Elevator Pitch
We provide predictive maintenance for the manufacturing industry checking metal cutting tool's wear during each cycle of machining, using a computer vision based on deep learning algorithm that segments the wear of the tool image to approve the continuation to optimize life-time or request change to a new one due to safety. All this automates the process reducing the downtime period, while keeps the data and shows dashboards of tool wearing, to help ERP on purchase planning.
Product
Implementation Modes
We offer adaptable products
We deliver high-quality services spanning two distinct modes of application.
Check our Application Preview
Disclaimer: It is not our final product, but you can get a glimpse from an old version to see how the main features works.
Team
Yuri Achermann
Head of Software, Data & Operations
Gustavo Mello
Gustavo Schewinski
Fernando Kendy
Carsten Holst
Head of Business & Manufacturing Expert
Patrick Schwemmer
Head of Computer Vision & AI
Paul Kunze
Head of Sales & Marketing
Q&A
TECH
What is the accuracy level of the prediction system?
Our prediction system represents a significant leap forward in accuracy compared to traditional methods of measuring tool wear, which rely on subjective assessments by human operators.These assessments can introduce variability and subjectivity into the process.
By leveraging statistical principles, we can quantify the current uncertainty in our predictions and continually refine our model based on data. And in terms of industry-standard metrics, we currently achieve an error range of up to 10% when compared to human operators. However, it's important to note that this error arises from assuming that the human operator is 100% correct, which our trials have demonstrated is not always the case.
By leveraging statistical principles, we can quantify the current uncertainty in our predictions and continually refine our model based on data. And in terms of industry-standard metrics, we currently achieve an error range of up to 10% when compared to human operators. However, it's important to note that this error arises from assuming that the human operator is 100% correct, which our trials have demonstrated is not always the case.
How long does it typically take to implement the solution in a manufacturing environment, and what level of technical expertise is required from the customer?
Hardware Installation (2-3 hours):
- Our hardware setup is streamlined and can typically be completed within 2 to 3 hours.
- This involves mounting the necessary cameras and sensors, which are designed for easy integration into the manufacturing environment.
Software Integration (1-hour seminar):
- Software integration is straightforward and typically requires just a 1-hour seminar.
- Our team provides comprehensive training and support to ensure a smooth transition.
- Technical expertise from the customer is not a major requirement, as we offer user-friendly interfaces and guidance throughout the process.
- Our hardware setup is streamlined and can typically be completed within 2 to 3 hours.
- This involves mounting the necessary cameras and sensors, which are designed for easy integration into the manufacturing environment.
Software Integration (1-hour seminar):
- Software integration is straightforward and typically requires just a 1-hour seminar.
- Our team provides comprehensive training and support to ensure a smooth transition.
- Technical expertise from the customer is not a major requirement, as we offer user-friendly interfaces and guidance throughout the process.
To what extent is the solution agnostic to different machine models?
Our solution is fully agnostic to various machine models. It is designed to seamlessly integrate with and adapt to the unique characteristics and configurations of different machines, ensuring its versatility and compatibility across a wide range of manufacturing equipment.
Can you explain the scalability of your solution? How well does it perform as the volume of data increases?
Our solution is designed with scalability in mind to meet the evolving needs of our customers. As data volume increases, our system remains highly performant and adaptable.
MARKET
What is the competitive landscape, and how does our solution differentiate itself?
→ Standalone Microscopes:
- Pros: Offer high-quality images for tool inspection.
- Cons: Require manual labor for analysis, making them labor-intensive and expensive.
→ Laser Bridge Systems:
- Pros: Integrated into machine tools, allowing for automation.
- Cons: Typically lack industry-relevant metrics for comprehensive tool status assessment.
→ Built-in Microscopes (Emerging Trend):
- Many firms are exploring built-in microscope solutions.
- We collaborate with these companies as partners. They provide the hardware, and we enhance it with our intelligent software for more effective tool wear assessment.
- Pros: Offer high-quality images for tool inspection.
- Cons: Require manual labor for analysis, making them labor-intensive and expensive.
→ Laser Bridge Systems:
- Pros: Integrated into machine tools, allowing for automation.
- Cons: Typically lack industry-relevant metrics for comprehensive tool status assessment.
→ Built-in Microscopes (Emerging Trend):
- Many firms are exploring built-in microscope solutions.
- We collaborate with these companies as partners. They provide the hardware, and we enhance it with our intelligent software for more effective tool wear assessment.
Who are our target customers, and what segments or niches do we plan to serve?
1. Manufacturing Companies (SMEs or Big Companies):
- This includes a wide range of manufacturing companies, from small and medium-sized enterprises (SMEs) to large industry leaders like MTU Aero Engines and Rolls Royce.
2. Tool Manufacturers:
- Companies such as SANDVIK, Fraisa, and Kennametal are key players in the tool manufacturing sector.
3. Coolant Manufacturers:
- Coolant manufacturers, like Blaser, play a crucial role in machining processes.
4. Machine Tool Manufacturers:
- Machine tool manufacturers such as DMG, Makino, and GF are at the forefront of machining technology.
- This includes a wide range of manufacturing companies, from small and medium-sized enterprises (SMEs) to large industry leaders like MTU Aero Engines and Rolls Royce.
2. Tool Manufacturers:
- Companies such as SANDVIK, Fraisa, and Kennametal are key players in the tool manufacturing sector.
3. Coolant Manufacturers:
- Coolant manufacturers, like Blaser, play a crucial role in machining processes.
4. Machine Tool Manufacturers:
- Machine tool manufacturers such as DMG, Makino, and GF are at the forefront of machining technology.
What is our business model and how we plan to generate revenue?
Subscription Model:
- Our pricing structure is based on a percentage of the potential cost savings that our system can deliver to the customer.
- For example, a typical company with a high-throughput series production could save approximately 5000 € per year per machine using our system. We aim to enable our customers to capture a significant portion of these savings.
- Our pricing structure is based on a percentage of the potential cost savings that our system can deliver to the customer.
- For example, a typical company with a high-throughput series production could save approximately 5000 € per year per machine using our system. We aim to enable our customers to capture a significant portion of these savings.
What are the specific pain points and challenges in the manufacturing industry that our solution addresses?
→ Tool Wear Assessment: Accurate assessment of tool wear is traditionally subjective and prone to errors.
→ Downtime Costs: Unplanned machine downtime due to tool failure leads to production delays and significant costs.
→ Maintenance Inefficiencies: Inefficient maintenance schedules can lead to premature tool replacements, increasing expenses.
→ Quality Control: Inconsistent tool wear affects product quality and consistency.
→ Downtime Costs: Unplanned machine downtime due to tool failure leads to production delays and significant costs.
→ Maintenance Inefficiencies: Inefficient maintenance schedules can lead to premature tool replacements, increasing expenses.
→ Quality Control: Inconsistent tool wear affects product quality and consistency.
Are there any specific industries or verticals where our technology has shown particularly promising results?
Our technology has demonstrated exceptionally promising results, particularly in the field of milling applications. Milling is a critical process in various industries, such as aerospace, automotive manufacturing, precision engineering, and more.
The ability to optimize tool usage and minimize unplanned downtime has a direct and positive impact on the bottom line for businesses operating in these sectors.
The ability to optimize tool usage and minimize unplanned downtime has a direct and positive impact on the bottom line for businesses operating in these sectors.
ROADMAP
What are the key milestones we have achieved so far and what are our future goals?
→ ✅ Proof of Concept (POC) algorithm development
→ ✅ POC for automated machine internal measurement
→ ✅ Web App Minimum Viable Product (MVP) launched
→ ✅ Successful testing of commercial Inline Hardware
→ ✅ Development of a fully functional MVP
→ 🟩 Develop Proprietary Hardware
→ ✅ POC for automated machine internal measurement
→ ✅ Web App Minimum Viable Product (MVP) launched
→ ✅ Successful testing of commercial Inline Hardware
→ ✅ Development of a fully functional MVP
→ 🟩 Develop Proprietary Hardware
What is our go-to-market strategy and how do we plan to reach potential customers?
→ Leveraging a network of Fraunhofer research communities
→ Harnessing word of mouth recommendations
→ Proactive cold acquisition efforts
→ Engaging with 2nd order contacts in the industry
→ Harnessing word of mouth recommendations
→ Proactive cold acquisition efforts
→ Engaging with 2nd order contacts in the industry
Do we have any strategic partnerships or collaborations in place or planned for the future?
We have established a strategic partnership with Rotoclear, a leading provider of rugged cameras for CNC machines, enhancing our data collection capabilities.
We're also proud to be in collaboration with Microsoft and in discussions with potential manufacturing partners for future collaborations.
We're also proud to be in collaboration with Microsoft and in discussions with potential manufacturing partners for future collaborations.
What is your plan for international expansion?
Initially, our primary target is the DACH region (Germany, Austria, and Switzerland), where we have established a strong foothold and a deep understanding of the manufacturing landscape.
We see potential opportunities in Japan, where manufacturing industries connections are significant and can benefit from our predictive maintenance solutions.
We see potential opportunities in Japan, where manufacturing industries connections are significant and can benefit from our predictive maintenance solutions.
Are there any regulatory or compliance considerations within the manufacturing industry that your solution addresses or complies with?
Specifically, we proudly comply with two essential standards:
ISO 27001: Information Security Management
- ISO 27001 is a globally recognized standard for information security management systems (ISMS). It demonstrates our dedication to safeguarding sensitive data and ensuring the highest level of data security for our clients.
ISO 9001: Quality Management
- ISO 9001 is an international standard for quality management systems (QMS). It reflects our commitment to maintaining the highest quality standards in our product and service delivery.
ISO 27001: Information Security Management
- ISO 27001 is a globally recognized standard for information security management systems (ISMS). It demonstrates our dedication to safeguarding sensitive data and ensuring the highest level of data security for our clients.
ISO 9001: Quality Management
- ISO 9001 is an international standard for quality management systems (QMS). It reflects our commitment to maintaining the highest quality standards in our product and service delivery.