Why We Invested in Infinite Uptime and Accelerating Digital Transformation of Industry

The Industrial Landscape and the Prevalence of Mechanical Breakdowns

Processing plants are a backbone of global industry, converting raw materials into finished products through intricate machinery systems. Success of these plants is, naturally, very dependent on the efficiency and reliability of their unimpeded operation. Unfortunately, mechanical breakdowns represent a very real, common, and significant threat. Statistical studies show that most breakdowns are due to mechanical issues, stemming from factors like wear and tear, improper maintenance, corrosion, or similar issues. These failures lead to unplanned downtime, causing operational and financial problems, including costly repairs, lost production, missed deadlines, and regulatory penalties. Despite recent leaps in advancing technology, the continued frequency of mechanical failures demonstrates persistent shortcomings that remain in current maintenance approaches.

Predetermined schedules or symptom-based methods often lack precision, either leading to unnecessary work or allowing minor issues to escalate. IoT systems have been hailed as a solution, offering real-time monitoring and predictive capabilities. However, these too have limitations. Current IoT systems struggle with mechanical predictive analytics, handling high-frequency data above 100 kHz, and deciphering meaningful insights from noise. Bandwidth and storage constraints further limit data analysis. Standard IoT systems were not designed for the complexities of industrial environments. Time-series analysis, common in IoT, is ineffective with high-frequency industrial machinery data. The unique nature of the data requires a more sophisticated approach for effective analysis and predictive abilities.

Figure 1. The intimate link between asset condition and recoverability compared against how a failure is identified and addressed.

When considering the limitations of traditional maintenance methods along with the shortcomings of current IoT solutions, a few key insights become apparent which outline specific industry needs and state of the overall landscape -

1. Primary Industries Concerned: Automotive, heavy industries, and oil & gas sectors have the most vested interest in improving process efficiency and reliability through predictive maintenance (PdM) solutions. These industries operate on a colossal scale, where even brief downtime can trigger extensive financial losses and as such suffer the most from unplanned maintenance. Unforeseen stoppages in automotive assembly lines disrupt production chains, while breakdowns in heavy industries and oil & gas facilities lead to significant maintenance expenses and potential safety hazards.
2. Critical Need for merging Data Science and Physics-based High-Frequency Model : Any PdM solutions in consideration by heavy industries will require high-frequency data acquisition to keep up with dynamic nature of operation, and to ensure accuracy must be anchored in data science and physics-based understanding. This drives some natural design preferences such as interest in acquiring larger volumes of data at regular intervals through wired powered sensors over wireless battery operated (lower operating cost, higher intervals of data acquisition, and no battery replacement considerations) as well as the augmentation of AI models dealing with mass data with physics informed criteria.
3. Full Stack Software/Hardware Solution: Customers seek holistic solutions that encompass both hardware and software components. Instead of adding another system to monitor, the preference would be any solution to include provider “ownership” of the problem, including ownership of the hardware, as well as installation and support of the software throughout use. This means the quality of both aspects are key, and the trend is moving towards hardware-enabled SaaS models.
4. Dedicated Specialized Support: Related to the previous insight, bottom line any PdM solution must be more than just about sensors and alerts — but provide dedicated support to provide timely and actionable insights — insights that lead to direct actions. Having technical experts closely involved in the AI loop enhances solution effectiveness and customer consultation.
5. Data Security: Data security and total cost of ownership are major considerations. There is understandable hesitation to share data with external clouds, especially for comprehensive process-wide monitoring — which has led to some delay in adopting some state-of-the-art technologies. This concern can be alleviated by utilizing internal cloud solutions and proper implementation of collaborative AI/human in the loop infrastructure.
6. Return on Investment (ROI): To enhance adoption of PdM solutions, its critical to prove the ROI of such digital solutions and tying to the business outcomes is an essential step.

By addressing these industry needs and leveraging advanced technologies, businesses can overcome the limitations of current approaches and significantly enhance plant reliability. The next section will introduce Infinite Uptime, a company that has recognized these needs and developed innovative solutions to address them.

Introducing Infinite Uptime: Revolutionizing Plant Reliability

Infinite Uptime is a pioneering company that has recognized the pressing need for advanced solutions to enhance plant reliability and optimize industrial operations. With a strong focus on leveraging cutting-edge technologies and data-driven approaches, Infinite Uptime has developed a suite of innovative PdM solutions to pave a way to a new future of improved plant reliability. At their core, Infinite Uptime differentiates themselves by following means:

1. Providing a robust AI-driven PdM system anchored by physics-based machine failure models that can handle large volumes of data without sacrificing accuracy. This includes a library of 1000’s of types of equipment so the system is ready to monitor any set of equipment the customer may need.
2. Has developed a one-of-a-kind algorithmic approach to overcome the signal to noise ratio challenges of high frequency data, improving monitoring accuracy and response time.
3. Delivers an optimized and scalable cost, leveraging wired sensor technology and removal of any battery to reduce CAPEX and OPEX, and designed to interface with existing already-in-place plant systems.

Infinite Uptime is a team of passionate and experienced individuals with backgrounds in industrial automation, artificial intelligence, and data analytics. This diverse team brings together expertise from various domains, allowing Infinite Uptime to offer comprehensive solutions that combine advanced technology and industry knowledge.

The mission of Infinite Uptime is to empower industries with the tools and insights necessary to achieve enhanced plant reliability, minimize downtime, and optimize operations. They understand that plant reliability is a critical factor in the overall productivity, efficiency, and profitability of industrial processes. By providing real-time monitoring, diagnostics, and predictive analytics, Infinite Uptime enables businesses to take proactive measures to prevent machine failures, reduce maintenance costs, and ensure uninterrupted operations.

At the core of Infinite Uptime’s technology is their state-of-the-art digital intelligence platform. This platform integrates advanced-sensor technology, machine-learning algorithms, and cloud-computing capabilities to enable real-time monitoring, diagnostics, and predictive maintenance of critical equipment. With their expertise in mechanical predictive analytics, Infinite Uptime goes beyond traditional condition monitoring and offers a comprehensive solution that can accurately detect and predict mechanical failures.

One of the key offerings of Infinite Uptime is their Diagnostics as a Service (DaaS) software. This real-time digital-intelligence platform continuously monitors critical equipment 24/7, collecting data on machine health, performance, and operational parameters. By leveraging advanced analytics and machine-learning algorithms, the platform can analyze this data in real-time, identify anomalies, and notify operators of potential faults or failures. This proactive approach allows businesses to take timely actions, such as scheduling maintenance or replacing components before catastrophic failures occur.

Figure 2. Proprietary, machine-learning informed frequency analysis enables deep- information gathering from massive amounts of real-time data, providing in-the-moment updates on mechanical condition and upcoming failure(s), including specific modes.

In addition to real-time diagnostics, Infinite Uptime provides a Digital Reliability Service (DRS) as part of their comprehensive solution. The DRS platform integrates with the existing industrial infrastructure and drives corrective actions and interventions based on the insights provided by the DaaS software. By combining real-time monitoring with data-driven decision making, the DRS platform enables businesses to optimize maintenance strategies, improve overall equipment effectiveness, and minimize downtime.

To achieve these objectives, Infinite Uptime has developed advanced technology that overcomes the limitations of current IoT systems and traditional maintenance approaches. Their solution can handle high-frequency data exceeding 100 kHz, ensuring that no critical information is missed. By employing advanced signal-processing algorithms, they effectively decipher meaningful insights from the noise, even in environments with low signal-to-noise ratios such as very slow speed equipment. Furthermore, Infinite Uptime’s technology is designed to integrate mechanical data with other relevant data sources, such as operational data, maintenance history, and environmental data. This holistic approach provides a comprehensive view of equipment health and performance, allowing businesses to make informed decisions and develop proactive maintenance strategies.

The remarkable growth of Infinite Uptime serves as a testament to the effectiveness of their solutions. These impressive numbers reflect the value that their technology brings to industries seeking to enhance plant reliability and optimize their operations. Infinite Uptime’s commitment to innovation, technological excellence, and customer-centric solutions has positioned them as a leading player in the field of plant reliability. Their expertise in mechanical predictive analytics, real-time diagnostics, and digital reliability services, sets them apart from traditional maintenance practices and standard IoT systems. By empowering industries with the tools and insights necessary for enhanced plant reliability, Infinite Uptime is driving the digital transformation of the industrial sector and supporting the goal of more optimized and sustainable manufacturing processes.

Why We Invested in Infinite Uptime

At TDK Ventures, we are dedicated to investing in innovative technologies that contribute to and accelerate global digital transformation for a better and more sustainable tomorrow. When we first encountered Infinite Uptime, it was evident that they aligned perfectly with our mission goals and had the potential to revolutionize the industrial sector.

1. Technology trailblazer: Infinite Uptime used the power of physics and engineering based AI driven data science models for 1000’s of equipment types and use cases, providing high accuracy of failure prediction and low miss rate.
2. Large volume of data to train AI algorithms: By virtue of using wired powered sensor module, Infinite Uptime is able to collect larger volumes of data at much shorter intervals. Using high frequency data sampling and the vast number of sensors deployed on machines, Infinite Uptime has built a significant moat through the volume of data it has been able to train its AI algorithms.
3. Superior Customer experience with prescriptive insights and scalable solution: Having built models specific to machine type and use case, Infinite Uptime has been able to provide detailed prescriptive insights rather than raw data. The hardware has been designed in a manner where a single cable connector is sufficient.
4. Market Traction and Strong Customer Revenue Retention: Infinite Uptime has shown a promising land and expand trend within marquee global customers which proves the value of their solution
5. Better ROI: Leveraging the cost base of India to build the product and provide technical and customer support, Infinite Uptime is able to offer better ROI compared to global competitors . With expansion to US and EU to engage with customers with higher willingness to pay, Infinite Uptime will have a significant advantage on their profitability.

By investing in Infinite Uptime, we are not only supporting their growth and expansion, but also actively participating in the transformation of the industrial landscape. We believe that their innovative approach will catalyze the adoption of digital technologies in manufacturing, paving the way for Industry 5.0. This next phase of industrial revolution goes beyond automation and focuses on the seamless integration of sustainability, digitization, and industry. Their mission to enhance plant reliability, optimize operations, and drive the digital transformation of the industrial sector aligns perfectly with our strategic goals.