ML 100 Awards
 
gm.pngGM was able to complete development and multi-regional pilot deployments in a little over a year.

 

 

 

 

PROJECT


New production monitoring and control system
drives productivity and quality gains for auto giant

Even manufacturers that are coping with extremely challenging markets can’t afford to sit back and wait for demand to improve before launching improvement projects.

Take General Motors. In September 2008, as the automotive market was beginning to implode, the company’s Castings, Engine, and Transmission Center (CETC) decided to develop and deploy a standard Production Monitoring and Control system to drive capacity utilization, throughput optimization, and improvement in its manufacturing plants. The system would collect machine state, fault/diagnostic and machine performance data from controllers, allowing GM to use that information to improve throughput and quality. GM aimed to bring the system to 35 sites in 15 countries to advance business processes across the globe and improve its ability to respond to global competitors.

When planning the project, GM observed a gap in its capability compared with foreign and domestic competition. Some competitors, for example, already had real-time alarming and comprehensive data collection and analysis capabilities. GM’s answer was to design and deploy a platform based on MES systems, extensive reporting, and comprehensive data collection from flexible machining, automation, and service systems.

GM was able to complete development and multi-regional pilot deployments in a little over a year. The company finished deployment at 23 plants, and plans to complete the balance of deployments in the near term. Manual data collection was eliminated, and resources have been shifted to corrective actions and validating results of those actions.

The Production Monitoring and Control system now provides feedback to GM suppliers, allowing them to improve machine design. Users can generate historical reports and analyses such as mean time to repair, mean cycle between failure, top five faults, cycle time, and jobs per hour.

The system, in conjunction with business process changes, yielded a 10%-15% improvement in jobs per hour within a year of deployment. Machine productivity data can be shared with OEMs and vendors, and plant data is accessible globally. GM earned a patent for the method and process used in the project. Case studies performed on a subset of engine and transmission plants achieved a 20% improvement in jobs per hour, significant reductions in faults associated with constraint operations, and a 14% improvement in hours per unit.