Unplanned downtime costs American businesses billions every year, and wipes away early ROI from automation. It’s unsurprisingly one of the causes of margin erosion in manufacturing. The opaque commissioning process that delays automation and trial and error programming approach add to the cost and timelines, making system reliability one of the biggest challenges for manufacturing today.
But what are the systemic causes that lower system reliability?
Read on to find out what affects system reliability and how a combination of unified platforms and next generation motion control devices can permanently solve it.
The Three Causes of Lower System Reliability
Across hundreds of deployments, three main causes stand out consistently as contributors to lower reliability.
The first is the absence of validation. System design can often skip through structural checks to ensure all the right components are added, or if the design can work with the layout of the floor and other systems. These issues are usually unearthed during deployment, and any workarounds used to avoid delaying install may not be sustainable in the long run. For most traditional systems, program logic is frequently tested on real hardware for the first time on the floor, with the clock already running. It’s too late to find a robust solution which can last the entire lifetime of the system, mandating frequent ‘software touch-ups’.
The second is integration and equipment sprawl. Nearly half the manufacturers surveyed by IndustryWeek cited integration as their top external challenge. It’s common for a system to have cells with parts from multiple manufacturers, requiring costly workarounds and translation layers during deployment. The handshakes required to make disparate systems talk to each other increase the complexity, and raises the odds of system failure.
The last is the loss of process memory. The knowledge required to run, maintain, and troubleshoot a complex cell often is often with a handful of key operators and external integrators. Even when this know-how is readily available, troubleshooting can be challenging due to limited access and unavailability of system logs. As a result, new technicians can take longer to access programs and diagnose specific issues that can prevent small errors from accumulating and causing bigger system shutdowns.
Reliability, then, is a property of how a system is designed, programmed, and maintained. It doesn’t come from a flawless commissioning day or one irreplaceable expert. It comes from building automation the way software teams build their codebase: on validated components, tested before deployment, and connected for the life of the system.
The Essentials of Building Reliable Systems
Before jumping into the solution, it’s important to highlight what a reliable system actually looks like. Four principles below map directly to the three failure patterns above.
- Validation before you proceed: Every step, from design to program to throughput, should be confirmed before money or floor time is committed.
- Less sprawl: Fewer disconnected tools, parts that communicate more easily to each other, and fewer unvalidated vendor handoffs mean fewer places for small errors to compound into stoppages.
- Preserved process memory: Configurations, recipes, and best practices should live at the system level, saved and reusable, so reliability survives staff turnover instead of leaving with the person who built the cell.
- Accessible monitoring: Reliability does not mean minimizing errors. In case something breaks, an accessible and easy way to troubleshoot is just as important to contain the disruption.
Two catalysts move these principles from theory into daily practice. An AI-powered software-defined platform handles the design and programming side. A modern controller handles the physical, on-the-floor side. Solving one without the other leaves a gap where failures still get through.
Software-Defined Automation as the Foundation for Reliable Systems
The design and programming side is where reliability is either built in or left to chance. Vention’s software-defined automation platform addresses it across four areas, each tied to one of the essentials above.
From Design to Deployment on a Single, Connected Platforms
The full cell is modeled before anything is ordered, and the bill of materials is generated from that design rather than assembled by hand. Design can be seamlessly moved to programming instead of working with multiple platforms and managing separate files. A single platform allows teams to move between design and simulation with ease, and the exact same program can be directly transferred to the equipment, reducing any last minute surprises.
AI built into the platform catches costly mistakes early
Design-time checks can flag problems like misaligned or missing components before they ever reach the floor, where the same problem would cost hours of rework. At Acutec Precision Aerospace, MachineBuilder’s Design Checker caught a misaligned connector during the design phase, and the team now completes designs that once took weeks in days, according to Adam Dunn, Automation Engineer at Acutec. The error was caught when it was cheap to fix.
Digital twins validate the program before a dollar is spent
Physics-based simulation lets a program be tested against throughput, robot kinematics, and collisions before any hardware is ordered, and the same validated program then deploys to the real machine. Problems get caught in the model, not on the floor. Modern manufacturers such as Solestial are already using physics-based simulations and digital twins to de-risk workflows, and accurately estimate throughput before a single dollar is spent.
The platform hardens the design and programming side. The other half of reliability lives in what actually runs the cell.
Process knowledge is preserved at the platform level
When configurations and best practices are saved, versioned, and reusable across lines and sites, turnover stops being a single point of failure. The second and third deployments start from a validated foundation instead of a blank page.
One view of every cell across the operation
Preserved knowledge answers what a cell should do. Fleet-wide visibility answers what every cell is actually doing right now. Because each machine stays connected to the same platform, a control engineer can monitor performance across multiple cells, lines, and sites from a single view rather than checking each one at its own panel. Throughput, uptime, and machine status roll up into one place, so a slowdown at one site is visible from anywhere instead of surfacing only when someone walks the floor.
On the Floor: More Control Per System with New-Age Controllers
Traditional PLC-based deployments carry a hidden tax. Each new cell needs a translation layer between different vendors’ systems, so every project attempts to solve integration from scratch. Wiring complexity, drives, safety PLCs, and power supply infrastructure accumulates with each added part, and every one of those connections is another point that can work loose, corrode, or get miswired during a rebuild. The result is that each deployment is roughly as hard as the last.
A modern controller is designed to bend that curve down. Vention’s MachineMotion AI was designed to be the extension of the software platform. Software wasn’t an add-on but part of its DNA from the get go. So the same controller and workflow carry from one cell to the next instead of starting over. It runs on NVIDIA Jetson Orin, which means perception and motion planning happen at the edge in real time rather than depending on an external server and the latency that comes with it.
How MachineMotion AI reduces fragmentation and troubleshooting challenges
- Plug-and-play integration with robots, conveyors, motors, sensors, and safety devices, based on Vention’s product specifications.
- EtherCAT daisy-chaining of up to 20 motors on one compact controller, delivering up to 3,000 W of motion output power, which cuts the number of cables, and connectors that can fail. It also eliminates the need for drives.
- Built-in cellular and Wi-Fi connectivity, one of its kind Over-the-Air updates without any need for heavy network infrastructure.
- An IP54-rated enclosure certified to U.S., Canadian, and European safety standards, with ISO 27001 and NIST certification for its cloud and OTA components.
The combined effect is fewer translation layers and fewer physical failure points. That same connectivity also changes how the system is maintained. Because the controller stays connected to the software, a control engineer can diagnose it without standing next to it. Full log visibility lets a technician trace what actually went wrong instead of guessing, and fixes push back to the machine as OTA updates rather than a site visit. A problem that once meant a flight and a day of downtime becomes a remote session, so small faults get resolved before they cascade into a shutdown. The result is a deployment and troubleshooting process that gets easier each time rather than harder.
Platform, the Grounding Layer for the AI Era
Automation as we know it is changing, and as agentic AI arrives on the factory floor. A software-defined platform is that grounding layer for AI. It keeps autonomous behavior mapped, validated, versioned, and observable, so added intelligence brings flexibility instead of chaos.
For the control engineer, that shift is worth investing time and effort in. The rewards certainly outweigh any learning curve with less time firefighting on the floor, deployments that get faster and safer instead of riskier, and knowledge that compounds across projects instead of walking out the door with the last person who understood the cell. Reliability and autonomy stop being a trade-off when the foundation underneath them is sound.
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Planning your next automation cell with reliability in mind? Contact Vention experts to review your approach.
