditions at the item level (e.g., temperature, moisture for perishable goods). This smart data, combined with edge analytics, is what powers real-time inventory control. To understand how this works, let's look at some potential use cases for AIDC across a few industries: • Parts are scanned on delivery using batch barcode scanning to speed up inventory receiving. Edge analytics updates inventory counts in real time and flags shortages before they impact production. • Components are tagged with RFID at workstations. Edge systems track usage and trigger restocking automatically. • Items are scanned in bulk at receiving and picking. Edge-based barcode scanning verifies inventory with a visual image of all items scanned, flags any discrepancies and stores the image for compliance. • Pallets and items may be tagged with RFID, enabling detection without line of sight. Edge analytics maintains real-time stock levels and verifies physical versus digital inventory. • Staff scan item barcodes for restocking. Edge systems suggest optimal replenishment. • RFID tags enable shelf-level visibility and auto-replenishment via triggers. • Barcodes track items from factory to pharmacy. Bulk scanning enables hundreds of lab samples or drug boxes to be scanned in one pass and a visual record stored for audit. Edge systems verify their authenticity, expiry and batch while tracing their movements for regulatory compliance. • RFID tracks bulk or high-value inventory through transit and storage. Edge systems detect if stock is nearing expiry or is in the wrong area. • IoT sensors monitor temperature and humidity in storage. Edge analytics triggers alarms and corrective action if conditions cross a safe threshold, ensuring compliance. Designing For Edge Insight While edge processing is the key to real-time decisions, cloud sync is still important. A best of both worlds approach combines smart data capture, lightweight, no-latency, local processing for real-time decisions and syncs with cloud-based enterprise resource planning (ERP) systems for long-term analytics: • Edge: Deploy mobile phones equipped with barcode scanners and RFID readers as edge devices, capturing data and processing locally in real time. Use batch barcode scanning to receive, count and check inventory faster than manual scanning. Harness a mobile app to perform local validation, check stock thresholds and spot anomalies such as duplicate scans or expired items and trigger immediate action. • Cloud: Integrate the technology (via APIs and SDKs) with cloud-based ERP/WMS systems for centralized visibility and long-term analytics. • Sync: ERP/WMS with periodic or event-driven updates from edge devices can provide global inventory visibility and analytics for strategic planning. Essential Insights For Tech Leaders In Industry 4.0, edge computing moves from the fringe to the frontline. AIDC devices are deployed throughout complex supply chains not only to maintain visibility but also to self-correct based on real-time data. Inventory can be re-ordered, re-routed and flagged using AI and edge with minimal human intervention. Inventory goes from being a ledger to a real-time data feed. For tech leaders navigating Industry 4.0, real-time inventory is emerging as a core driver of agility, automation and resilience. It's no longer simply about stock management—it's about building responsive systems that act on data the moment it's captured. To differentiate, tech leaders must shift focus from where the data is stored to where it is captured and processed, ensuring that frontline scanning and sensing technologies are deeply integrated into production, warehousing and distribution workflows. There are also a few minefields to navigate. Edge and AIDC devices may capture sensitive personal or product data, triggering regulatory requirements. You'll need to consider data encryption (in-transit and at-rest) to prevent snooping, storing minimal data locally, tokenizing identifiable fields and logging for audit visibility. The other big challenge is cybersecurity. Edge devices often operate outside of traditional firewalls, making them vulnerable to attack. To tackle this, I'd recommend adopting a zero-trust architecture, enforcing regular firmware updates for edge devices (which often ship with outdated firmware) and segmenting networks to control flow between edge and core systems. If you are leading digital transformation, now is a good time to compare notes with peers in other industries: How fast is your inventory data driving decisions? Are you still relying on legacy manual scanning and cloud lag, or are you capturing data at the edge and triggering action immediately? Sharing these insights across teams and industries will be the key to unlocking the true value of Industry 4.0. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Zawya
4 days ago
- Business
- Zawya
South Africa: Township retail and millennial consumers' fast-food buying patterns in industry 4.0 and 5.0
A friend shared how his kids complained about visiting their Eastern Cape home during festive season, citing no fast-food delivery, poor internet access, and disliking supermarket trips, preferring convenient online services instead. Fast-food restaurants and chain supermarkets are leveraging on emerging technologies to swiftly deal with growing customer demands for digital delivery services. Using new technologies has become a culinary trend that intensifies modern-day retail trends. Lately, artificial intelligence (AI) tools offer immense potential for enhanced value and efficiency to many fast-food lovers. This can be attributed to inspiration from North America and European markets, where fast-food retailers considerably shape what and how the world eats. Therefore, it would be beneficial for township fast-food retailers in emerging markets to embrace industry 4.0 which focuses on integrating technology and digitalisation into business processes. All driven by latest shifts in manufacturing practices brought by industry 5.0 to optimise productivity with machine-based operations aimed at amplifying value. Such trends would greatly appeal to techno savvy fast-food patrons, including the millennial consumer cohort. Known to be technologically well informed and equipped with electronic gadgets, they seem to be growing endless demand for quick and simple service offerings. Also, they do have candid purchase experiences with everlasting cravings, often nudging them to consume foods with unconventional ingredients for daily feasts. The procreative AI tools that drive consumer consumption patterns, brought innovative means and ways of satisfying such customers' love for food. Many fast-food retailers across the globe explore AI infused tools to prepare food for quick serves to patrons. In general, global fast-food market was valued at around R1.59tn by the end of 2024 and estimated to grow at a compound annual growth rate of CAGR 4.5%, to reach almost R 21tn by the year 2033 (Business Research Insights, 2025). In South Africa, several technologies in the fast-food market are applied using AI tools such as gamification, display kiosks, cashless digital graphics and chatbots to name a few. These tools could also be useful for fast-food retail operators based in townships if they are to embrace AI's worth for their businesses. The gradual use of AI in various business sectors in the country, including education, manufacturing and retail environment, signifies the essence of digitising productivity and supply for business survival. Insight Survey (2024) reports that during 2023 financial year, South Africa's fast-food industry showed significant growth, exhibiting an increase of 8.7% compared to previous years. This growth is anticipated to continue with projected CAGR of 8.0%, from 2024 to 2028. Given that Indurty 5.0 tools emerged to be beneficial for many businesses, it is still surprising that many businesses, particularly in township markets are resistant to change traditional customer service means and embrace new technologies which could positively impacts their profitability to a foreseeable future. The issue here is that: Are township fast-food retail operators ready to competently serve millennial consumer's needs based on projections of their ever-changing demands? Also, are they able to effectively apply Industry 4.0 and 5.0 using AI infused tools? Currently, only a few appreciate the potential of AI tools to intensify efficiency and increase profits. Key factors that influence changes in South Africa's fast-food retail industry - Global economic shifts: Continuous revisions aimed at meeting evolving consumer demands in a dynamic global economy. - Physical environment and health awareness: Millennial consumers' increasing health awareness and preference of nutritious meals apart from responsible practices they expect in the environment. - Convenience: Greater demand for rapid service, delivery options, and mobile ordering at affordable prices are critical in distinguishing consumer purchase intentions. Thus, shifts towards modern urban dining outlets are imperative. - Brand identity and appearance: Aesthetic appeal and packaging stimulate purchasing intentions and rapidly changing consumer lifestyles and consumption patterns seen in the market. - Rapid digitalisation: Technological integration for deliveries, cashless payment methods, loyalty cards, and omnipresence of fuel price changes are also noteworthy. - Changing consumer lifestyles: Lately, consumers follow flexible consumption times and look for adaptable dining options and settle towards diverse menus that offer diversity. The above-mentioned factors should be considered as many South Africans habitually shop online and enjoy Serve Direct-To-Consumer experiences with e-commerce platforms. Millennials from townships, are gradually moving away from conventional buying patterns, and this forces their fast-food retail operators to adapt and embrace AI to optimise operations leveraging latest technological trends. Sarah Jarvis from Forbes reiterates that embracing AI infused business operations while serving customers from a personalised level, would be a prudent approach to venture into. Enhancing personalised user experiences employing data analytics as an example, would assist businesses to keep track of customer buying patterns. Again, township fast-food retailers could start hiring remote AI masterminds to execute and oversee digital innovations in their outlets. Also, understanding different types of data to use when assessing customer consumption patterns to effectively develop AI-driven solutions is important. Ultimately, embracing Industry 4.0 and 5.0 with AI-driven data analysis tools can increase township based fast-food retail operators' efficiency and profitability serving customer preferences applying AI tools to techno savvy consumers.
Zawya
4 days ago
- Business
- Zawya
Sharjah takes the lead in advanced manufacturing with launch of Maxbyte Industry X.0 Innovation Hub at SRTI Park
Sharjah, UAE: In a major leap toward strengthening the UAE's advanced manufacturing ecosystem, the Sharjah Research, Technology and Innovation Park (SRTI Park) has launched the Maxbyte Industry X.0 Innovation Hub, a cutting-edge centre of excellence designed to accelerate industrial transformation in the region. The initiative stems from a strategic partnership between SRTI Park and Maxbyte Technologies, a leading industrial deep tech company headquartered in Abu Dhabi. The new hub is positioned to become a regional catalyst for Industry 4.0 transformation, enabling companies—especially SMEs—to adopt digital, robotic, and decarbonization technologies that enhance competitiveness, productivity, and sustainability. Hussain Al Mahmoudi, CEO of SRTI Park, said during the inauguration: 'We are proud to launch the Maxbyte Industrial Hub from within SRTI Park—a step that marks a pivotal moment in supporting industrial modernization across the UAE and the wider region. The hub offers a real opportunity for manufacturers to access transformative tools, digital strategies, and new frameworks that will allow them to scale efficiently and smartly.' The Maxbyte Industry X.0 Innovation Hub is built on five key pillars: Innovation, Transformation, Education, Career Development, and Community Building. It aims to train 6,000 skilled professionals and engage over 125 companies in Industry 4.0 adoption by 2028. More than 75 specialized training programs are planned over the next three years, complemented by an annual Industry X.0 Innovation Festival and ongoing meetups for industrial leaders. Ramshankar CS, CEO of Maxbyte, said: 'This hub is where forward-thinking manufacturers will forge their futures. We have designed it as an agile transformation platform where enterprises can adopt digital tools, embrace automation, and build future-ready teams equipped for the next industrial era.' Among the key initiatives presented during the launch were advanced programs in Quantum Computing, Semiconductor Design & Manufacturing, Machine Tools & Smart Production, and the company's flagship LEAP program, which integrates innovation, education, and workforce readiness. The hub has already conducted over 200 ITTI readiness assessments, laying the groundwork for regional transformation. It aims to impact more than 1,500 individuals and become a cornerstone for job creation and talent development in the UAE's industrial sector. The launch of the Maxbyte Industry X.0 Innovation Hub aligns with the UAE's national Operation 300bn strategy, which is focused on boosting the industrial sector's contribution to GDP, strengthening local manufacturing, and attracting high-tech investments. SRTI Park continues to lead as one of the fastest-growing innovation ecosystems in the Middle East, providing world-class infrastructure and a thriving collaborative environment that bridges government, academia, and the private sector to shape the future of research, innovation, and industrial excellence in Sharjah and beyond.
Yahoo
09-07-2025
- Business
- Yahoo
AI-Powered Manufacturing in the U.S. Set for $6.08 Billion Market by 2028
Delray Beach, FL, July 09, 2025 (GLOBE NEWSWIRE) -- The report "Artificial Intelligence in Manufacturing Market by Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing), Application (Predictive Maintenance & Machinery Inspection, Cybersecurity) - Global Forecast to 2028" The Artificial Intelligence in Manufacturing Market in the US is expected to reach USD 6.08 billion by 2028, up from USD 0.92 billion in 2023, at a CAGR of 46.0% from 2023 to 2028. The growth of Artificial Intelligence in the Manufacturing Market in the US can be attributed to the rapid adoption of industrial robots in manufacturing plants, which generate large volumes of data used to train machine learning algorithms, enhancing the capabilities of robots. Additionally, the US is a leader in adopting the Industrial Internet of Things (IIoT), which, along with computer vision and context-awareness computing technologies, facilitates smarter, more efficient manufacturing processes. These technological advancements, combined with the country's strong focus on innovation and digital transformation, contribute to the anticipated growth of AI in the manufacturing market in the US. Download PDF Brochure: List of Players in the AI in Manufacturing Industry: IBM, Intel Corporation, NVIDIA Corporation, General Electric Company, Google LLC, Microsoft, Micron Technology, Inc., Amazon Web Services, Inc. (AWS), Sight Machine, and others. US AI in Manufacturing Market Segmentation: Hardware segment to grow with significant CAGR during the forecast period. The hardware segment of AI in the manufacturing market in the US is set to experience substantial growth, driven by the increasing demand for high-performance processors that can efficiently handle complex AI algorithms. This segment includes various components such as processors, memory, and network systems, with processors being categorized into microprocessor units (MPUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs). Among these, GPUs are particularly expected to see rapid growth due to their exceptional parallel computing capabilities, which are essential for running AI-driven applications in manufacturing. As the industry continues to embrace AI technologies to optimize production, improve automation, and enhance data processing, the demand for advanced hardware solutions like GPUs, MPUs, and FPGAs is expected to rise, further fueling the market's expansion in the US. Computer vision technology segment to grow with significant CAGR during the forecast period. The computer vision segment within the AI in manufacturing market in the US is experiencing significant growth. This technology enables machines to analyze visual data, improving production processes by detecting defects, monitoring quality, and enhancing automation. In industries like automotive, electronics, and food & beverage, computer vision is used for quality inspections, defect detection, and ensuring precise assembly. It also supports predictive maintenance by identifying equipment issues early, reducing downtime. In the automotive sector, it plays a key role in part recognition and surface inspection. As AI and computer vision technology advance, their application in US manufacturing will continue to grow, driving greater efficiency, reducing costs, and improving production capabilities across various industries. Predictive maintenance & machinery inspection hold a significant market share in the AI in manufacturing market in the US. Predictive maintenance & machinery inspection hold a significant market share in the AI in manufacturing market in the US. AI systems analyze data from machinery and sensors to predict potential failures, allowing maintenance to be performed only when needed, thus reducing downtime and costs. In machinery inspection, AI detects defects and anomalies in real-time, improving quality control and reducing human error. This application is especially beneficial in industries such as automotive, aerospace, and energy, where equipment reliability is crucial. By enabling early issue detection, predictive maintenance & machinery inspection enhance operational efficiency, extend equipment life, and ensure smooth production. As AI continues to advance, these applications will remain central to manufacturing optimization in the US market. Ask for Sample Report: Automotive industry holds a significant market share in the AI in manufacturing market in the US. The automotive industry holds a significant market share in the AI in manufacturing market in the US. AI technology is widely used in automotive manufacturing for process automation, quality control, and predictive maintenance. AI-powered systems help detect defects, monitor assembly lines, and ensure that components meet required specifications. Computer vision and robotics are applied for tasks such as part recognition, defect detection, and precise assembly. Additionally, AI enables predictive maintenance by analyzing machinery data to forecast potential failures, minimizing downtime and reducing repair costs. As AI technology evolves, its integration into the US automotive industry will continue to enhance production efficiency, reduce costs, and improve overall manufacturing processes. 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