Advanced Process Monitoring Solutions for the Automotive Manufacturing Industry

Automotive manufacturers, including suppliers to the automotive industry, benefit from a multitude of STATISTICA products to achieve the most efficient processes in the business. Typical applications include monitoring processes, finding important controllable factors and anticipating issues before they occur. STATISTICA solutions available for these tasks include: STATISTICA Enterprise QC, STATISTICA Monitoring and Alerting Server (MAS), WebSTATISTICA Enterprise QC, and STATISTICA Process Optimization and Root Cause Analysis.

Areas of Application: Monitoring Processes with STATISTICA Enterprise QC and MAS

STATISTICA Enterprise QC monitors the various critical manufacturing processes that are taking place simultaneously at the facility during testing and assembly. Immediately knowing when a process gets off spec saves time and materials. STATISTICA Enterprise QC offers SPC solutions for automotive suppliers to monitor processes and part testing to ensure quality of parts and assemblies.

STATISTICA Monitoring and Alerting Server (MAS) provides automated monitoring and dashboard summaries for highly automated automotive manufacturing and assembly processes.

Collaborating with Suppliers using WebSTATISTICA Enterprise QC

WebSTATISTICA Enterprise QC enables automotive manufacturers to collaborate with suppliers through its web interface. This allows for the sharing of supplier data and collaborative review of results.

Anticipating Issues before they Occur with STATISTICA Process Optimization and Root Cause Analysis

STATISTICA Process Optimization and Root Cause Analysis is an exceptional tool for monitoring the manufacturing process at each step along the way, even anticipating quality control problems with unmatched sensitivity and effectiveness. By integrating cutting-edge predictive modeling and data mining techniques with the vast array of traditional quality tools including quality control charting, process capability analysis, experimental design procedures and Six Sigma methods, STATISTICA Process Optimization and Root Cause Analysis allows for complete process understanding, root cause analysis, and accurate predictions of quality outcomes during the manufacturing process.

STATISTICA Process Optimization and Root Cause Analysis allows you to take advantage of existing historical data and find patterns in the data that affect the final outcome. As most automated manufacturing processes involve a large number of steps to get to the end product and interactions between these effects often exist, a traditional experimental design would require far too many runs. Root Cause analysis uses your historical data to find factors and combinations of factors that affect the end product quality.

STATISTICA Process Optimization and Root Cause Analysis builds predictive models that reflect the relationship between manufacturing inputs and outcomes (e.g., conformance to specifications) of the manufacturing process. The models can then be used to simulate runs, finding optimal settings and improving overall quality of the process.

For an overview of the application of predictive modeling to manufacturing processes, read the article from Quality Digest, Finding Direction in Chaos, Data mining methods make sense out of millions of seemingly random data points