Peter Howard, President & CEO of Realtime Robotics.

What specific challenges in robotic automation were you aiming to solve when developing Resolver, and how does it address them better than traditional solutions?

The three biggest challenges utilising robotic automation in manufacturing are cost, brittleness, and time-to-market. To improve system throughput and cost, multi-robot workcells are increasingly common, as they help to minimise floorspace, transfer equipment, and reduce cycle time. However, using today’s human-based tools to design them drives up brittleness and time-to-market.

Resolver handles the toughest challenges in designing and programming workcells of any size and complexity, affordably finding the optimal solutions and choreography for a given system architecture in minutes to hours, as opposed to days, weeks, or months. Our Resolver software is an Industrial AI that quickly and intelligently evaluates thousands to millions of potential solutions to quickly find and generate optimal, collision-free motion paths and interlock signals. Additionally, Resolver can automatically calculate the fastest sequence of process points and how to distribute them across robots – accelerating workcell design from months to days – all while cutting engineering time in half and increasing overall throughput.

Resolver promises significant reductions in engineering time and cycle times – can you share examples or case studies that illustrate these gains in real-world manufacturing environments?

Sure thing. There are two different ways that we've helped customers realise significant gains.

One example was when Ingemat, a European integrator, was dealing with complicated workcells – and had a cycle time target of 47 seconds to hit. The reality was that despite their best efforts, some cells were still as high as 55 seconds. Instead of continuing to work on it and make incremental gains, or deciding to move forward despite the consequences of being delayed and above cycle time, they turned to us. By using Resolver, Ingemat was able to achieve 18% cycle time savings.

We’ve also had other projects where customers used Resolver pre-emptively, to optimise their workcells and layout as much as possible before starting the project. Not only did these customers avoid having any cycle time issues, they also reduced the hours required for their simulation team to work on these cells by ~50%.

How does Resolver integrate with existing simulation and programming tools that manufacturers are already using, and how steep is the learning curve for engineering teams?

Resolver requires minimal onboarding; all a user needs to get started are CAD objects, robots, and process points. Resolver will take care of the rest. The goal is for teams to be able to upload their workcell data directly from their preferred simulation tool into Resolver’s cloud platform, where parallel processing with high performance computers can happen. The results are then imported back into the simulation tool, which fits nicely with existing workflows. Currently, users can do this using Siemens Process Simulate (from version 2301 onward), but support for other leading simulation platforms are currently being worked on and will be available later in the year.

Manufacturing needs are constantly evolving. How adaptable is Resolver to changes in production workflows, such as new product introductions or line reconfigurations?

Resolver has been engineered to help manufacturers embrace those changes. Our software shortens the design phase by streamlining manual path planning into simple steps, automatically defining interlock signals and minimising mechanical design iterations.

This means that when there are change orders, a need to scale up or down, or the need to reconfigure for a new product, Resolver gives users the flexibility they need to adapt their automation and re-balance robot tasks within a workcell, or even a whole manufacturing line. Robots can also be easily added or subtracted, and different variables can be adjusted based on production needs. All without a lengthy reprogramming process.

Because of its inherent cloud-based scalability, with only a digital twin of a production line, Resolver could enable overnight reprogrammings of everything – even if there were hundreds of robots. A task like this would prove challenging to accomplish manually, even if you had every robot programmer in the United States working on it at the same time. Not only that, Resolver could balance the entire production line while doing said reprogramming. So, in the long run, we believe Resolver has the potential to totally change the economics of automation.

Looking ahead, how do you see Resolver shaping the future of collaborative robotics and smart manufacturing ecosystems?

Resolver has the potential to finally realise smart manufacturing for any combination of high or low mix and volume applications. It offers users speed and flexibility previously unheard of in the manufacturing industry. Resolver eliminates the uncertainty of not knowing until the end of a project if cycle times will be met, saving time and money – while improving efficiency across projects and industries.

Beyond that, Resolver also democratises robot path planning, enabling non-experts in an organisation to plan paths and validate designs themselves. But probably the most revolutionary aspect of Resolver is its ability to be used at any point in the project lifecycle, from proposal to workcell design to OLP.

While optimising existing workcells and projects is critically important today, in the future this technology will let companies begin with an optimised setup. That creates huge implications for giving manufacturers the ability to do more than currently possible – and at a lower cost. Imagine removing a single robot from a workcell, in the early concept stages, while maintaining cycle time certainty. It saves companies time and money across the design, procurement, build, and commissioning phases, and limits recurring costs, improving the lifetime cost of ownership.

In an age where the location of manufacturing facilities and the creation of new sites are actively being discussed at the highest levels, it is technology like Resolver that will make realising those changes possible.

Peter Howard is President & CEO of Realtime Robotics. He has a passion for innovative business formation, and the process of creating order and value out of formative chaos. His roles have included entrepreneur-CEO, investor, and board director. As CEO, Peter has founded and successfully grown four previous companies, leading two to IPOs, one to strategic sale, and another to a major technology license. Peter has also been integral in the creation and launch of hundreds of innovative products as an industry leader in outsourced R&D and manufacturing services businesses based in the US, Japan, France, the Netherlands, Singapore, and China. Peter holds an MS degree from MIT in Management, and a Professional Director Certification from the American College of Corporate Directors.