Mitsubishi Electric Europe B.V. has launched DataNavigateApp, a browser-based production analytics solution designed to help manufacturers better understand machine performance, downtime and energy usage.
The launch comes as manufacturers face increasing pressure to improve productivity and reduce energy consumption amid rising operating costs, tighter production targets, and ongoing engineering resource constraints. While most factories already collect large volumes of machine data, many still struggle to turn that information into practical operational insight that teams can use on the shopfloor.
DataNavigateApp is a dedicated application for Mitsubishi Electric’s MELSEC iQ-R series C Intelligent Function Module. Simply installed via an SD memory card, the browser-based solution supports visualization at the production level, helping manufacturers take a first step towards wider factory visualization, IoT and digital transformation initiatives.
The solution has been designed around three core principles: simple setup, monitoring from anywhere, and easy data collection. The application can be configured intuitively through a web browser with no programming required and without the need for specialized knowledge of ladder programming or C language programming, while machine status and production trends can be viewed remotely from PCs or tablets without dedicated HMI hardware.
DataNavigateApp also supports easy data collection from both Mitsubishi Electric and third-party PLC environments through standard industrial communication protocols. If the CPU module already holds production data, this information can be easily visualized without extensive integration work or modifications to existing PLC programs, supporting deployment across mixed-vendor and brownfield production environments.
The app has also been designed to support gradual adoption. Instead of requiring factory-wide deployment from the outset, manufacturers can begin by monitoring a single machine or production line before scaling the same approach across wider operations.
Daniel Sperlich, Strategic Product Manager Controllers EMEA at Mitsubishi Electric, said: “Many manufacturers already have access to the data they need, but turning that data into something practical and actionable on the shopfloor remains a challenge.
“DataNavigateApp can help lower the barrier to production analytics. It gives manufacturers a practical way to improve visibility of machine performance, helping teams identify opportunities to improve output stability, reduce downtime, better understand energy behavior and reduce operating costs, without needing large-scale software projects or specialist programming expertise. Just as importantly, manufacturers can start small, prove value quickly and then scale at their own pace.”
The platform helps manufacturers address a range of common production challenges, including output instability, unplanned downtime, rising energy consumption and performance degradation. By visualizing equipment operating status and operational trends, identifying factors affecting operating time, highlighting wasted power consumption and supporting predictive maintenance, the solution enables teams to prioritize improvements more effectively and respond more quickly to emerging issues.
It is designed to operate alongside existing equipment via standard PLC communication functions, allowing manufacturers to introduce production monitoring across mixed-vendor or brownfield environments without significant disruption to running operations.
Information is visualized through intuitive graphical dashboards, allowing users to compare operational data side-by-side across different time periods, machines, or production conditions. This helps teams identify trends, prioritize improvement opportunities, and respond more quickly to operational issues. The result is a simple but powerful shift: faster decisions, clearer priorities, and measurable improvements in machine performance.
For more information, please visit: emea-fa.mitsubishielectric.com/fa/products/datanavigateapp
