Lesson Learned Explained: Data visualization in components manufacturing for automatics

Challenge: Improving production KPIs for electrical accessories
A global company in the electrical accessories manufacturing industry used in automation faced the challenge of improving key performance indicators (KPIs), particularly increasing the availability and efficiency of production cells. Each workstation involved multiple stages of assembly and production across various positions and locations, requiring a coordinated approach to managing work, materials, and proper planning.
Solution: Visualization of data collected from various sources
The company decided to integrate with third-party systems and machines on the production floor to address the challenge. The key element of the solution was data visualization from various sources (e.g., production plans, the number of units produced from a given order across all cells, manually confirmed assembly stages from work screens, and warehouse order information). This approach enabled better monitoring and streamlining of the assembly process and its auxiliary functions. Dashboards displayed above work centers aimed to provide operators with real-time information necessary for efficient task execution.
Implementation Challenges: Lack of clear vision and insufficient input data
Despite delivering the initial visualizations, the client needed a clearer vision to utilize this data further. They assumed that simply displaying the data would significantly improve work efficiency. While the displayed information partially supported operators, it fell short of optimizing the entire process. It revealed a gap in data utilization (presentation and analysis). The lack of practical application of some provided visualizations meant they did not meet the client’s expectations.
Adjustment: Enhancing visualizations with trends and measurement comparisons
In response to the identified issues, the visualizations were enriched with additional elements such as historical trends, the ability to compare measurements, and in-depth analysis. Additionally, some operations and team communication were automated, and the entire process was measured. These changes enabled more accurate conclusions and a better understanding of which stage of the process had issues. It allowed both operators and production leaders to optimize their actions better.
Results: Effective production optimization after system adjustment
Initially, the delivered features did not fully meet the client’s expectations because some needed more practical application. Only after a deeper analysis involving line workers and adjusting the system to the actual needs of the operators was it possible to create a tool that truly supported production optimization. The solution was enhanced with useful features such as historical trends, measurement comparisons, work order support, automatic recognition of missing materials in the cell, and similar functions, providing operators with the necessary tools to make accurate decisions and effectively support their daily work.
Conclusion
Based on the actions taken, several key conclusions can be drawn:
- Engaging end-users at every stage of the project is crucial for success. Therefore, we always recommend that an end-user representative be regularly involved in the team’s work.
- Providing the right data to the right people at the right time is essential for making accurate decisions. Identifying these aspects (data, people, time, context) is critical to planning and gathering requirements.
- Change management is a more important process than the technology itself. Even the best tools are worth little without users.
- The goal of innovation is the complete user experience, not just the application itself. Users must feel comfortable with the solution to want to use it.
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