Cars In Assembly line At Car Plant

Smarter cars need a smarter factory.

Building the cars of the future is a challenge.

Consumer demand for built-to-order options complicates on- and off-line work sequencing. Short product cycles are getting shorter, meaning automotive manufacturers are expected to do more with less time. And with new technologies increasingly common in cars and trucks, compliance is as important as ever. Traceability down to the SKU is essential. Existing systems aren’t flexible enough to support the high-mix, built-to-order factory, and paper-based processes hinder the collection of real-time data.

Empty Manufacturing Facility

Rapid product cycles with costly NPI cycles

Multiple discrete assemblies

High-mix driven by built-to-order

Steep standards for regulation and compliance

Tulip’s no-code platform streamlines even the most complex work sequences. 

Tulip apps support build-to-order and customized manufacturing, helping engineers optimize mixed assemblies. Tulip’s Enterprise deployment integrates into ERPs and MESs, and IoT enabled devices guarantee compliance from day one.

Interactive work instructions for high-mix assemblies

Guide operators through complex assemblies and make sure they get it right the first time.

Learn more about work instructions.

Histogram of completion times graph

Real-time data from people and machines

Measure and improve operator productivity through continuous time studies and increase your overall process effectiveness with integrated machine monitoring.

Learn about Tulip Analytics

IoT connectivity guarantees quality and productivity.

Leverage your connected tools, machines, and devices to reduce human error and increase first pass yield.

Learn about Shop Floor IoT

Tulip process on a bench with IoT torque driver

Case Studies

Manufacturing Engineer quote from Automotive Industry

Training time cut from months to weeks

By using IoT-connected work instructions apps, Techniplas standardized employee cycle times and eliminated the need for shadowing during training. As a result, they reduced training times on assembly processes from 3-5 months to 2 weeks.

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