Improve Your Process Control with Real-time Insights and Predictive Capabilities
Blog: The Tibco Blog
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The digital factory is powered by new capabilities for processing sensor data—along with big data, machine learning, artificial intelligence, cloud, streaming, and edge technologies. These capabilities facilitate proactive management of processes, products, and factories—culminating in the ultimate process control strategy.
What is Process Control?
Process control is the ability to monitor and adjust processes based on performance. When a process is continuously monitored and controlled, manufacturers can ensure that it works at its full potential, resulting in consistent, quality manufacturing.
Process control has a range of benefits:
- Reduces waste and warranty claims
- Maximizes productivity in a manufacturing unit
- Increases operational efficiency
- Reduces the need for manual inspections
- Enhances customer satisfaction
- Controls costs
- Improves analytics and reporting
Next-generation Process Control Capabilities
With advances in cloud computing, real-time analytics, data science, and other technologies, cheaper and more scalable factory solutions are available, allowing every organization to digitally transform, develop future-ready strategies, and capitalize on opportunities. Here are some key use cases:
Root Cause Analysis
The first phase of a manufacturing program is to identify the root cause of product quality problems. Manufacturers may analyze simple linear correlations between a damaged end product and the upstream process that created it. After identifying the most evident causes of product quality problems, manufacturers may have additional problems more difficult to diagnose. These are often due to complex non-linear effects and interactions between undetectable predictors.
Predictive maintenance uses targeted data for AI-driven analysis, which can anticipate potential failures and increase operational equipment efficiency (OEE). Prescriptive actions can be triggered and make multiple recommendations to plant supervisors. Companies can then schedule maintenance at times with minimal impact on operations, avoiding unexpected equipment and product waste downtime.
Having end-to-end data visibility helps manufacturers get insights from control charts for early warning systems that monitor KPIs or deviations. Process control raises automated alerts. Knowing if manufacturing processes are in a state of control is critical to minimizing production costs.
STMicroelectronics Deploys TIBCO at the Heart of Its Manufacturing
STMicroelectronics sought an industrial-scale deployment of advanced analytics to increase operational performance by industrializing interactive reports, improving data governance, and supporting the company’s goals for data-driven semiconductor production. The company initially developed a solution in-house, leading to performance, maintenance, usability, scalability, and data governance issues.
With TIBCO, STMicroelectronics gained interactive visual performance monitoring (iVPM), delivering immediate insight and actionable guidance with historical and real-time data. Inside manufacturing clean rooms, large analytic-fueled touchscreens display updated safety information, equipment updates, and production priorities for the coming shift. Sharing across sites and organizations is easier, leading to faster decision-making and a higher service level for end users.
TIBCO for Manufacturing
For the modern factory, success relies on transforming from reactive to proactive management. The TIBCO Connected Intelligence platform seamlessly connects data across processes, equipment, and IoT devices, intelligently unifying data for greater access and control.
Using real-time monitoring, TIBCO’s digital manufacturing intelligence allows you and your team to proactively respond to dynamic conditions with AI-infused process control methodologies that predict the future and help you solve potential issues before they become problems.
Learn more about TIBCO’s solutions for manufacturing by reading this whitepaper.
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