Thinaer Blog
Smarter production decisions and AI initiatives
Gaining Team Buy-In for Digital Transformation
Digital transformation is more than a buzzword—it’s a critical evolution for modern businesses. It involves leveraging digital technology to enhance how businesses operate and serve their customers. This transformation is essential for driving efficiency, improving decision-making, reducing operational costs, and gaining a competitive edge. However, successfully implementing digital transformation requires buy-in from all levels of an organization.
Unlock the Power of IIoT with Low-Code/No-Code Platforms
How IoT and Cloud Computing Resolve Operational Blind Spots
As the renowned management consultant Peter Drucker famously said, “You can’t manage what you can’t measure.” This timeless wisdom is especially relevant in today’s industrial landscape, where over 80% of operations remain unconnected, resulting in significant digital data blind spots. These blind spots hinder companies from achieving optimal efficiency, agility, and competitiveness. So, why do these gaps exist, and how can companies overcome them? In this blog post, we’ll explore the top reasons your operations are in the dark and provide actionable steps to fix them.
Applications of IoT Asset Management Across Industries
Applications of IoT Asset Management Across Industries
In today’s rapidly evolving industrial landscape, effective asset management has become a crucial determinant of success. The integration of IoT asset management platforms is transforming traditional asset management, ushering in a new era of efficiency, productivity, and cost savings. Leveraging IoT asset management, IIoT (Industrial Internet of Things), smart manufacturing, IoT asset performance management, and predictive maintenance is key to unlocking the full potential of modern industries. This comprehensive guide explores the applications of IoT asset management solutions across various sectors, including healthcare, aviation, and manufacturing.
Revolutionizing Location Tracking: Apple and Google’s Find Networks
Apple and Google have recently enabled what are likely the world’s largest, most accurate, and widest-reaching location networks since the dawn of GPS itself. The implications are massive and are poised to shake up the industry. These networks are not unlike the internet or GPS; they’re built upon them. They are, however, fundamentally different, and their existence enables technologies and use cases that would previously have been impossible or cost-prohibitive. They’re also spurring discussion on safety and privacy and just how far is too far. Today, I am talking about Apple’s “Find My” and Google’s “Find My Device” networks.
Real-Time Asset Tracking: A Comprehensive 9-Step Guide for Factory Automation
Tracking factory assets in real-time: 9 steps to maximizing ROI
Thinaer Takes on Vegas: Recap of HPE Discover 2024
Last week, the Thinaer team attended and sponsored HPE Discover 2024 in Las Vegas, an event that brought together industry leaders, innovators, and technology enthusiasts from around the globe. I had the privilege to attend the event, which was full of insightful conversations, exciting announcements, and a chance to showcase Thinaer’s ongoing efforts to drive digital transformation through the Industrial Internet of Things (IIoT).
How Thinaer Transforms Customer Feedback into Strategic Roadmaps
At Thinaer, we recognize the immense value of our customers’ insights. Our commitment to fostering continuous collaboration ensures that the feedback we receive significantly impacts our roadmap and product development process. This approach not only enhances our solutions but also strengthens our partnerships with clients, paving the way for mutual success.
The Power of Healthcare Logistics: A New Way to Improve Patient Outcomes
The healthcare sector is undergoing revolutionary digital transformation and is under increased pressure to automate processes while maintaining first-class patient care. This can be quite a daunting task. Luckily, this is happening at a time of great technological advancement in automation and machine learning with the onset of AI and Industry 4.0.
4 Challenges Facing the CPG Industry and How AIoT Can Help
The global Consumer Packaged Goods (CPG) market is expected to realize a steady 3% CAGR and exceed $2.5 trillion by 2028 from $1.99 trillion in 2021. Like most every industry, CPG manufacturers face challenges in unpredictable shifts in supply and demand all the time. The solution to most of those challenges lies in intelligence.
Assessing the Future of Industrial Asset Management Solutions: BLE, UWB, and BLE Mesh
Asset tracking technology has become an essential tool across industries, from manufacturing and healthcare to logistics and aviation. What is asset tracking? Asset tracking is a method for businesses to manage their assets, such as equipment, tools, and technology....
Unlocking IoT Success: The Power of API-Centric Platforms
What You'll Learn How an API-centric platform works and its key components, including REST APIs and webhooks. Why an API-centric platform is critical for maximizing your IoT investment, offering flexibility, scalability, enhanced security, improved decision-making,...
Filling Aviation Data Blind Spots Across The Airport
There are over 5,000 public airports just in the United States, and each airport has its own set of issues, requirements, and vendor availability. While an individual aviation company can control everything inside their aircraft, they will have to have a different level of conversation to capture data across the airport as multiple vendors are usually required. The good news is that there are still areas that can have a dramatic impact of data availability that are still in your control.
Supply Chain Health Requires Industry 4.0-Level Data
Back in 1735 Benjamin Franklin provided one of the most important reminders to leaders across any industry or discipline when he wrote that “an ounce of prevention is worth a pound of cure.” Turn the clock forward to 2024 and this becomes a strong reminder of why understanding the actual health of a supply chain on a real-time basis can be the basis for amazing profits or a lack of understanding leading to dismal failures.
The Emergence of Supply Chain Health
Supply chain health is actually something measurable, but unfortunately, it seems as if the supply chain is constantly playing catch-up against unprecedented, unforeseen obstacles. With the average global supply chain disruption costing organizations $228 million and forty percent of C-suite executives reporting a marked tarnishing of their brand image due to disrupted supply chains, the state of individual supply chains may not be what shareholders desire. Sixty-one percent agree that achieving greater resiliency in their supply chains is more important than speed and efficiency. Fifty-four percent believe significant changes must happen to curtail disruption in the next five years.
The good news is that if you can measure something, then you can make better decisions to improve the outcome. Addressing supply chain health issues will succeed or fail based on the availability of data from withing the plant as well as across the supply chain and that means uncovering digital data blind spots to ensure the right data is presented to the right people at the right time in order to optimize decisions impacting supply chain health.
Data and the handling of it is critical to survival. It’s no longer enough to have sensor technology on select equipment. How do you create a critical mass of data and harness it to make better decisions on a macro level? How can you track raw materials and finished goods as they move throughout the supply chain? You can easily drown in too much data if you aren’t careful. A small team of people couldn’t possibly take in all data generated by the supply chain and make a rational decision that takes every factor into account.
This is where Industry 4.0 smart manufacturing comes into play. Industry 4.0 taps into the data generated by internet of things (IoT) sensors, cloud computing, and artificial intelligence (AI) and making autonomous decisions. Guided by smart data collection and analysis, some manufacturing equipment has become self-sensing, self-acting, and interconnected in real time. Instead of relying on machine operators, engineers, and those on the shop floor to meet and discuss solutions and reengineering designs, intelligent systems consume every bit of information and arrive at rapid, accurate decision-making, greater efficiency, and resiliency in the face of disruption. Unfortunately, the average manufacturer suffers from significant digital data blind spots which greatly affects the outcomes and directly impacts their supply chain health scores.
Achieving Industry 4.0 Requires Filling Data Blind Spots
Prior to the pandemic, 75 percent of large manufacturers were looking to update supply chain operations using IIoT and analytics-based situational awareness, but now 90 percent of all manufacturing supply chains will have invested in the technology and business processes necessary for true resiliency.
A key breakthrough in Industry 4.0 smart manufacturing is the digital transformation of manufacturing data. Filling digital data blind spots with a fact-based granular, data-centric contextualized view of asset movement as well as digital twin of legacy equipment and manual processes provide the related providence attribute data has become the foundation for supply chain health improvements. Companies can gain access to unprecedented asset traceability and insight into both process health as well as machine health to improve yield, quality, safety, compliance, and brand confidence while reducing waste and environmental impact. And it’s all made possible by collecting data across the value chain from existing IoT sensors and business systems.
IIoT Asset Tracking and Digital Twins For Supply Chain Health
Organizations like Thinaer bring a comprehensive approach to filling these digital blind spots with IIoT asset tracking and digital twin solutions across both commercial as well as the unique security and privacy requirements of classified area manufacturing. The more comprehensive your data set, the better your AI initiatives will deliver on their promise as well as allowing operations executives to spot prevention opportunities before they become problematic.
Let’s discuss your data issues and understand where your manufacturing blind spots put your supply chain health at most risk. Our experts are ready to answer all of your questions and help you get a handle on your digital transformation processes and AI initiatives. If you prefer to research more on this topic then download our latest eBook titled “Track The Untrackable: How to fill manufacturing blind spots for better production decisions and the most complete data set for AI initiatives.”
Empowering Productivity: The Significance of User-Friendly Applications in the Workplace
In today's fast-paced and dynamic work environment, the importance of user-friendly applications cannot be overstated. As businesses continue to embrace digital transformation, the usability of software and applications plays a pivotal role in driving productivity and...
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