Value Stream Mining in automotive industry company

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road
5%

of executions show non-standard movements

60%

increase in lead time due to unexpected executions

25%

of AGVs show a performance below what is expected

automotive-comp

Automotive industry company

Analysis of repetitions and non-expected activities in the production line

Our client was an automotive company looking to optimize the movement patterns of their AGVs (mobile robots) as well as identify inefficiencies in the manufacturing process.

Challenge

To find non-optimal patterns in the movement of the AGVs (mobile robots) and identify re-work in the manufacturing process

We analyzed more than 30.000 events from the AGVs and 800.000 manufacturing events gathered in a month and segmented the data by production line, vehicle brand and family to identify the errors.

Solution

We identified and quantified errors in the control of automatic vehicles

Identified differences by shift and equipment.

Location of areas within the plant that caused bottlenecks in the motion of the automatic vehicles.

Segmentation of the causes of the repetition of activities in the Paint section according to vehicle families and end customer request.