Introduction and Overview
Modern visualization, statistics, and machine learning tools provide a wealth of methods for analyzing manufacturing data. TIBCO Spotfire® provides the ability to build out a wide variety of solutions to better understand equipment, processes, products, operations, customers and sales; and then to act on the insights gained.
Spotfire is used in many manufacturing companies throughout the world in the following industries: semiconductor, electronics and medical devices; automotive & aviation; equipment manufacturing, pharmaceuticals; chemicals, metals and mining and consumer products goods
Some of the key capabilities and use cases relevant in this sector include:
Key Spotfire Capabilities:
- Ad-hoc data discovery with interactive visualizations and built-in statistics
- Seamlessly integrate advanced analytics and machine learning into dashboards using in-built TIBCO Enterprise Runtime for R and other (SAS, Matlab, etc.) engines
- Big Data analysis via Spark, Hadoop and other connectors
- Scheduled to real-time Alerting with streaming sensor data
- Enterprise-class platform to quickly and easily configure lowest-cost custom solutions
- Dashboards available on cloud, desktop, tablet or mobile devices
Key Use Cases
- Product Quality and Reliability
- Machine learning to accurately model and predict equipment, process and product results
- Process Control and Capability with alerting
- Equipment maintenance: Predictive, condition-based and scheduled with alerting
- Management dashboards including KPI charts.
- Demand forecasting, inventory optimization, supplier performance
- Resource modeling and optimization
- Customer Analytics – customer & product segmentation, cross-sell / up-sell opportunities
- Sales - Pricing optimization and Account management
OEE Global Operations dashboard
Core Manufacturing Use Cases
Quality and Reliability of Products and Processes
Gain insight into quality and reliability issues. Spotfire helps manufacturers to identify, understand and minimize problems due to process variability, incoming supplies, test or design. An intensified interest in product quality and reliability analysis is being driven by a number of market forces. As Lean and Six Sigma manufacturing methodologies take hold in industry after industry, customers’ expectations continue to rise. Reliability failures are more visible and sometimes more costly than ever before. Meanwhile the forces of technology, globalization and regulation make our quality and reliability calculations more complex and urgent. Many of the world’s largest manufacturers are turning to TIBCO Spotfire to identify issues earlier, respond more rapidly and effectively and then build better products.
Equipment Commonality Analysis - Effect of Machine on Paper Towel Product Quality
For semiconductor manufacturers, yield analysis can include wafermaps, zonal, pattern and defect analysis
Semiconductor wafer yield analysis
Read the Six Sigma datasheet - Six Sigma is a business management approach that seeks to improve performance by reducing errors, outliers and process variability.
Machine Learning is a recent evolution in advanced analytics that can help uncover the causes of complex manufacturing problems and make accurate predictions about when and how to improve maintenance and operations. The following assets provide an overview of relevant machine learning techniques and how they are being applied to yield and quality improvements, predictive and condition-based maintenance, micro-segmentation of markets, and resource optimization. Watch Video. View Slides. Read Whitepaper.
Machine Learning - Effect of process measurements on product yield - shows nonlinearities & interactions
To learn more:
- Read the blog article on Creating a Big Data Analytic workflow that features use of a machine learning algorithm to understand a manufacturing big data product quality problem
- View the video presentation on Integrating Spotfire with H20 machine learning featuring manufacturing quality use cases
- Visit the Machine Learning Wiki page
- Download machine learning analysis templates and data functions for manufacturing from the Community Exchange
See how Spotfire can help you monitor and predict claim rates. analyze root causes of reliability failures and analyze warranty repair and call center activity.
Warranty analysis for all components of an automobile model
Read the Warranty and Reliability datasheet
View the Warranty claims demo
See how customers are addressing quality and reliability problems with Spotfire:
Predictive and Scheduled Equipment Maintenance
The expansion of connected sensor data creates new business opportunities for monitoring machine performance and failures in the field and on the factory floor. Service organizations have up-sell opportunities to offer options to their customers for maximizing value of their assets. Manufacturers can increase uptime, minimize costs, and optimize processes for expensive equipment on the factory floor. TIBCO Spotfire® helps organizations optimize maintenance schedules by monitoring and responding to key signals in sensor data. In general, fixed assets— vehicles, plants, and machinery, communication devices and computers, and even buildings, are becoming smarter. But they are also becoming more complex and more costly to repair. Spotfire can help you understand these machines more fully, monitor them in real time, and react faster to impending issues. TIBCO supports the following maintenance use cases: • Predictive maintenance with automatic notification of impending failures • Minimizing scheduled maintenance costs • Root cause analysis of equipment failures.
Real-time dashboard showing predicted pump fails
View a short video on Using pump sensor data to predict and prevent failures
Read the Spotfire and OSIsoft PI System Interactive Analytics data sheet - Analyze OSIsoft PI System data, mashed up with other data sources and visualized within Spotfire, to bring new, rich insights into product quality, operations, distributed assets, and the Internet of Things.
To learn more:
- Watch a webinar on Event Analytics in Machine Management
- Download and try out the Industrial Equipment Accelerator on the Community Exchange
Process Control and Exception Reporting
Control charts are widely used in the Manufacturing, Technology and many other sectors. They are the foundation of early warning systems that monitor key metrics, detect deviations from the baseline, and generate automated alerts. See how Spotfire supports many types of Shewhart and custom charts; integrated limits generation, storage and deployment; selection of rules to detect out-of-control points; tagging and annotation; management and operations dashboards; periodic or real-time alerts; process capability studies and root cause drill-downs
Process Control Summary with drill-down to Control Chart
The Spotfire Plug-in for Alerting allows you to configure alerts directly from any Spotfire analysis file and can be used to alert when rules on any control chart are violated. It is an extension for TIBCO Spotfire that integrates with Automation Services via an alerting task. The task can generate e-mail, text or pop-up alerts.
Try the Dynamic Control Chart demo
Visit the Spotfire Community Wiki Home Page: This is the starting point for an extensive, growing collection of linked Wiki pages covering all things Spotfire. Links to comprehensive, current information on these Main Topics landing pages: Getting Started, Data Access and Wrangling, Visualizations, Maps, Advanced Analytics, Applications and Vertical Solutions, Extending Spotfire, Administration, Partners and more.
Back to Spotfire Wiki home page