Countering the Loss in Efficiency Caused by Mandated Serialization Compliance

Article

igital tracking of overall equipment effectiveness can improve efficiency.

With the November 2017 deadline for the Drug Supply Chain Security Act (DSCSA) looming, US pharmaceutical manufacturers, contract manufacturing organizations, and contract packaging organizations are getting their serialization solutions ready and validated. Few, however, are as concerned with what happens next. While widespread track-and-trace adoption will help mitigate many longstanding problems-counterfeiting, supply chain security, pinpointing recalls-it will create issues well beyond the immediate hassles of infrastructure investment, implementation, and validation. Most prominent is loss in production line efficiency. As manufacturers continue to outfit and upgrade packaging machinery to comply with regulations, the extra steps in serialization (and aggregation) will bring an unwelcome 5–10% reduction in overall equipment effectiveness (OEE), as experienced by early adopter countries such as Turkey. Some companies have seen decreases of 20–30%.

The good news is that with serialization incorporation, any process causing an initial slowdown can produce data that, when properly interpreted, can reveal a roadmap to restoring OEE to pre-track and trace levels, or even higher. Data generated by serialization compliance can be parlayed into guideposts for improving production practices. The metrics are there for the mining, allowing manufacturers to track and trace their operations along with their pharmaceutical products with exceptional granularity.

Serialization implementation and the data mining it affords are the first vital steps toward transforming pharma production facilities into digital factories whose foundations are built on web-enabled and data-driven technologies. Its advantages touch every aspect of manufacturing, including enterprise-wide resource allocation, asset tagging, and real-time inventory and personnel tracking.

Digital factory transformation

Tomorrow’s digital factories can use a three-tiered digital transformation process to successfully deliver the promise of smart manufacturing, or Industry 4.0. The race is on for manufacturers to optimize production practices by navigating from data to dashboards to decisions. In doing so, they will apply mined information toward comprehensive yet digestible operational feedback that, in turn, leads to logical adjustments for improved production practices. The three “D”s of this process are described as follows:

  • Data. Unique unit-level serial numbers for enhanced supply-chain product visibility are only the beginning. Emerging Internet of Things technologies, such as wireless sensors and gateways, offer opportunities to enhance datasets collected by traditional "transaction-based" systems such as enterprise-resource planning, manufacturing execution systems, and warehouse management systems. Additional environmental and location-based data can tremendously enrich previously untapped metrics with unprecedented granularity.  

  • Dashboard. Dashboards convert raw data into actionable insights through business and management platforms, made available to personnel throughout an organization depending on their specific roles. For example, managers could access live dashboards showing all production lines, and view preconfigured reports showcasing exceptions, trends, and downtimes in detail. Undesirable situations can be addressed faster and more effectively. Conversely, optimum outcomes are identified so that ideal conditions can be replicated. 

  • Decisions. Data and dashboards are used for critical resourcing and prioritization decisions. For example, scheduling work orders on shop floors using real-time data and historical trends can significantly improve resource utilization and overtime/waste reduction, while increasing capacity and throughput. 

Scheduling and beyond

Replacing manual or paper-based tracking with a digital tracking system improves operational visibility and allows identification of procedure-driven activities that show significant variability in duration so that managers can identify areas for improvement. Such systems can also help allocate personnel more efficiently, in real time. More fundamental performance improvement can use digital tracking of shop floor activities to create a more robust scheduling process. Digital tracking can thus improve management of operations.

About the Author

Evren Ozkaya, PhD, is founder and CEO of Supply Chain Wizard, LLC, www.supplychainwizard.com.

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