Make Invisible Factory Work Visible: Velotic and Data Time Space Connect Physical Work to ThingWorx

Machines can tell you when they stop. But what tells you whether a manual assembly step is progressing, a part has reached the next station, or a handoff is holding up production? In many factories, answering those questions still requires someone to walk the floor, observe the process, and enter an update. That leaves important parts of production invisible to the software used to manage it.

Velotic is partnering with Data Time Space (DTS) to bring that physical activity into the connected factory. By turning observed actions and states into digital events delivered through Kepware, DTS extends the data available to ThingWorx beyond machines and connected devices. The opportunity is broader visibility into how production actually flows—and a new source of context for performance monitoring, quality, and continuous improvement. 

Data Time Space’s Physical AI captures what is happening in physical work areas and turns those observations into digital events that industrial software can use. Using iPhone Pro devices with on-device AI and spatial sensing, DTS can recognize configured activities and conditions, such as a part reaching an installation position or a physical step being completed. These observations become Virtual Sensors that extend visibility beyond machines and connected equipment.

The integration follows a simple path: DTS observes the physical event, Kepware connects that event to ThingWorx, and ThingWorx combines it with the machine, production, and business context the application needs. Configured events are exposed as Kepware tags, so they enter the same connected environment manufacturers already use for machine, tool, and sensor data. Instead of relying on someone to observe the process and manually report every update, manufacturers gain another source of operational data from the factory floor.  With that physical context aligned to machine and production data, ThingWorx applications can show not only what a machine reported, but what was happening around it. 

Privacy and data handling: Virtual Sensor processing happens on the device. Video does not need to be recorded or uploaded to the cloud for Virtual Sensors to operate, and each observation can be reduced locally to a trigger, confidence value, or pass/fail state. DTS is designed not to identify individuals. Customers can choose to record Spatial Video separately when they want a historical spatial record. What is retained or shared depends on the deployment configuration and should align with site privacy, security, and governance requirements.

A spatial record of physical activity can help connect what happens between machines with the production outcomes manufacturers already measure. Depending on the process and application configuration, the primary opportunities are:

• Production visibility with less manual reporting: Use configured physical events to capture process milestones and make activity in previously unconnected areas visible in production dashboards. Teams can spend less effort gathering status and more time investigating exceptions. 

• More context for performance losses: Combine observed process activity with equipment states to investigate delays around loading, unloading, manual work, and handoffs. This can enrich overall equipment effectiveness (OEE) analysis. It complements, rather than replaces, the availability, production-count, and quality data required to calculate OEE.

• Continuous improvement grounded in actual execution: Use the Spatial Historian, a record of physical activity over time, to compare process cycles, examine variation, and distinguish value-added activity from waiting or unnecessary movement. Repeat observations can help teams assess whether a process change delivers the intended result. 

• Quality evidence: For defined visual conditions, DTS can provide a confidence value or a configured pass/fail event, adding evidence to the execution record rather than a blanket assessment of product quality.

DTS delivers physical events to ThingWorx through Kepware, the same connectivity layer manufacturers already use for machines, PLCs, and tools. Each event arrives as a standard Kepware tag or pass/fail signal, so any ThingWorx application can use it. That includes Velotic's out-of-the-box applications, such as Connected Work Cell, RTPPM, and DPM, and any custom ThingWorx application you have built. The result is one integration path rather than a separate connector for every application.

One physical event, many uses: Once an event is available as a tag, you decide how to use it. It can advance a work instruction step, feed production dashboards, add context to OEE and performance-loss analysis, or support continuous-improvement studies. This works in the applications your teams already use. 

DTS helps ThingWorx AI see beyond the machine. By connecting physical events—material arrivals, loading activities, and manual handoffs—to ThingWorx’s machine and production context, manufacturers can give LLM-based assistants more complete evidence to investigate operational losses.

Asked “What contributed to yesterday’s throughput loss?”, an assistant could connect equipment downtime with surrounding physical activity to highlight potential causes and guide investigation. With aligned timestamps, production-context mapping, and governed data access, this richer context can support faster investigations and better-targeted improvements—not just better summaries. 

Start with a manual process, material handoff, or production area that still depends on someone checking progress and entering updates. Bring that blind spot to Velotic and Data Time Space for an exploratory discussion. Together, we can identify the physical events that matter, assess fit with your ThingWorx environment, and agree on a measure of success, such as reporting effort, cycle-time variation, or time spent waiting between steps.

“Physical AI gives us an opportunity to extend connected industrial workflows into areas of manufacturing that have historically been difficult to instrument. By combining Data Time Space with ThingWorx and Kepware, we can explore new ways to make physical work actionable within the industrial software ecosystem,” said Ayush Tiwari, Senior Director Product Management, ThingWorx, Velotic.

“Factories already generate enormous amounts of machine and IoT data, but much of the physical work performed by people remains digitally invisible,” said Valentin Heun, PhD, CEO of Data Time Space. “Together with Velotic, we can turn that physical activity into useful industrial data while giving manufacturers a spatial record they can use to continuously improve how work is performed.”