The challenge: Unexpected interruptions in production, unpredictable fluctuations in the quality, painful downtimes, missing connections between individual causes. Many challenges in day-to-day production can be promptly addressed by looking into the world of data. In modern highly automated production plants, thousands of measuring and control elements deliver valuable information every second. Those who manage to integrate this information, analyze it and combine it with historical data in connection with various evaluation criteria and use it as a basis for decision-making will gain a decisive competitive advantage.

The tool: Timefuse allows quality managers, system developers, service and maintenance technicians, and many other key people to analyze very large amounts of data in an instant. The analysis is interactive, visual and so intuitive that you don‘t have to be a data scientist to benefit from the results.

The key capital – knowledge and experience: The knowledge and experience of your employees. Timefuse enables the search for patterns in very large amounts of data. Outline your hunch, mark similar data series and let Timefuse find all historical occurrences of comparable behavior. See the results as a relevance-sorted list with a preview so that you can promptly identify and interpret temperature fluctuations before a failure or vibrations occur leading to a decline in the quality.

Action-relevant knowledge: Timefuse not only finds patterns in time series, but also links them to documents. How was the last similar shutdown handled? What maintenance measures are required at this time? Has anyone ever reported a similar problem? Timefuse knows this and provides you with the relevant information at the right time and in the right form. This offers you an opportunity to make the right decisions in a particular situation.

Annotate – the new cultural technique: Data contains evidence, but the mind contains knowledge. Your experts interpret patterns detected by Timefuse and record these interpretations for marked data areas. This creates annotations that link knowledge and data. In this way, Timefuse can find expert opinions on data anomalies, optimize repairs and maintenance, and provide expert knowledge data examples for training.