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Author: leo keenan

We’ve Never Done That Before

We’ve Never Done That Before

And that's exactly why our clients keep hiring us.

You need a product development team to develop your new idea. 

Your first instinct is that it would be ideal to find a design team that has developed a device that is similar to your new idea.

The best thing a product development partner can tell you is not “we’ve done this before.” It’s “we haven’t but we do this all the time.”

That sounds wrong. You’re about to spend six figures on engineering. You want experience. You want proof. But think about what you’re actually building. If your product could be developed by following a playbook that already exists, you wouldn’t need a development partner. You’d need a contractor. The reason you’re talking to a firm like Design 1st is because your project has something in it that hasn’t been done before. Some environment, some constraint, some combination of requirements that nobody has put together in quite this way.

The question isn’t whether your partner has seen your exact problem. The question is what they do when they haven’t. At Design 1st, that moment is the starting line. It always has been. It’s in the name.

Here are some of our firsts.

A Motel for a Drone

The first time Design 1st built an autonomous recharging station for an unmanned aircraft.

The drone flies roughly 100 miles over pipeline or infrastructure, then needs to land, recharge, upload its data, and go again. No human in the loop. Design 1st built the ground station that makes that possible. The roof doors open. A receiving platform rises to accept a vertical landing. The platform descends, the roof closes, and the onboard PLC manages the recharge cycle while pushing flight data to the cloud. All of it happens in remote locations, unattended, in weather that would keep most people indoors.

Nobody had asked us to build a drone motel before. We figured it out.

sky-x-drone-garage

Three Parts You Need a Microscope to See

The first dental product Design 1st ever worked on.

The head of a dental drill contains three components so small you need magnification to inspect the features. That’s the engineering constraint: design for manufacturing at a scale most people can’t see with their eyes, then make it reliable enough for thousands of hours of daily clinical use. Dentistry wasn’t in our portfolio when this project started. The precision engineering required to get there was.

Your industry doesn’t have to be in our portfolio yet. The engineering discipline is.

parts

A $2,000 Device That Competes with $25,000 Lab Equipment

The first time Design 1st monitored a user's breath intake and output.

Calibre is a wearable IoT device that measures breath biometrics. The challenge was building something comfortable enough to wear during activity, accurate enough to match lab-grade instruments, and affordable enough to reach a real market. Design 1st delivered on all three. The result competes with equipment that costs 12 times more.

That gap between $25,000 and $2,000 is where the engineering happened.

Surviving a Canadian Winter Underwater

The first time Design 1st worked on a product submerged in a river.

A hydrokinetic energy harvesting system needed to sit at the bottom of a slow-moving Canadian river, generate power, and keep working through an entire winter. Ice, current, debris, near-zero visibility, no access for maintenance. Everything about the environment wanted to kill the electronics. The team designed for all of it. When they pulled the unit out after a full winter, it was in pristine working condition.

Rivers don’t care about your IP rating. They test it.

Packing a Borehole

The first time Design 1st designed for a mining environment.

GeoSight needed sensors, optics, lighting, data processing, and wireless communication packed into a probe that fits inside a 2.5-inch mining borehole. That’s roughly the diameter of a tennis ball. Every component had to survive the vibration, dust, temperature swings, and impact forces of an active mine while delivering reliable data from deep underground. The mechanical and electronics teams worked in parallel to fit technology into a space that doesn’t want technology in it.

The probe works. The mine keeps running.

mining-borehole-pcb

Charging Every Walmart in Canada

The first time Design 1st added electronic charging to a locker system.

ARC Enterprise needed a mobile device charging kiosk that could deploy at retail scale. Not a prototype. Not a pilot. A production-ready system being installed in every Walmart location across Canada. That meant engineering for manufacturing volume, retail-environment durability, multiple device types, and the kind of daily abuse that comes from thousands of employees using the same piece of equipment every shift.

It’s in every Walmart in Canada now.

arc-tradeshow-charger-kiosk

What's Next

The first time Design 1st ever put a winch inside a drone is in the works right now. So is the next first we haven’t imagined yet.

That’s the nature of new product development. Your project has something in it that hasn’t been solved before. Some constraint, some environment, some combination of requirements that nobody has put together in quite this way. That’s not a risk. That’s the starting line.

We can do the job. We know because we’ve been challenged before and always came through. It’s what we love to do.

Every time was the first time.

Published on: April 15, 2026

Guide to Developing Products with Ultrasonic Wear Sensors

Guide to Developing Products with Ultrasonic Wear Sensors

Ultrasonic wear technology is revolutionizing how we maintain and monitor industrial machinery, employing advanced sensors to peer into the heart of equipment without ever needing to take it apart.
 
By leveraging the principles of ultrasonic testing (UT), these sensors provide crucial data that help prevent equipment failure, ensuring operational efficiency and enhancing safety across various industries.

Table of Contents

What are Ultrasonic Wear Sensors?

Ultrasonic wear sensors utilize high-frequency sound waves to detect abnormalities in materials or components, making them an indispensable tool in predictive maintenance strategies. They are especially useful in environments where precision and early detection of wear and tear can save significant resources.

  • Principle: These sensors operate based on ultrasonic testing (UT), a non-destructive testing technique that uses sound waves to detect material inconsistencies.
  • Utility: Primarily used in heavy machinery, these sensors are key to timely maintenance, helping avoid costly downtimes and equipment failures.
five ultrasonic wear sensors of different shapes and sizes

Why use Ultrasonic Wear Sensors?

Incorporating ultrasonic wear sensors into maintenance strategies not only extends the lifespan of equipment and ensures operational safety but also seamlessly integrates into physical products. This integration allows for real-time health monitoring of machinery, providing immediate insights without disrupting ongoing operations.

  • Seamless Integration: Ultrasonic wear sensors can be embedded directly into machinery and components, offering real-time monitoring without the need for manual inspection.
  • Proactive Maintenance: Their ability to detect early signs of wear enables proactive maintenance, drastically reducing the likelihood of unexpected downtime.
  • Safety Enhancement: The early detection capabilities of UT sensors contribute to a safer working environment by preventing equipment failures before they can cause accidents.

How Ultrasonic Wear Sensors Work

ultrasonc-wear single

Ultrasonic wear sensors work by sending out and interpreting sound waves to assess the condition of machinery without needing to touch it. Here’s a breakdown of how they do it:

  1. Emitting Sound Waves: The sensors produce high-frequency sound waves that are too high-pitched for us to hear, which can deeply penetrate the material under observation.
  2. Wave Interaction and Reflection: When these sound waves hit an irregularity, like wear or cracks, they bounce back to the sensor.
  3. Capturing and Analyzing Signals: The sensor picks up these bounced-back waves and uses advanced analysis to figure out the material’s health or thickness.
  4. Making Maintenance Decisions: By regularly or continuously checking the data, the system identifies when the wear reaches a critical level, signaling it’s time for maintenance.

Example UT Sensors in Heavy Mining Equipment

Big Dump Truck truck bulldozer vehicle

A practical application of ultrasonic wear sensors can be seen in the mining equipment industry, where heavy machinery like excavators are subject to intense wear.

Here’s how it UT wear sensors work with an excavator’s bucket, which often wears out:

  • Placement: An ultrasonic wear sensor is attached to the bucket’s edge, which is a part that gets worn down a lot.
  • Monitoring: This sensor sends out sound waves into the bucket’s edge to keep track of how thick it is and if it’s still in good shape while it’s being used.
  • Detection: The sensor figures out how worn the bucket is by looking at how long it takes for the sound waves to bounce back. The longer it takes, the more worn the bucket is.
  • Alerts: If the bucket wears down to a certain point, the sensor system will let the operators or the maintenance team know that it’s time to fix or replace the bucket before it gets too damaged.

Types of Applications for UltraSonic Sensors:

Ultrasonic wear sensors find applications in a variety of industries, demonstrating their versatility and effectiveness in monitoring equipment health.

  • Construction Equipment: Ultrasonic wear sensors are crucial for monitoring the integrity of construction equipment like crane cables and bulldozer tracks, preventing accidents and ensuring project timelines are met.

  • Mining Equipment: These sensors are used to keep an eye on the wear and tear of mining drills and earthmover tires, helping to avoid costly downtime and ensuring the safety of mining operations.

  • Medical Devices: In healthcare, ultrasonic wear sensors ensure the reliability of life-saving medical devices, such as heart pumps and diagnostic machines, by monitoring their condition for early signs of wear.

  • Smart Agriculture: Farmers use these sensors to predict maintenance for tractors and combine harvesters, optimizing harvest times and reducing the risk of machinery failure during critical agricultural operations.

  • Food Processing: In food processing plants, sensors monitor the wear on cutting blades and mixing equipment, crucial for maintaining food safety standards and production efficiency.

  • Marine Industry: These sensors play a vital role in detecting hull thinning and corrosion in ships and submarines, ensuring vessel integrity and safety at sea.

  • Rail Transport: Ultrasonic wear sensors are key to maintaining rail safety, used for inspecting the wear and cracks in train wheels and rail tracks, preventing derailments and ensuring smooth operations.

Limitations of Ultrasonic Sensor Technology:

ultrasonic-wear-sensor-failure

While ultrasonic wear sensors offer significant advantages, they also come with limitations that must be considered.

  • Surface Prep: They require clean, smooth surfaces for accurate readings, challenging in rough environments like mines or construction sites.
  • Skilled Interpretation: Data analysis demands expertise in ultrasonics, scarce in remote or technologically underserved regions.
  • Material Limits: Not effective with materials like certain composites or highly porous substances due to sound absorption issues.
  • Cost Barrier: High initial and maintenance costs make them a steep investment, particularly for smaller entities.

As an alternative, Electromagnetic Acoustic Transducer (EMAT) technology offers a solution that bypasses some of these challenges, such as the need for direct contact or extensive surface preparation, potentially providing a more versatile and less labor-intensive option in certain applications.

Ultrasonic wear sensors are transforming the landscape of industrial maintenance, offering a proactive approach to equipment management. Despite their limitations, the benefits they provide in terms of safety, efficiency, and cost savings make them an invaluable tool in the modern industrial sector.

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Published on: November 1, 2025

Industrial Design vs. Product Design: What Sets them apart?

Industrial Design vs. Product Design: What Sets them apart?

Ever wondered how a sketch becomes a sellable product? At Design 1st, we leverage both industrial and product design to make this transformation. Here’s a quick guide to understanding these crucial design disciplines.

What is Industrial Design?

Industrial Design is the craft of designing products to be mass-produced, blending art, science, and business to optimize function, value, and appearance. This discipline ensures that products not only meet aesthetic and functional needs but are also viable for large-scale manufacturing.

  • Mass Production Focus: Designs are tailored for large-scale manufacturing processes.
  • Wide-Ranging Impact: Applies to a diverse array of products, from electronics to furniture.
  • Manufacturability: Prioritizes designs that are economical and efficient to produce.
  • Function and Form: Balances aesthetic appeal with practical functionality and production requirements.
quirk logic board being used as a part of industrial design support

What is Product Design?

Product Design is dedicated to enhancing the user experience, meticulously crafting how a product is used and engaged with. It’s a process that starts with understanding user needs, then ideates, designs, and tests solutions to ensure satisfaction and usability, often within specific market niches.

  • User Experience at the Forefront: Focuses on how the product feels and operates for the user.
  • Problem-Solving Process: Starts from identifying user needs to designing and testing solutions.
  • Diverse Product Range: Encompasses everything from tech gadgets to everyday consumer items, emphasizing functionality and innovation.
  • Usability and Functionality: Designs physical products to be intuitive, satisfying, and tailored to user ergonomic needs.
design concept

Three Key Differences Between Industrial Design and Product Design


When specifically talking about design for
volume manufacturing, the distinctions between Industrial Design and Product Design become crucial:

Design for Mass Production: Industrial Designers are trained with a keen understanding of how to design products for mass production. They incorporate knowledge of manufacturing techniques, material properties, and cost efficiency into their design process to ensure that products can be produced at scale without compromising design integrity. This includes considerations for tooling, production costs, and the feasibility of manufacturing processes.

Focus and Approach: While Industrial Designers have a broad focus that includes the aesthetic, functional, and manufacturable aspects of a product, Product Designers dive deeper into the user’s interaction with the product, prioritizing usability and user experience. Product Design’s approach is more centered on solving specific user problems through design, often leading to innovation in product functionality and user interface.

Expertise and Skills: The expertise required for designing products that can be efficiently mass-produced is a hallmark of Industrial Design. This includes a deep understanding of industrial processes, material science, and engineering principles. Product Designers, by contrast, often specialize in user research, digital prototyping, and interface design, using these skills to enhance the user’s interaction with the product.

feature image chocholate truck

Three Similarities Between Industrial Design and Product Design


Despite these differences, both disciplines share several core principles in physical product design and development:

User-Centric Design: At the heart of both Industrial and Product Design is a commitment to the user. Both disciplines strive to improve the user’s life through well-designed products, whether through ergonomic solutions, intuitive interfaces, or overall product enjoyment.

Collaborative Effort: Successful product design and development require a multidisciplinary approach. Industrial and Product Designers often work closely with engineers, marketers, and other professionals to ensure that the final product is not only manufacturable at scale but also meets user needs and market demands.

Iterative Design Process Process: Both fields embrace an iterative design process, utilizing prototyping and user feedback to refine and improve product designs. This approach is crucial for addressing the complexities of designing for volume manufacturing and ensuring that the product meets both market and manufacturing requirements.

Acer-3-prototype
A Design 1st Perspective


At Design 1st, our approach integrates the strengths of both Industrial Design and Product Design, focusing on creating products that are not only innovative and user-friendly but also optimized for volume manufacturing. By blending these disciplines, we ensure that our designs are feasible for mass production without sacrificing user experience or design quality.

Our team is dedicated to transforming ideas into successful products, leveraging our expertise in both Industrial and Product Design to meet the challenges of today’s competitive market.

 

 

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Have a new product idea?

We can help take you from idea to design, prototyping, and volume manufacturing.

27 Years Experience

75+ Design Awards

1,000+ Manufactured Products

From Idea to Prototype in as Little as Six Weeks!

Ready to Start?

Published on: April 8, 2024

Navigating Edge AI for Physical Products

Navigating Edge AI for Physical Products

Artificial Intelligence (AI) is ushering in a new era of innovation, particularly with Edge AI, which allows companies to embed smart, responsive AI capabilities directly into their physical devices.

By processing data on the device itself, Edge AI enhances efficiency, privacy, and performance, making it a game-changer for product innovation. Let’s dive into how Edge AI is redefining the capabilities of physical products.

Embedding Intelligence in Physical Products

Edge AI refers to the technology that processes data on the device it’s generated, like in smartphones, IoT devices, and industrial machinery, rather than sending it to a centralized location. This approach streamlines the way we interact with data, presenting unique challenges and unlocking new advantages. Learn how Design 1st navigates the evolving Edge AI Landscape:

Table of Contents

Challenges in Edge AI Integration


When integrating Edge AI into new products, it’s crucial to be aware of several challenges that can impact performance and user experience:

  • Resource Constraints — Optimizing AI models for compact devices with limited power is a critical step towards harnessing Edge AI’s full potential.
  • Data Privacy and Security — Implementing robust security measures is essential for leveraging local processing without compromising user privacy.
  • Latency Issues — Minimizing latency through efficient algorithms ensures real-time applications run smoothly and reliably.
Advantages of EDGE AI for Physical Products


Embedding Edge AI into physical devices brings several key advantages that significantly enhance performance and user experience:

  • Reduced Latency: Local data processing cuts down latency, a game-changer for critical-response applications like autonomous vehicles and wearable IoT devices.
  • Bandwidth Efficiency: By minimizing data sent to the cloud, Edge AI conserves bandwidth and reduces the costs tied to cloud storage and communication.
  • Cost Savings: Edge computing slashes the overhead linked to cloud services by reducing the need for ongoing data transfers and storage in distant data centers.
  • Improved Reliability: With the ability to function independently of cloud connectivity, Edge AI ensures devices remain operational and reliable across various conditions.
  • Scalability 

Image: Five benefits of Edge AI

Real-World Applications of Edge AI in Physical Products


Edge AI is transforming the landscape of physical products, making them smarter and more responsive to our needs:

  • Wearable Health and Well-being: Revolutionizing the way we monitor health, Edge AI in wearables provides instant analysis of vital signs and biometric data. It extends its capabilities to monitoring the health of humans, pets, animals, and even plants, efficiently transmitting only essential information to conserve bandwidth and battery life.
  • Remote Sensors: In applications ranging from agriculture to security, Edge AI enhances the functionality of remote sensors. It enables automatic actions, like shutting off utilities during emergencies or detecting security breaches, offering rapid responses and valuable insights in real time.
  • Anomaly Detection/Preventive Maintenance: Edge AI is crucial in industrial settings for early detection of wear and potential failures. This prevents costly downtime and maintains operational efficiency. This predictive maintenance capability ensures smoother, uninterrupted industrial processes.
  • Fast Activation and Battery Saving:: Through technologies like wake word detection and gesture recognition, Edge AI improves device usability and energy efficiency. It supports a wide array of applications, from inventory management to quality control in manufacturing, by enabling quick activation and smart monitoring without excessive power use.
  • Signal Enhancement and Smart Processing: By refining and augmenting data directly on devices, Edge AI significantly enhances the quality of information derived from audio and visual inputs. This includes noise reduction, signal enhancement, and real-time content generation, like blurring backgrounds for privacy or translating spoken language instantly, making devices more versatile and user-friendly.

Image: Industries and applications of Edge AI

Examples of Industries Embracing Edge AI

 

Discover how Edge AI is transforming industries by integrating intelligence directly into physical products:

  • Logistics and Transport: Revolutionizing logistics with Edge AI for seamless real-time tracking and autonomous vehicle navigation, streamlining data processing for efficiency.
  • Intelligent Sports Wearables: Edge AI in sports wearables offers instant performance feedback, risk assessments, and training enhancements, leveraging sensor analytics.
  • Retail Stores: Transforming the retail experience with Edge AI for tailored recommendations, streamlined inventory management, and faster checkout processes.
  • Urban Mobility and Traffic Control: Improving traffic management and autonomous vehicle safety in urban settings with Edge AI, utilizing advanced data analytics.
  • Healthcare Devices: Edge AI plays a crucial role in wearable healthcare devices, focusing on sensor integration and efficient AI algorithms for privacy-respected real-time monitoring.
  • Consumer Electronics: Elevating user experiences in consumer electronics like smartwatches and home assistants with Edge AI, emphasizing low power use and swift processing.
  • Industrial Equipment & Manufacturing: Edge AI is reshaping manufacturing with predictive maintenance and quality control, enhancing operational efficiency and addressing integration challenges.
Cloud Computing vs. Edge AI
edge ai vs. cloud

Edge AI enables processing and decision-making at the source of data generation, offering a tailored solution for physical devices that operate with immediacy and autonomy, in contrast to Cloud Computing which relies on centralized data processing. The main benefits of using Edge AI over Cloud Computing include:

  • Latency: Edge AI minimizes the delay between data creation and action by processing information directly on the device, crucial for time-sensitive operations where even milliseconds matter.

  • Security: By processing data locally, Edge AI reduces the exposure to potential vulnerabilities that can occur during data transit to and from the cloud, thereby safeguarding sensitive information inherent in physical devices.

  • Power Efficiency: Physical devices leveraging Edge AI can operate with greater power efficiency since they don’t rely heavily on long-distance data transmission, which can be energy-intensive, thus extending the operational time of devices on a single charge.

  • Real-time Operations: For devices that need immediate response, such as autonomous vehicles or industrial automation, Edge AI ensures that real-time data is acted upon instantly without the inherent lag of cloud-based decision-making processes.

The table below compares the main features of Edge AI vs. Cloud Computing for usage with physical devices.

Features

Edge Computing

Cloud Computing

Latency

Low

High

Bandwidth Required

Low

High

Processing Power

Low

High

Storage Capacity

Low

High

Security

High: no transmission

Medium: cloud backup

Cost

Medium

High

Scalability

High: number of devices

High: Processing/storage

Context Awareness

High

Low

Power Efficiency

High

Low

Maintenance & Upgradeability

Medium

High

Where Design 1st Can Help

 

Navigating the complexities of Edge AI development can be daunting, but Design1st is here to streamline the process, reduce risks, and accelerate your journey to market. With over a decade of experience and a full-service team of experts, we provide a safe and efficient path to bring your Edge AI product from concept to volume production. Here’s how we can help:

  • Optimizing AI Models: Our team specializes in refining AI solutions for physical products with limited resources, ensuring optimal performance while mitigating risks associated with power consumption and processing capabilities.
  • Accelerate Your Path to Market: Leveraging our expertise and efficient processes, we expedite your product development timeline, enabling you to launch your Edge AI solution faster and stay ahead of the competition.
  • Commercialize Your R&D: We assist in commercializing your research and development efforts, helping you turn your Edge AI innovations into market-ready products quickly and efficiently.
  • Prototype Fast: Using rapid prototyping techniques, we iterate and refine prototypes swiftly, allowing you to validate your Edge AI concept and make informed decisions early in the development process.
  • End-to-End Product Development: From concept to volume production, Design1st offers comprehensive support, ensuring a smooth and successful transition from idea to market-ready solution while minimizing risks and maximizing speed to market.

What’s Next?

Edge computing is reshaping the landscape of AI, offering unique challenges and unmatched advantages. Partnerships with seasoned experts like Design1st are essential for navigating this transformative journey. Together, we unlock the full potential of edge AI, ushering in a new era of smarter, more efficient technologies. Ready to explore the possibilities? Let’s embark on this journey together.

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Have a new product idea?

We can help take you from idea to design, prototyping, and volume manufacturing.

27 Years Experience

75+ Design Awards

1,000+ Manufactured Products

From Idea to Prototype in as Little as Six Weeks!

Ready to Start?

Published on: April 1, 2024

How to Sell Your Invention to Canadian Tire

How to Sell Your Invention to Canadian Tire

Canada’s iconic “we-sell-everything” retailer, Canadian Tire, is launching thousands of new products, relying on local inventors who understand the market, weather, economy, and unique needs of Canadians to fill the gap, embodying its mantra “Tested for life in Canada.”

Highlights:
  • Canadian Tire is actively seeking new innovative products to enhance its portfolio, focusing on the Canadian lifestyle.
  • Private-label brands are central to Canadian Tire’s strategy, emphasizing unique innovations exclusive to the retailer.
  • A new straightforward process for inventors and companies to bring their products to the Canadian market through Canadian Tire
  • Design 1st – Canada’s largest product team, helps inventors develop their ideas for volume manufacturing for partnerships with Canadian Tire
inside canadian tire edmonton showcase store display of products
Image: Canadian Store in Ottawa, Ontario

What Types of Products is Canadian Tire Looking For?

Canadian Tire seeks products that address the unique challenges of Canadian living, from the harsh winters to the diverse outdoor activities enjoyed across the country. If your invention simplifies daily life, increases safety, or adds enjoyment in a distinctly Canadian way, it could be the perfect fit for Canadian Tire. 

Tip: Explore Canadian Tire’s “Consumer Brands” division webpage to explore all the in-house brands Canadian Tire currently sells. Will your product fit into one of these? What is missing? Build a story angle that showcases your product’s value.

Image: Canadian Tire Consumer Brands

Why Should Inventors Care?

Partnering with Canadian Tire offers a transformative opportunity for your invention, turning it from a concept into a household name across Canada. It’s a chance to make a significant impact on the daily lives of millions, providing solutions that resonate with the unique Canadian lifestyle. Your product could become an essential part of homes nationwide, cherished for its utility and innovation.

Plus, Canadian Tire has over 500 stores across Canada alongside a robust distribution network.

left: exterior of the new canadian tire store in ottawa. right: rows of shelves from a second floor view
Image: New Canadian Store Design

How Catch Canadian Tires Attention With Your Idea?

To catch Canadian Tire’s attention, your product must innovate or significantly improve upon existing solutions, addressing everyday problems in ways previously unimagined. Products that offer a unique benefit or solve a problem in a new way are especially appealing. 

Most importantly, have a well-thought-out design and path to volume manufacturing for your product. Major retailers, like Canadian Tire, need new products to sell now. A rough product idea will not cut it, development time times a minimum of one year. So start now!

Canadian Tire Inventor Success Stories:

Rumidifier and Wheel Nut Caddy, Ottawa Inventors.

Two Ottawa-based inventors caught the attention of Canadian Tire with unique, simple product innovations that were fully developed, tested, and ready for scale manufacturing. 

Rumidifier: an eco-friendly, zero energy home humidifier

wheel nut caddy on wheels

Wheel Nut Caddy: storage for wheel nuts (bolts) with the off-season wheels

How Can You Get Your Invention into Canadian Tire?

 
Step 1: Register Your Company

Start by registering your company with the Canadian Tire Vendor Gateway. This crucial first step allows you to introduce your product to Canadian Tire. Follow the provided directions carefully and wait for your registration confirmation.

Step 2: Participate in a Sourcing Review

Next, participate in a sourcing review, which includes specific training and documentation. This step is designed to prepare you for presenting your product to Canadian Tire, moving you closer to potential selection.

Step 3: Negotiate Your Contract

If Canadian Tire shows interest in your product, you’ll enter negotiations on contract details, such as costs and discounts. This is your opportunity to finalize the details and secure a spot for your product within their offerings.

Step 4: Onboarding

After selection, you’ll undergo an onboarding process to familiarize yourself with Canadian Tire’s operational procedures. This ensures a smooth transition for your product into the market, setting the stage for a successful launch.

April 29, 2020 - Dartmouth, Canada - Cargo containers stacked high at a Canadian Tire Distribution Centre/Warehouse located in Burnside Industrial Park.
Image: Canadian Tire Shipping Containers

Getting Help Bringing Your Product Idea to Volume Manufacturing

If you’re in the thick of product development and encounter obstacles, remember that assistance is within reach. Collaborating with experts who excel in scaling products to mass production is pivotal. These specialists provide support in navigating manufacturing challenges, ensuring your invention aligns with Canadian Tire’s quality standards and market expectations.

Act now—your invention could be the next big hit at Canadian Tire.

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Have a new product idea?

We can help take you from idea to design, prototyping, and volume manufacturing.

27 Years Experience

75+ Design Awards

1,000+ Manufactured Products

From Idea to Prototype in as Little as Six Weeks!

Ready to Start?

Published on: February 26, 2024

Navigating 20 Years of AI with 10 Groundbreaking Trends

Navigating 20 Years of AI with 10 Groundbreaking Trends

Discover the ten key AI trends impacting the future of product development.

In 20 years, AI has shifted from being a tech outlier to a central player in shaping product development’s trajectory. This piece sheds light on the top 10 groundbreaking AI trends redefining our digital age and offers a peek into the future.

Table of Contents

Trend #1: Machine Learning  – The Heartbeat of Modern AI

In the vast world of Artificial Intelligence, Machine Learning (ML) algorithms are pivotal. Imagine these algorithms as either a ‘White Box’ – where we can see and understand the inner workings – or a ‘Black Box’ – where the internal processes remain hidden, and we primarily see the output.

What’s interesting is how these algorithms learn from data. Just like we might guess the next move in a game based on past plays, ML algorithms predict outcomes using a technique called ‘backpropagation’. Think of backpropagation as the algorithm’s way of retracing its steps, refining its guesses until it gets them right.

Here’s a brief look at the types of learning these algorithms use:

  • Supervised Learning: Like a student with a teacher, it uses known data to predict outcomes.
  • Semi-Supervised Learning: Combines the methods of the student and the explorer, using both known and unknown data.
  • Self-Supervised Learning: An independent learner that sets its own questions based on the data it sees.
  • Unsupervised Learning: The explorer, discovering patterns on its own, often used in visual systems and making recommendations.
  • Reinforcement Learning: Learns through trial and error, like playing a game and adjusting strategies for the win.
  • Deep Reinforcement Learning: Uses deep thinking (or complex processing) to further refine the game strategies.
  • Incremental Learning: Continuously evolves by incorporating new data, similar to how we never stop learning.
  • Transfer Learning: Takes knowledge from one area and applies it to another, like using basketball skills in a netball game.
types-of-machine-learning

Machine Learning is more than just tech jargon; it’s the magic behind today’s AI innovations, making it crucial for tech startups and product developers to understand.

Trend #2: Navigating the World of Artificial Neural Networks (ANN)

 

Ever wondered how machines can recognize faces or predict what song you’ll love next? Enter the world of Artificial Neural Networks (ANN).

  • What’s an ANN? Think of ANNs as the brain of a machine, made up of connected nodes (like our brain’s neurons) that process information.
  • Layers: These networks have different layers – input (where they get the data), output (the final result), and some hidden layers in between (where the magic happens).
  • How Layers work: Each node in these layers does a mini job like filtering or multiplying data. Together, they identify patterns and make sense of the information.
  • ANN Learning Process: Just like how we learn from our mistakes and successes, ANNs have a two-step dance – forward propagation (making an initial guess) and backpropagation (adjusting based on how right or wrong they were).
  • Legacy: While ANNs sound futuristic, they have a rich history. The first basic neural network was introduced in 1957 by a visionary named Frank Rosenblatt.
ai-artifical-neural-networks

There are various types of these neural networks. Some of the big names include:

  • CNN (Used commonly for images)
  • RNN (Great for sequences, like videos)
  • DBN, GAN, GNN, and GCN (Others with specialized functions)

Did you know? By 2023, we’ve discovered over 100 different types of neural networks!

Trend #3: The Expanding Horizons of Deep Learning

Deep learning is not just another buzzword; it’s shaping the future of Artificial Intelligence (AI). Picture this: a supercharged version of neural networks, sometimes comprising an incredible 150 layers. These computational structures sift through vast amounts of data and, akin to refining a skill, utilize a method known as backpropagation to perfect their functions.

Key Impacts of Deep Learning:

  • Generative AI: Pioneering innovations like GPT-4 for text creation, vibrant chatbots, artistic AI renditions, and even coding assistive tools such as Microsoft’s GitHub Copilot.
  • Image Manipulation: Witness on-device enhancements with technologies like Pixel 8 and those embedded in iPhones.
  • Recognition Tools: Handwriting deciphering, voice commands with assistants like Alexa, or the seamless conversion from speech to text – all thanks to deep learning.
  • Image Analysis: Systems that categorize images (from human detection to forest fire management) and others that recognize intricate details within them, including form scanning for efficient data entry.
  • Information Tech: Amazon’s eerily accurate product suggestions or platforms that provide detailed answers owe their capabilities to deep learning.
  • Future Transportation: The drive towards self-driving cars, real-time language translations, and even assisting in complex tasks such as chip designing.
  • Medical Advancements: Detecting medical conditions from images, providing health recommendations, groundbreaking drug discoveries, and predicting protein structures.
  • Biometric Evolution: Beyond the usual fingerprint and facial recognition on phones, deep learning powers specialized systems that identify individuals by unique traits, from their walk to their voice.

With deep learning orchestrating advancements across diverse sectors, its influence is destined to grow, charting new territories in the tech landscape.

Trend #4: The Rise and Evolution of Conversational Technologies

Conversational tech, whether chatbots or advanced agents, are defining the next frontier in user interaction. The journey’s just begun.
  • Chatbots: Text-based helpers powered by machine learning, evolving through each interaction.
    • Example: Website Chatbots
    • Core: Natural language processing (NLP) to generate responses.
  • Virtual Assistants: Voice-oriented aides remembering past interactions to offer better insights.
    • Example: Amazon Alexa, Siri
    • Core: Voice interaction, contextualized responses.
  • Conversational Agents: Text wizards that dive deep into conversations to address user problems.
    • Example: Chat-GPT, Bing-GPT
    • Core: Advanced text generation, problem resolution

Table 1: Evolution of Voice AI Virtual Assistants

Virtual Assistant Company Year Capabilities
Siri Apple 2011 Advanced speech recognition tech.
Alexa Amazon 2014 Wake word-activated, preset functions.
Cortana* Microsoft 2015 Bing search-powered (*now discontinued).
Google Assistant Google 2016 Multimodal: Text, GUI, Voice.
Bixby Samsung 2017 Successor of S Voice Assistant.

Table 2: Modern AI Conversational Assistants

Conversational Agent Company Year Capabilities
Chat GPT OpenAI 2022 GPT-3.5 AI-backed chatbot.
Bing Chat Microsoft 2023 GPT-4 AI, custom site sources.
Bard Google 2023 Transitioned from LaMDA to PaLM 2.
Alexa Enhanced Amazon 2023 LLM hallucination guardrails.
Google Assistant (w/ Bard) Google 2024 Bard’s generative reasoning for Android & iOS.
Siri (w/ Apple GPT/Ajax) Apple 2025 Experimental generative AI; possible Siri extension.
From predictive text to sophisticated LLMs, conversational technologies have revolutionized our interactions. The attached timeline offers a snapshot of this transformative journey in generative AI.
Image: History of AI Text Generation 1995 - 2023

Trend #5: Progress and Potential of Large Language Models

Introduction: The universe of AI has been swept by the storm of Large Language Models (LLMs). These massive computational brains, trained on extensive datasets, are now at the forefront of generating, translating, and understanding human language with unprecedented proficiency. What’s an LLM? Google describes an LLM as “A statistical language model, trained on a massive amount of data, capable of performing numerous natural language processing (NLP) tasks. Deep learning architectures, notably the Transformer model introduced by Google in 2017, serve as its backbone, empowering it to decipher and generate vast amounts of text.” LLM in Action: A Snapshot Generative Pre-trained Transformers (GPT) epitomize LLMs. Training an LLM is no small feat—it’s a laborious process, often spanning over a year. What makes them particularly intriguing is their “Black Box” nature, where these AI systems employ profound learning from colossal datasets to comprehend and produce fresh content.

Table 3: Noteworthy LLMs: A Brief Catalog

LLM COMPANY YEAR SIZE CAPABILITIES TYPE
GPT-2 OpenAI 2019 1.5B Basic text based Generative AI capabilities / conversational skills Proprietary
GPT-3 OpenAI 2020 175B Advanced text based Generative AI capabilities / conversational skills Proprietary
GPT-3.5 OpenAI 2022 175B Optimized for ChatGPT – Comprehend complicated linguistic structures and provide effective replies Proprietary
GPT-4 OpenAI 2023 1.5 Trillion Most advanced text based Generative AI capabilities / conversational skills Proprietary
Orca Microsoft 2023 13B Orca is built on top of the 13 billion parameter version of LLaMA, small enough to run on a laptop Open Source
Bing GPT Microsoft 2023 Microsoft Version of Chat GPT-4 Proprietary
RankBrain Google 2015 N/A First time the Google search engine’s algorithm adopted artificial intelligence to understand content and search using Machine Learning only Proprietary
BERT Google 2019 110M – 340M Increases the Google search engine’s understanding of human language by understanding the relationships between words in a sentence Open Source
T5 Google 2020 11B Research/Demo purposes > Unified Text-to-Text Transformer Open Source
FLAN-T5 Google 2022 11B Research/Demo purposes > Enhanced T5 transformer, better at everything Open Source
FLAN-UL2 Google 2023 20B Research/Demo purposes > Enhanced FLAN-T5, upgraded pre-training procedure dubbed UL2 Open Source
LaMDA Google 2021 137B Basic conversational skills Proprietary
LaMDA 2 Google 2022 137B Advanced conversational skills > trained on anonymous conversations providing enhanced capabilities for natural dialogue Proprietary
PaLM Google 2023 540B Advanced conversational skills / Reasoning tasks, code, math, Classification and question answering Proprietary
PaLM 2 Google 2023 1.3 Trillion Most advanced conversational skills / Commonsense reasoning, arithmetic reasoning, joke explanation, code generation, translation, robotics Proprietary
Gemini Google 2024 1.8 Trillion ??? Gemini is expected to succeed PaLM-2, Announced at Google IO Proprietary
The rapid evolution and diversification of LLMs signify a remarkable chapter in the annals of technology. As they continue to refine and expand, the horizon for what’s possible in the realm of language processing and generation looks boundlessly promising.

Trend #6: The Shift to On-device AI – PCs & Smartphones

We’re seeing a technological shift where AI processing is transitioning from cloud-based systems to personal devices like PCs and smartphones. These devices are now equipped to handle Machine Learning algorithms and basic inference engines, including the more compact LLMs. This transition reduces the need for cloud computing and boosts user privacy.

Key Players in the On-Device AI Shift:

 

A) Google’s Pixel 8: Harnessing the “Tensor G3 Processor” (2021-2023)

  • Photo Features: Best Take, Face Swap, Magic Eraser, Magic Editor, Cinematic Blur, and exclusive Pixel 8 Pro features like Image Zoom with Interpolation.
  • Audio Innovations: Audio Magic Eraser for background noise removal.
  • Text-based Applications: Automated transcription of voicemails, Automatic Call Screening, and Smart Replies via Gboard Keyboard.
  • Hybrid AI (2024): Integration of Google Assistant with Bard, offering page summarizations and Video Boost with features like Night Sight and Video HDR exclusive to Pixel 8 Pro.
  • Phone Enhancements: Call Screening with transcription, AI-driven responses, and Google Watch 2 support introducing Call Screening Button with transcription.
  • Other Notable Features: Google Gboard and Apple QuickType advancements offering better text suggestions.

B) Apple’s  iPhone 15: Powering Through “Apple Neural Engine/ANE” (2017-2023)

  • Photo Capabilities: Cinematic Mode, person, dog, and cat detection, and US-exclusive Visual Look Up for object and scene recognition.
  • Text Features: Live Text for image-to-text conversion, automated transcription of voicemails, and an enhanced predictive text recommendation system.
  • Other Significant Features: Offline Siri operations, Face ID, on-device search, the revolutionary Personal Voice feature catering to ALS patients, and Voice-isolation to mute background noises.

C) Qualcomm’s Vision: Chip Platform With Built-in AI Processor:

  • Boosts VR and action cameras with powerful recognition capabilities and premium 4K video playback.
  • Combines high performance, low power consumption, and adaptability for a range of AI tasks.

As on-device AI continues its growth trajectory, it promises enhanced user experience, faster response times, and increased privacy. This shift from cloud to device not only signifies technological advancement but also a move towards democratizing AI, making it accessible and efficient for all.

Trend #7: Hybrid AI – Merging the Power of Cloud and Devices

Hybrid AI is the next big step in technology, blending the vast capabilities of cloud computing with the convenience of our everyday devices. In simpler terms, it’s like having the strength of a supercomputer right in your pocket.

Google spearheaded this movement with the Pixel 8 Smartphone and even brought some features to iPhones through Google Apps. Apple and Microsoft are not far behind, gearing up their devices to leverage Hybrid AI. For instance, come 2024, the Google Assistant with Bard will be available on both Android and iOS, using advanced AI to summarize web pages instantly.

Additionally, Microsoft is rolling out “Copilot”, which enriches their products with smarter features:

  • Windows 11: A quick “Windows-C” command brings up Copilot.
  • Bing: Upgraded for a smarter search on Android and iOS.
  • Edge: Offers a tailored browsing experience.
  • Microsoft 365: Smarter document understanding and collaboration.
  • Microsoft Office: Assistance with text in Word, formulas in Excel, and presentations.
  • Paint: Teams up with DALL-E 3 for artistic creations.

The fusion of Hybrid AI, combining cloud strength with device agility, will revolutionize product development. Designers and engineers can anticipate swifter prototyping, enhanced device intelligence, and more personalized user experiences. This transformative shift ensures that future connected devices are smarter, faster, and more attuned to user needs.

Trend #8: AI Safety and Decoding the ‘Black Box’

Understanding and ensuring the safety of AI has taken center stage. With technological marvels increasing daily, it’s vital to ensure they’re transparent and trustworthy.

ai-safety-joke

Spotlight on Anthropic: This standout leader in the AI safety realm has caught the tech giant Amazon’s attention. Their partnership is a testament to the importance of AI safety.

Guardians of AI: Multiple global organizations, like OECD, GPAI, and NIST, have risen to the challenge. They’re establishing standards and best practices to ensure that AI technologies are both innovative and responsible.

Mechanistic Interpretability Unveiled: Sounds technical? At its core, it’s about dissecting AI – understanding its inner workings. Think of it as a peek behind the curtain of a magic show, revealing the secrets of how the trick is done. By breaking AI processes down into circuits and algorithms, we can shed light on the often termed “Black Box” of neural networks.

Research at the Forefront: Many minds, especially from Anthropic, are diving deep to ensure the safety of AI. They’re committed to ensuring that as AI evolves, it remains a tool we can understand, trust, and control.

What to dig deeper into AI Safety? Take a look at these resources:

As AI powers ahead, there’s a concerted effort to make sure it’s a journey we can all follow, trust, and feel safe with.

Trend #9: Pioneering AI Hardware: Accelerators & Supercomputers

The Surge of AI Supercomputers and Accelerators

The world of AI is not just about algorithms and data. The hardware that powers these intelligent systems is evolving rapidly, driving both innovation and efficiency.

Precision Breakthrough: IBM’s revelation that AI predictions remain consistent with reduced bit precision paves the way for custom AI Accelerator chips. Simplified, it means we can achieve powerful results with less computational “heft.” 

Future Glimpse: IBM’s Analog AI Accelerators, using Phase Change Memory, are tipped to be the game-changers, promising powerful computation with minimal energy. 

The Cerebras Marvel: Envision a chip with 2.6 trillion transistors and a whopping 850,000 cores! And the potential to scale up to 13.5 million cores? That’s Cerebras for you, revolutionizing the AI hardware landscape. 

The AI Hardware Galaxy:

  • Amazon: Supercomputers AWS Trainium & AWS Inferentia2; Processors Trainium & Inferentia2
  • Google: Supercomputers TPUv4 & TPUv5; Processors TPU/Tensor Processor Unit
  • IBM: Supercomputer Vela; Processors AIU/Artificial Intelligence Unit
  • Microsoft: Relies on NVIDIA Clusters; Processor A100
  • NVIDIA: Leaders with Supercomputers Helios & H200 SuperPods; Processors H200, H100, & A100
  • Apple: Pioneers with Apple Neural Engine/ANE; Processors A17, A16 & A15 Bionic Chips
  • Baidu: Minwa Supercomputer; Featuring 72 AI processors & 144 GPUs
  • Cerebras: Supercomputer Andromeda; Processor WSE-2/Wafer Scale Engine 2
  • Graphcore: The Good Computer; Processors GC300 MK3 & GC200 Colossus
  • Meta: RSC/Research Supercluster; Processor MTIA Accelerator
  • SambaNova: DataScale SN30; Processor Cardinal SN30
  • SpiNNaker: SpiNNcloud; A Neuromorphic AI Accelerator
  • Tesla: Supercomputer Dojo; Processor D1 Chip, compatible with Open-Source RISC-V

In essence, as AI continues to redefine industries and lives, the silent heroes powering this transformation are these innovative accelerators and supercomputers. Their advancements promise a future where AI is faster, more efficient, and integrated into every facet of our existence.

Trend #10: Leaders and Innovations Transforming AI Today

Artificial Intelligence (AI) and Machine Learning (ML) have become indispensable in the current business landscape. As technology matures, we’re witnessing an unprecedented acceleration in AI/ML development, empowering businesses to create more sophisticated and innovative solutions. Here’s a breakdown of the current state and trajectory of AI and ML for the modern business:

Table 4: Key AI/ML Development Tools

Tool Description
PyTorch Widely adopted for its Python interface; a powerhouse for deep learning projects.
Microsoft Azure Tools Suite providing functionalities like Cognitive Services, ML Services, and AutoML.
Amazon Bedrock A fully managed platform bolstered by foundational services, facilitating streamlined AI/ML development.
Google TensorFlow & JAX Offer interfaces in Python, C++, and R; backed by giants like Google Brain, DeepMind, and Apple.
NVIDIA CUDA Pivotal for parallel computing on GPUs; a testament to NVIDIA’s dominance in AI.
Caffe Versatile for various AI tasks; integrates with Nvidia cuDNN and Intel MKL.

Understanding AI Training and Inference:

  • Training: This is where AI models learn. With the advancement in technology, even massive datasets can be processed within a year, powering robust LLMs.
  • Inference: Post-training, the AI model is put into action. As AI continues to evolve, the demand for inference escalates, spotlighting the importance of hybrid AI for scalable generative AI solutions.

Market Influencers: Did you know that 70% of all AI chips come from NVIDIA? Their CUDA platform’s expansive developer base accentuates the preference for NVIDIA GPU resources, especially in the Cloud.

Power Players in AI & Cloud Synergy: The fusion of AI and Cloud is redefining the business ecosystem. Let’s evaluate the “Big 6” companies at the forefront of this transformation:

Table 4: Power Players in AI & Cloud Synergy

Company Key Contributions/Assets
NVIDIA Known for custom silicon and extensive GPU lineage; preferred choice for AI training; partnerships with Microsoft, Amazon, and Google.
Alphabet/Google Acquisitions like DeepMind and tools such as TensorFlow; seamless integration of AI into daily digital experiences (e.g., Google Translate, LaMDA).
Amazon Pushes the AI envelope with tools like Amazon Bedrock and investments in companies like Anthropic; also dominates in the e-commerce realm.
Apple Relatively new to the AI supercomputing arena but shows promise with systems like Ajax and Apple-GPT.
Microsoft Collaboration with OpenAI, tools like Azure AI, and the intent to embed AI capabilities into daily computing applications (e.g., Outlook, GitHub).
IBM Legacy in tech innovation; offerings like Watsonx and unique hardware solutions such as phase-change memory for AI acceleration.

As AI tools transition from research labs to the forefront of business, the way we design and develop products is undergoing a radical shift. Following these AI trends isn’t just smart – it’s essential for seizing the bright opportunities of tomorrow’s innovative devices.

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Published on: October 26, 2023

Design 1st – Color Teller Connects with Stevie Wonder

Design 1st – Color Teller Connects with Stevie Wonder

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“As a messenger of peace I want to encourage countries throughout the world to find ways of subsidizing technology and ways of making the world more accessible to those with disabilities.” – Stevie Wonder

Advances in technology and innovative product development have made Stevie Wonder’s message of accessible technology for the disabled – a reality. Selective material sourcing, user-centric design methods and innovative technology have all been combined to produce useful and empowering devices for the impaired.

A recent 2010 NFL Superbowl Volkswagen commercial highlighted the latest advances in technology for the visually impaired. In the ad featuring Stevie Wonder, a variety of people in different driving situations are playing “Punch Buggy”, where the first person to see a Volkswagen playfully slugs his or her friend. The twist comes when Stevie Wonder correctly identifies the color of a nearby Jetta and slugs a surprised Tracy Morgan. To find out how Stevie did it, watch here:

“Just because a man lacks the use of his eyes doesn’t mean he lacks vision.”  
– Stevie Wonder

Brytech’s Color Teller˙ provided a substitute for Stevie Wonder’s vision in the commercial allowing him to accurately determine the color of the car through the push of a button. The “Color Teller” device announces colors, shades and whether a light is on or off to the user. Design 1st was the physical product design and development team behind the product, working closely with the electronics and business team at Brytech.

Working with the blind requires designing with your eyes closed. The Design 1st team had to think blind to come up with the shape of the object that deals with getting it out of a pocket or purse, tethering the product for security, comfort in the hands and simplicity of use. Simple can be the best thing ever for those with vision disabilities ˆ a must have. To come up with the right shape a dozen shapes from wallet rectangles to long tubes were created and reviewed with a group of blind volunteers. From this feedback the final shape was determined and the complex color measuring window was developed with keys, speaker and accessible battery door that could be used without sight. The Color Teller features a single button operation that never needs to be switched off, multiple language selections, different volume levels and a talking battery monitor. Buy one at www.brytech.com

We’re proud that our partnership with Brytech brought an innovative and highly useful product to market. A product that is being recognized for its vision.

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Published on: July 20, 2023

New Way to Shovel Snow – Heatstone™

New Way to Shovel Snow – Heatstone™

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Santa can bring you a new way to shovel snow off the walks – from your living room! Collaborating with the Design 1st team, a Toronto Inventor has been busy creating a new product for the northern markets where an aging population will experience more back injuries by snow shovelling walks and driveways.

Introducing HEATSTONE™ a new way to get rid of unwanted snow from your home, in the market since 2012!

heatstone winter snow melt

Consiglio, a Toronto based inventor, approached Design 1st with the idea to build outdoor radiant flooring with concrete patio stones.  Seeing an opportunity to increase winter safety, comfort and convenience Consiglio engaged with the Design 1st team and began the product development process. From the initial first meeting a year ago, to introducing the product to the marketplace, a creative engineering and design team was needed to work alongside Consiglio on his first journey as an inventor.

The first stage for a design team working with new ideas and inventions is simply to listen. From there we help determine all the things that are important to the success of the product.  Ol’ Saint Nick makes a list and checks it twice; the Design 1st team uses the same process when designing product concepts.  First we get creative, imagine possibilities and illustrate the concepts with sketches, images and models.  It is good practice to outline requirements that meet both our clients and their end customers’ needs. For Consiglio this included safety, ease of installation and maintenance of his radiant flooring concrete patio stones. Safety wise, the patio stones had to clear pathways of ice and snow while meeting reglatory compliance issues in North America.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

The patio stones will be selling in local commercial hardware stores so ease of installation was a must, as many clients would be building the outdoor radiant flooring themselves.  Winter seasons vary from one year to the next so maintenance and quality were also key design requirements.  No better walkway for ruggedness across the seasons than decorative concrete stone. All the electronics are well protected inside the stones so mother nature and garden tools cannot get  at them.

From there the Design 1st team creates 3D models of the concepts checking over the details and ensuring every surface, edge movement and feature is resolved with critical consideration of the product image, human interaction, materials and manufacturing requirements.

From idea to physical working models, once the technical details and product requirements are met, modelled and reviewed – the 3D virtual design concept is sent Santa’s workshop to be assembled into a working prototype.  In a similar fashion to Santa’s North Pole facilities Design 1st’ onsite workshop has all the tools to build technical products including CNC Machines, micro-saws, cutting machines, epoxies, batteries, bolts, wires, hardware and building materials of all sorts.

For Consiglio’s outdoor heated patio stones the prototyping process involved creating working concrete stone patio blocks that were tested, modified and delivered on the promise to melt the snow as it falls or even after it accumulates.  After some minor tweaks the new product introduction (NPI) phase commenced where the Design 1st engineering team documented every screw, part, assembly and surface treatment in preparation for manufacturing.

Now as Consiglio moves into production cycle the Design 1st acts as a guide helping provide manufacturing introduction, design support, quality control and identifying opportunities for cost savings as the product facilities make last minute improvements.  This holiday season when the snow begins to fall, ice begins to form and sleigh bells are ringing the gifts from Santa’s workshop will put a smile on children’s faces and patio stones designed in our workshop will put a smile on yours!

A joyous Christmas & a Prosperous New Year to All

~Design 1st staff

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Published on: July 20, 2023

ING Robotic Aviation Read for Takeoff

ING Robotic Aviation Read for Takeoff

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What happens when you combine robotics, airplanes and a dash of aesthetic mechanical innovation?

Well, with the right team and experience you may end up re-inventing aviation with unmanned aircraft that deliver airborne sensing solutions in the fields of surveying, environmental monitoring, and critical infrastructure inspecting.

ING Robotic Aviation’s Serenity UAV

ING Robotic Aviation is a Design 1st client whose disruptive aviation technology is shaking up industries and forcing operational change across the globe. The company has found the right mix of innovation, sensing solutions and aesthetic design that has allowed them to put the right information, into the right hands, at the right time. ING’s fixed-wing “Serenity“ Unmanned Aerial Vehicle (UAV) aircraft was recently purchased by IFMS, a Chilean company to help fight forest fires. While ING’s rotary-wing, “Responder” UAV was purchased last week by a client for surveillance operations in East Africa.

ING Robotic Aviation’s Team with Responder UAV

To find out more about ING Robotic Aviation and how their technology is being used in multiple industries across the globe, checkout their webpage at www.ingrobotic.com.

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Published on: July 20, 2023

Ottawa Personal Trainer with a Product Idea

Ottawa Personal Trainer with a Product Idea

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After meeting Guy Murray for the first time you’re guaranteed to hear at least one product idea. The Ottawa personal trainer embodies the definition of an inventor and has used his ingenuity to create several products over the years.

In early 2010, Guy came up with one product idea he knew would take more than elbow grease to bring to life. After contacting several machine shops, engineers and prototype outfits he stumbled across Design 1st online.  Quickly a meeting was set up, budget identified and a team put in place. Over the next six months the design team moved Guy from Idea through to engineering and prototyping.

The results following the early stages of product development were a finalized concept, detailed design and a  CAD rendered video showcasing the new benchpress revolution called PowerPress:

This followed with a low volume production run of the PowerPress and various product trials. The most popular trial was at the 100% Raw Bench Press Provincials in Ottawa where the PowerPress was tried out by dozens of conditioned Powerlifters. The consensus — they loved it, PowerPress was a hit.

After product trials Guy took the feedback and put together a professional commercial video detailing the mechanics, technology and benefits of the PowerPress.

Now moving into 2014 Guy is nearing the end of the product design process and is preparing to sell and distribute the PowerPress. While currently a hit at his private gym, Studio Elite Fitness – Guy  is hoping other gyms’ will have a chance to reap the benefits of his innovation.

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Published on: July 20, 2023