10 Ways Real Time Data Is Revolutionizing Manufacturing

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Competing for new opportunities and growing quicker than competitors requires real time data and the insights it provides.

All manufacturers are pursuing greater speed, scale and simplicity across every area of their operations. Real-time data is the catalyst making these three goals and many others possible to achieve.

For many manufacturers, they are competing more against time and customers’ continually increasing expectations of consistent manufacturing quality.  Of the many areas where real-time data is contributing today, product quality is one where the results are most measurable and revolutionary.

The technologies enabling real-time data capture are also fueling a revolution in manufacturing quality. Programmable logic controllers (PLCs) are now commonplace across many manufacturing operations, providing real-time data on machine quality, reliability, and performance.

Machine to machine (M2M) technology is also bringing real-time data to Statistical Process Control (SPC) applications capable of providing real-time alerts, graphs and reports. And the potential for Internet of Things (IoT) to capture data that has eluded manufacturers for many years is now within reach.

From the shop floor to the top floor, real-time data is one of the most powerful catalysts enabling greater manufacturing growth. By improving the quality of decisions, real-time data is meeting a diverse and demanding series of needs across every phase of manufacturing today.

The results are greater revenue earned from higher levels of compliance, manufacturing quality and best of all, delighted customers.

The following are 10 ways real-time data is revolutionizing manufacturing:

Knowing which production processes, machines, work centers and product lines are operating at high-quality levels and which aren’t is essential for keeping shop floor operations running smoothly. Having real-time data to use in SPC for continually tracking, controlling and fine-tuning manufacturing processes is key.

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Machine operators can also get a real-time view of process performance using quick inspection, control and trend charts. Setting up alerts in SPC Modules to alert quality management, production engineering, and scheduling when there is a deviation in performance can help avert millions of dollars in lost production time.

Given the rapid advances in PLC-based monitoring and Machine to Machine (M2M) interfaces, it’s possible to capture real-time data on metrics and Key Performance Indicators (KPIs) of interest.

Collecting data across the shop floor in real-time and looking for patterns, trends and predictive insights form the foundation of Manufacturing Intelligence.

It’s possible today to capture item number, manufacturing number, work order details, lot numbers, date, time and additional KPIs to make traceability one of the strongest aspects of a manufacturing operation.

It’s best to consider fixed production times on the Bill of Materials (BOM) as an average or median estimate that can vary widely depending on work center assignments, parts availability and many other factors.

By having real-time data, the production time on BOMs can be fine-tuned and checked for accuracy. Without it, long-standing assumptions of fixed production times can hold an entire production line back from accomplishing more.

Greater schedule accuracy based on real-time data from the shop floor makes production plans more efficient, increasing work center productivity and improving machinery utilization as well.

Manufacturers who are the quickest at delivering complete quotes are the ones winning the most deals. Providing ATP and CTP dates on every quote requires real-time integration between quoting, selling and manufacturing systems that scale across a company’s entire product line.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.