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Plant engineering firm Zeppelin GmbH in Garching, near Munich, is using the machine learning toolkit from US company Splunk to develop algorithms to monitor the performance of spark plugs in its combined heat and power units. If a failure is detected, the software sounds an alarm, to let the operator react promptly and prevent possible equipment downtime. Zeppelin is also leveraging Splunk Enterprise software to gain a constant overview of the machine data for the 25,000 items of Caterpillar construction equipment on loan to customers; this also gives the company reliable information about the equipment’s degree of utilization. Zeppelin utilizes the data to calculate the probability of problems and dispatches service technicians to the customer to carry out maintenance before the problem occurs. According to the Group , this has enabled it to increase the uptime and service life of its equipment and machines and to improve customer satisfaction levels.

Splunk’s tool collects machine data in a repository and makes it available to users. Graphs, reports, and warning messages can be generated on the basis of the data collected.