The promise of automation prototypes has rarely been fulfilled. Great conceptual product rarely makes it a commercially viable automation solution, says automation consultant, Steve Derby.
Nowhere has this gap been more evident than the AGVs (Automated Guide Vehicles) and mobile robot companies; few can actually deliver product for today’s 24/7 manufacturing and distribution operations.
Many of the industrial robotics currently on the market have simply updated and modified from technologies created five to ten years ago. They fail to adapt to the warehouse and factory demands required in an Industry 4.0 and IIoT (Industrial Internet of Things) environment.
While there is some resistance by plant managers on the shop floor or distribution centre managers accustomed to fork trucks, Industry 4.0 is the imperative of C-level executives. IIoT sensors are collecting data which must transform productivity, throughput, and predictive analytics over the next decade. This top-level strategy is driving automation implementation both in North America and globally, both enterprise-wide and inside the four walls of the facility.
Few mobile robotics and AGV companies currently possess the total connectivity required in Industry 4.0 corporate initiatives. The exception is AutoGuide Mobile Robots which uses the Industry 4.0 approach due to the semiconductor technical background of the company’s core C-level management.
Roadmap for mobile robots 2019
Many AGV companies have simply retrofitted existing fork truck platforms; they have attached vision-guided or LiDAR technologies claiming they are now Industry 4.0 ready. They lack a roadmap for both hardware and software development.
AutoGuide Mobile Robots, with an extensive research and development team based in Chelmsford, MA, offers modular hardware options including a single automation device with modular attachments. Compared to the competition, only AutoGuide offers flexible and reconfigurable devices which help lower the cost, creating a rapid ROI (return-on-investment).
Strategy of AI driving predictive analytics
AutoGuide Mobile Robots is working on Artificial Intelligence (AI) strategies to further expand technologies into industrial environments. This unique AI approach collects data by following and learning from the human operators over a period of time, enabling a fully autonomous AGV or mobile robot in tough applications. These predictive analytics ensure optimised processes, best-practices, and first in the industry addressing truly autonomous work.
Ready today: Not a futuristic science project
AutoGuide’s mobile robots are not a science project but commercially hardened. They have state of the art technology and have been integrated into numerous production facilities in record time, weeks rather than months or years. AutoGuide can fill an order in less than two months; its modular design facilitates adaptability to nuanced and specific customer requirements. The competition in the AGV space often requires eight months (or longer) to build and implement a system. That is lost productivity.
The company’s MAX N10 mobile robot can move up to 10,000 pounds with no tape, no RFID tags, no mirrors or reflectors. They also offer pallet loading, straddle forks, unit load, conveyor, car mover, and a manual option driver platform. The MAX N10 can travel 4.0 mph in actual industrial environments while the competition is limited to 2.3 mph.
Today’s warehouses and factories are challenged to find and keep a good workforce while simultaneously pressured to reduce costs and handle the growth of e-commerce, automation solutions like the MAX N10 can best address these issues.
As one who has spent many years creating and prototyping novel automation work cells, it is great to see AutoGuide’s industry leading ideas as finished working products. Although prototypes are a needed step in the development of production automation, too often they are never completed into a useful solution.
The author of this blog is Dr. Steve Derby, automation consultant
About the author
Dr. Steve Derby, Automation Consultant, is Mechanical Engineering Associate Professor Emeritus. He has nearly 40 years of experience and expertise in robotics, automation design for manufacturing equipment, robots, controls, machine vision, and processes. Derby enjoys working with engineering, maintenance, and production on projects to increase efficiency and improve safety. He earned his PhD in Mechanical Engineering from Rensselaer Polytechnic Institute.
Comment on this article below or via Twitter: @IoTNow_OR @jcIoTnow