Published on 6 May 2014
“ Scenario modeling has helped us assess the economic impact of managing humidity more actively. We expect to achieve a return on investment of 160 percent in the first year – an excellent example of how analytics helps us make better business decisions. ”
Matthieu Lirette-Gelinas, Business Analytics Junior Engineer, IBM Bromont
IBM’s facility in Bromont, Quebec, assembles CPU modules that power servers in banks, hospitals and other organizations around the globe. Each module can contain as many as 19,000 electrical connections, and a fault in just one of these connections could cause a client’s business-critical systems to fail. Every single one needs to be perfect.
When quality control systems on the production line detect problems, does it just mean that the specific items that failed the test are faulty, or could there be a problem with the whole batch?
Rather than commissioning time-consuming and expensive lab tests to answer this question, IBM Bromont is using analytics to identify fault patterns and predict outcomes – saving inspection costs and getting production back online again much more quickly.
"What if?” analysis shows that controlling humidity at one point on the manufacturing line will improve product quality and deliver a 160 percent return on investment.
IBM products and services that were used in this case study.
DB2 for Linux UNIX and Windows, Predictive Maintenance and Quality, SPSS Modeler, SPSS Statistics
SPSS Modeler, SPSS Statistics, Predictive Maintenance and Quality, BA - Business Analytics, BA - Predictive Analytics, BA - Predictive and Business Analytics - Predictive Maintenance, Business Analytics, Information Management Foundation, Predictive Analytics, Smarter Analytics, Smarter Analytics - Increase operational efficiency, Smarter Planet, Big Data & Analytics, Big Data & Analytics: Improve IT, Big Data & Analytics: Operations/Fraud/Threats
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