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Production Analytics Key Indicators in Modern Card Issuance: Availability, Performance, Quality

Feb

09

2024

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Shawn Brennan

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Modern card issuance operations have embraced advanced technology, replacing outdated manual methods like clipboard monitoring. Today, operators and managers no longer jot down notes as they walk the floor; instead, they use digital platforms. Alerts, achievements, and operational details are instantly communicated across locations, giving operations executives real-time data to monitor machine performance and critical issues without leaving their offices. The shift to automated data analysis allows operators and technicians to access information from tablets anytime, anywhere, ending the need for manual charting. Additionally, aggregated machine intelligence provides a comprehensive view of plant productivity and cost-effectiveness in real time across multiple sites for an entire corporation.

These advancements are commonplace today, as Industry 4.0 cements itself in manufacturing history. It’s no surprise that digital intelligence brings increased efficiency and ROI opportunities to the forefront of smart card manufacturing. The Entrust Adaptive Issuance™ Production Analytics Solution is a software and technical consulting platform built on delivering this value proposition to card personalization operations through a customizable, real-time, aggregated architecture. It continues to drive next-generation smart manufacturing, bringing positive Overall Equipment Effectiveness (OEE) and enhanced value to operations. OEE is expressed as a percentage sum of three key production indicators: availability, performance, and quality. Let us take a closer look at each and how they bring a deeper understanding to issuance environments, focusing on net losses:

  1. Availability

Availability is the percentage of planned production time the operation is available to run. It is the ratio of Run Time to Planned Production Time and considers loss, which includes events that stop planned production. Run Time is defined as the total time when machines are used for production in a running state, excluding idle and pause. Planned Production Time is defined as the total calendar time for the measurement period minus planned downtime, such as maintenance tasks, changeover, holidays, and shift breaks. Availability Loss includes any unplanned stops such as idle time, equipment failure or material shortage, and planned stops as noted above.

  1. Performance

Performance percentage is the actual total production output compared to theoretical perfect production output, which is calculated using the machine’s maximum cycle speed. A perfect performance score would mean machines are always running at maximum speed when active. Total Production is defined as the total number of cards processed, which includes both good and rejected cards. Maximum Machine Throughput is defined as the maximum machine speed in cards per hour, also considering that throughput could be reduced based on the total number of modules used. Performance Loss includes anything that causes the manufacturing process to run at less than the maximum possible speed when it is running. Examples of things that create Performance Loss include machine wear, inferior materials, line misfeeds, and jams.

  1. Quality

Quality is the number of good units produced as a percentage of the total units started. A perfect quality score indicates that all products are good: successfully manufactured the first time, and no rejects were produced. Simply and more realistically, total production equals good production + rejected production. Quality Loss accounts for manufactured parts that do not meet quality standards as defined by the operation. Examples of Quality Loss include scrap and rework.

Net Losses

Net Losses for all three production indicators can be explored further here from Vorne as variations in issuance type, facilities, and machines contribute to loss variability. The Six Big Losses are also common in issuance operations and include: unplanned and planned stops, small stops, slow cycles, production rejects, and startup rejects.

To learn more about OEE and the three key production indicators, measurement & analysis, and calculating speed and efficiency, read our white paper, “Understanding Production Efficiency in High-Volume Card Issuance Operations.”

The Future of Digital Intelligence and Production Analytics

Machine learning and artificial intelligence are expected to revolutionize the industry further. These technologies will be integral in production planning, inventory management, resource planning, and cost analysis. Next-generation Industry 4.0 subject matter experts will take the output from these technologies and use it to make improvements across operational architectures, building more efficiency into the process. Digital intelligence can be used to mitigate operational bottlenecks, quality gaps, and overall line inefficiencies by focusing on the three key production indicators.

Learn more about the Entrust Adaptive Issuance™ Production Analytics Solution and how it can aid in operational efficiency, utilizing digital intelligence, data analytics, and advanced technologies essential for smart card manufacturing.

Shawn Brennan
Shawn Brennan
Product Marketing Manager, Central Issuance
Shawn Brennan is a Product Marketing Manager in the Central Issuance business segment at Entrust. Shawn joined Entrust in 2022 after 25 years of regulated industry experience in the automotive, aerospace, and mobile telecom industries. His passion for business development and product management parallels his marketing responsibilities in the high-volume Payments and Identity space, bringing transformative unified issuance solutions to market.
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