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Smarter than the sum of its parts

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Intel drives manufacturing evolution with Internet of Things (IoT) and Big Data Analytics solution, Fusionex GIANT
As a leading driver of innovation in electronics manufacturing, Intel Corporation introduced an Internet of Things (IoT) and Big Data Analytics solution to bring new business intelligence to its manufacturing capabilities. Fusionex played a key role in this solution implementation with Fusionex Insights (GIANT), its big data business intelligence software.
The Challenge
Intel realized that its automated processes were generating an ever increasing volume of data that was not being adequately utilized. Data from disparate sources, including on the network and shop floor, could potentially be leveraged through Internet of Things (IoT) technology to enhance decision-making, leading to better manufacturing efficiency and increased product yields and quality.
Intel required a big data solution that could store, analyze and extract useful information from the massive data sets generated in manufacturing, which comprised different types of structured, semi- structured and unstructured data. The implementation needed to deliver insights that would help Intel extend the life and value of its manufacturing assets by using data to improve maintenance strategies and prevent costly downtime.
Intel looked for an overall solutions matrix made up of end-to-end building block suppliers to enable manufacturing intelligence from the factory floor to the Industrial Data Center (IDC). Key considerations included scalable infrastructure and capabilities to provide clear return on investment (ROI) on the solution and the ability to statistically use manufacturing data from disparate sources to differentiate existing operations.

The Solution
Fusionex provided the business intelligence and analytics capabilities in a Big Data Analytics solution for Intel’s manufacturing process. The end-to-end manufacturing intelligence solution from factory floor to the IDC also included software and hardware building blocks from Cloudera, Dell, Mitsubishi Electric and Revolution Analytics (see Figure 1). The IDC caters to the needs of local factory operations and resides in the local manufacturing shop floor control room. Each IDC ran on a Dell PowerEdge VRTX hardware platform hosting the data analytics and application software, as well as Cloudera Hadoop nodes running in multiple virtual machines (VMs). The analytics and application software workloads included Revolution R Enterprise from Revolution Analytics, the PostgreSQL open source object-relational database, and Fusionex GIANT. Fusionex GIANT is a Big Data Analytics software solution with streaming capabilities for real-time monitoring and analytics. The technology allows for encapsulation of R-based and other predictive models as “RESTful” web services. The Fusionex solution provided integration capabilities such as connecting and synchronising multiple data sources, performing data warehousing ETL tasks, empowering end users to discover, drill down, and drill through inexploration of underlying data.
Through Fusionex GIANT, the manufacturing data could be prepared, analyzed and presented in easy- to-understand visualisations. The Intel Big Data Analytics project also implemented IoT gateway devices to transmit manufacturing data from factory equipment to the IDC. Each gateway consisted of a Mitsubishi Electric C Language Controller of the MELSEC-Q Series.

The Benefits
The solution ultimately provided four main benefits:

  • Increased manufacturing throughput
  • Higher yields
  • Improved efficiency
  • Reduced downtime

Intel recorded results and benefits in three very distinct problem areas across different types of data and production processes.
Reducing non-genuine production yield loss through monitoring and analysis of machine parametric values and timely replacement of parts before they fail: By using monitoring and analytics, Intel was able to predict up to 90 percent of potential failures of test equipment. This early notification prompted the replacement of defective test equipment before incorrect diagnoses could occur. This reduced yield losses from false diagnoses of manufactured devices as being faulty by 25 percent.
Reducing yield losses by minimizing incorrect ball assembly in ball attach equipment: By visualizing and correlating sensor readings with various machine and execution data, Intel was able to minimize incorrect ball assembly in solder ball attach equipment. This resulted in reduced yield losses, optimized maintenance costs and avoidance of sudden equipment downtime.
Using image classification to identify good or defective units: Image analytics identified defective units from a pool of marginal units ten times faster than manual inspections, saving the time required to ensure product quality.
The IoT and Big Data Analytics solution has helped Intel to address its current and future manufacturing needs while producing a clear ROI. Intel’s project utilized building blocks from Fusionex and other hardware and software suppliers to create a scalable solution for differentiating manufactur
operations with business intelligence.
The project is forecasted to save Intel millions of dollars annually, along with other business value that Intel is still realizing. The monitoring, analytics and modelling provided by the solution allowed Intel to improve equipment component uptime, minimize yield losses, facilitate predictive maintenance and reduce component failures.

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