Real-time manufacturing dashboards improve production KPIs only when the people on the line use them to make decisions. This project with a global manufacturer of electrical accessories for automation shows why displaying shop floor data is not enough. The dashboards started to support production optimisation only after line workers took part in the analysis and the system was adjusted to their actual needs.

At TT PSC, we believe manufacturing leaders should rely on reliable, real-time data to reach the goals of Industry 4.0. Data builds knowledge and awareness, and it shows which actions need improvement. This is the foundation of digital manufacturing: connecting machines, systems and people so that decisions rest on facts rather than assumptions. In this series, we share completed projects and the insights they gave us, to help you avoid at least some of the pitfalls on the way to digital transformation.

What is a real-time manufacturing dashboard?

A real-time manufacturing dashboard is a visual interface that shows the current state of production using live data from machines, workstations and business systems. It displays KPIs such as output against plan, availability, efficiency and order status, so that operators and production leaders can react while the shift is still running.

Unlike a report prepared at the end of a day or week, a real-time dashboard supports decisions at the moment they matter. On the shop floor, production dashboards are often placed directly above work centres. Operators see what to produce next, how far an order has progressed and whether anything is blocking the work.

Why real-time manufacturing dashboards matter in digital manufacturing

In a smart factory, dashboards are the layer where data becomes visible to people. They sit on top of a connected data architecture and turn signals from the production floor into information that someone can act on.

Where dashboards sit in a connected factory

  • Connectivity. Industrial IoT and industrial connectivity platforms collect data from machines, PLCs and sensors.
  • Data integration. A common data layer, such as a Unified Namespace, combines machine data with information from ERP, planning and warehouse systems.
  • Operations. A manufacturing execution system (MES) and wider Manufacturing Operations Management (MOM) processes coordinate orders, materials, work steps and quality.
  • Visualisation and analytics. Dashboards and reports and industrial analytics show what is happening and why.
  • Data and AI. Advanced analytics and AI models use the same data to anticipate problems before they occur.

When the lower layers are fragmented, dashboards show incomplete or inconsistent data. When nobody defines how the data should be used, dashboards show information without practical value. The project below illustrates the second risk.

Case study: real-time production data in electrical accessories manufacturing

The challenge: availability and efficiency of production cells

A global company manufacturing electrical accessories used in automation needed to improve its key performance indicators (KPIs), in particular the availability and efficiency of its production cells. Each workstation involved multiple assembly and production stages across different positions and locations. This required a coordinated approach to managing work, materials and planning.

The solution: shop floor data visualisation from multiple sources

To address the challenge, the company decided to integrate third-party systems and machines on the production floor. The key element of the solution was data visualisation combining information from several sources:

Data sourceWhat it adds to the dashboard
Production plansWhat should be produced and when
Units produced for a given order across all cellsProgress of each order in real time
Assembly stages confirmed manually on work screensWhere each product is in the assembly sequence
Warehouse order informationStatus of the materials needed at the workstation

This approach enabled better monitoring and streamlining of the assembly process and its auxiliary functions. Dashboards displayed above work centres were designed to give operators the real-time information they needed to carry out their tasks efficiently.

The implementation challenge: no clear vision and insufficient input data

The first visualisations were delivered, but the client did not have a clear vision of how to use this data further. The assumption was that simply displaying the data would significantly improve work efficiency.

The information on screen partly supported operators, but it did not optimise the process as a whole. The project revealed a gap in data utilisation, in both presentation and analysis. Some visualisations had little practical application, so they did not meet the client’s expectations.

In response, the visualisations were extended with historical trends, the ability to compare measurements and in-depth analysis. Some operations and team communication were automated, and the entire process was measured.

These changes led to more accurate conclusions and a better understanding of which process stage was causing issues. Both operators and production leaders could then optimise their actions more effectively.

The results: a dashboard that supports production optimisation

The first release did not fully meet expectations because some features lacked practical application. Only after a deeper analysis involving line workers, and after adjusting the system to the real needs of operators, did the team create a tool that truly supports production optimisation. The final solution included:

  • historical trends,
  • measurement comparisons,
  • work order support,
  • automatic recognition of missing materials in the cell,
  • similar functions that give operators what they need to make accurate decisions and support their daily work.

Four lessons for real-time manufacturing dashboards that operators use

1. Involve end users at every stage

Engaging end users at every stage of the project is crucial for success. That is why we always recommend that a representative of the end users works regularly with the project team. In this project, the breakthrough came only when line workers took part in the analysis.

2. Deliver the right data to the right people at the right time

Accurate decisions depend on the right data reaching the right people at the right time. Identifying these aspects (data, people, time and context) is critical when planning the project and gathering requirements.

3. Treat change management as more important than technology

Change management is a more important process than the technology itself. Even the best tools are worth little without users.

4. Design for the complete user experience

The goal of innovation is the complete user experience, not only the application. Users must feel comfortable with the solution to want to use it.

How to plan a shop floor dashboard project: a practical checklist

The lessons above translate into a short set of questions worth answering before any production dashboard is built:

  1. Which production KPIs should the dashboard improve, for example the availability and efficiency of production cells?
  2. Who will use each view: operators, shift leaders or plant management?
  3. Which decisions should each user make based on the data, and when?
  4. Which sources are needed (machines, MES, ERP, planning or warehouse systems), and is the input data complete and reliable?
  5. Is historical context such as trends and measurement comparisons needed, or only the current status?
  6. Which routine operations or team communication can be automated?
  7. How will operator feedback be collected and built into the next iteration?

Where real-time dashboards lead next: from visibility to predictive analytics

Real-time visibility is usually the first step of a digital manufacturing programme, not the last. Once the data is reliable and people trust it, the same foundation supports more advanced use cases:

Each of these depends on the same condition as a good dashboard: data that is collected, stored and presented in a way people can act on. Our step-by-step digital transformation roadmap for manufacturing shows how to sequence these initiatives, and 13 Industry 4.0 use cases with real results shows what they deliver in practice. For the wider context, read what Industry 4.0 means for manufacturers.

Summary: what makes real-time manufacturing dashboards work

Real-time manufacturing dashboards are a core building block of digital manufacturing, but visibility alone does not improve KPIs. In this project, value appeared when the dashboards gained historical trends, measurement comparisons, work order support and automatic recognition of missing materials, and when line workers helped shape the solution. Start with the decisions people need to make, involve end users from day one and treat change management as part of the project scope.

Planning production dashboards that people will actually use?
Start with your losses, not the technology. The interactive Navigator on our Digital Manufacturing page matches your production challenges to proven use cases and estimates the ROI from your own downtime, scrap and energy figures.
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FAQ: real-time manufacturing dashboards

A real-time manufacturing dashboard is a visual interface that shows the current state of production using live data from machines, workstations and business systems such as MES, ERP and warehouse systems. It helps operators and production leaders react to deviations during the shift rather than after it.