Implementing an AI-Enabled Intelligent Manufacturing Solution for a Tier-1 Automotive Supplier

An automotive supplier worked with Riveron IMS experts to create a predictive solution that connected process data using artificial intelligence and increased productivity by approximately 100 parts per day.

Challenge

A Tier-1 automotive supplier had built a complex assembly plant that vertically integrated with other manufacturing operations throughout the enterprise. The plant assembly process, as originally designed, had created significant repair, rework, and quality control issues, resulting in depressed profit margins and overall operational inefficiencies. The supplier knew an intelligent manufacturing solution could address the challenges and help modernize operations to become more profitable and durable.

How we helped

Riveron’s Intelligent Manufacturing Solutions (IMS) team was engaged to formulate and execute the building of an enterprise-focused technology stack that could deliver on current customer requirements and enable the manufacturer’s migration to Industry 4.0. To accomplish this, our team first modernized machine-level controls with new communication protocols; then, we updated plant infrastructure to support the initiative and security protocols. Next, we translated the scope into specific intelligent manufacturing targets, which included building a data pipeline between plants to share processes, collect and analyze data, and use that data-driven knowledge to rebuild the assembly process.

Results

In an 8-week period, the intelligent manufacturing solution was able to change the company operations from reactionary methods to a streamlined one that could predict factory floor deficiencies. The results were remarkable:

  • Starting from an initial 40% waste or loss-of-product, which included machine rework and repair, the assembly process was first normalized and then made highly efficient.
  • First-Time-Through (FTT) was improved by 15%, which exceeded the manufacturer’s expectations.
  • By connecting process data using artificial intelligence, the automotive parts manufacturer experienced increased productivity by approximately 100 parts per day.

Overall, the engagement resulted in significant savings related to scrap and rework costs, eliminated premium costs and overtime shifts, and the automotive supplier saw an overall reduction of labor costs. Additionally, customer satisfaction improved due to greater confidence in the quality and delivery performance of the product.

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