Customer Renews Contract as Cyngn's Autonomous Vehicles Yield 4x Efficiency Gain
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Insights
Integrating autonomous vehicles into USC's operations likely offers a significant enhancement in supply chain efficiency. Self-driving industrial vehicles can reduce human error and increase productivity by operating 24/7 without the need for breaks, which is crucial in a 100,000-square-foot facility. The deployment of Cyngn's Enterprise Autonomy Suite could also lead to a reduction in soaring labor costs by automating tasks that were previously labor-intensive. However, the transition to automation requires an upfront investment and there may be challenges such as integration with existing systems and workforce adaptation.
Additionally, the AI-powered DriveMod tech stack promises to bring a new level of data analytics to USC's operations. This can lead to better decision-making based on real-time operational data, predictive maintenance of the vehicles and potentially a more agile response to supply chain disruptions. It's important to monitor how this technology scales and integrates with USC's current processes and whether it can deliver a return on investment through improved efficiency and reduced costs.
The announcement of successful deployment of Cyngn's technology in a leading private label care product company could be a positive signal for investors, indicating potential for wider adoption in the industry. The ability to streamline operations and reduce costs with Cyngn's EAS might be reflected in USC's financial performance, potentially leading to improved margins and profitability. It's essential to examine the cost-benefit ratio of implementing such technologies and the time frame for realizing financial gains.
For Cyngn, the partnership with a company like USC serves as a case study that could attract other clients, potentially increasing Cyngn's market share and revenue streams. However, the market will be looking for evidence of sustained benefits and scalability across different industries. Long-term financial implications for Cyngn hinge on the continued performance and reliability of their EAS technology, as well as the company's ability to maintain a competitive edge in a rapidly evolving sector.
The use of autonomous technology in manufacturing and distribution is a growing trend and Cyngn's entry into this space with a successful deployment at USC could indicate a strong market opportunity. Understanding the competitive landscape is vital, as there may be other players offering similar solutions. The extent to which Cyngn's technology differentiates itself from competitors, in terms of cost, efficiency and reliability, will be key factors in its adoption rate.
Market penetration for Cyngn's EAS will also depend on industry reception to autonomous solutions and the regulatory environment. The ability to generate and leverage novel data and analytics from their AI-powered technology could give Cyngn a competitive advantage, but it's also important to assess the readiness of the industry to adopt such advanced systems. Monitoring the adoption rates and feedback from early users like USC will provide valuable insights into the potential market size and growth trajectory for Cyngn's EAS.
Download the full case study here.
Enter Cyngn and its Enterprise Autonomy Suite ("EAS") to offer self-driving industrial vehicles with the AI-powered DriveMod tech stack, introducing novel data and analytics about how things move at customer sites. DriveMod Stockchasers began transporting pallets around USC's
Approach
Deploying DriveMod-powered vehicles at
- Conduct a site assessment. First, Cyngn's customer success team worked with USC's operations managers to obtain a thorough understanding of process flows and goals. In parallel, Cyngn's field engineers surveyed USC's facility to document the operational design domain ("ODD") including the lighting, lane widths, and types of obstacles the vehicles could encounter. From this, Cyngn was able to identify transporting pallets from the inventory warehouse to the production facility as the optimal use case for the deployment.
- Build the map. In order for an AV to operate, it must know where it is within its environment. Cyngn scanned USC's facility to create a detailed 3D representation of the physical world. DriveMod vehicles use this localization map to safely navigate within the environment with centimeter-level accuracy, which is achieved from the onboard vehicle computer and doesn't require constant internet connection or special infrastructure installations.
- Design the application. Once the map was created, Cyngn worked with management on application design, which included the routes the vehicle would take, the stops where pallets would be loaded and unloaded onto the vehicle, how employees would interact with the vehicles, and permissible driving zones and other operating rules.
- Train key personnel. Finally, before the vehicle was let loose with full autonomous operation, Cyngn trained USC employees on safe use of the vehicle and the various interfaces available to interact with the vehicles and data dashboards. Finally, the vehicle was seamlessly integrated into daily workflows.
Curious to see our bring-up process in action? Watch it here.
While this process seems complex, it is standard operating procedure for a robotics company like Cyngn. The company recently brought up a deployment at a 1 million square foot manufacturing facility in less than 10 days.
Throughout the deployment period, the vehicle continuously collected data on vehicle usage and labor productivity in real-time. This data was used both to effectively monitor the vehicle's performance as well as to eventually calculate cost savings.
Results
Since kicking off the deployment at USC in early 2023, the Autonomous DriveMod Stockchasers produced:
- 4x Gains in Efficiency. Previously, a substantial human effort of 200 trips per week was required to fulfill pallet delivery between the two buildings at USC. After the introduction of DriveMod Stockchasers, this workload has been seamlessly absorbed. Cyngn's vehicles surpass traditional manual labor, as they can transport four pallets in a single trip, as opposed to one pallet at a time that was being accomplished with a forklift. This not only multiplies efficiency, but also allows for labor to be reallocated to other more valuable tasks, such as order picking and pulling.
- Reallocation of Labor. Beyond operational enhancements, the adoption of EAS and DriveMod has sparked positive developments in USC's workforce. Opportunities for employee growth within the company have emerged, leading to promotions and role reallocations. Employees are now exposed to more digital interfaces and empowered to take on different responsibilities, contributing to a more versatile and skilled workforce. Importantly, this evolution in job roles highlights that autonomy is more about task reallocation and the creation of new opportunities than job displacement.
- Increased Organizational Precision. Teams working directly with the autonomous robots revised their workflows to better align with the vehicles' predictable schedules. This simple change made a big difference, reducing variability, boosting overall efficiency, and making it easier to train new employees.
About Cyngn
Cyngn develops and deploys scalable, differentiated autonomous vehicle technology for industrial organizations. Cyngn's self-driving solutions allow existing workforces to increase productivity and efficiency. The Company addresses significant challenges facing industrial organizations today, such as labor shortages, costly safety incidents, and increased consumer demand for eCommerce.
Cyngn's DriveMod Kit can be installed on new industrial vehicles at end of line or via retrofit, empowering customers to seamlessly adopt self-driving technology into their operations without high upfront costs or the need to completely replace existing vehicle investments.
Cyngn's flagship product, its Enterprise Autonomy Suite, includes DriveMod (autonomous vehicle system), Cyngn Insight (customer-facing suite of AV fleet management, teleoperation, and analytics tools), and Cyngn Evolve (internal toolkit that enables Cyngn to leverage data from the field for artificial intelligence, simulation, and modeling).
Find Cyngn on:
- Website: https://cyngn.com
- Twitter: https://twitter.com/cyngn
- LinkedIn: https://www.linkedin.com/company/cyngn
- YouTube: https://www.youtube.com/@cyngnhq
Investor/Media Contact: Bill Ong, bill@cyngn.com; 650-204-1551
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Any statement that is not historical in nature is a forward-looking statement and may be identified by the use of words and phrases such as "expects," "anticipates," "believes," "will," "will likely result," "will continue," "plans to," "potential," "promising," and similar expressions. These statements are based on management's current expectations and beliefs and are subject to a number of risks, uncertainties and assumptions that could cause actual results to differ materially from those described in the forward-looking statements, including the risk factors described from time to time in the Company's reports to the SEC, including, without limitation the risk factors discussed in the Company's annual report on Form 10-K filed with the SEC on March 17, 2023. Readers are cautioned that it is not possible to predict or identify all the risks, uncertainties and other factors that may affect future results No forward-looking statement can be guaranteed, and actual results may differ materially from those projected. Cyngn undertakes no obligation to publicly update any forward-looking statement, whether as a result of new information, future events, or otherwise.
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SOURCE Cyngn
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