Using Smart Manufacturing to Enable Energy-efficient Manufacturing of Pharmaceutical Products ​

Project Lead: Rutgers University
Partners: University of Delaware, Johnson & Johnson

Member % Cost Share: 50.07%
CESMII % Cost Share: 49.93%
Duration: 18 Months

Problem Statement

There is a significant market opportunity for the development of SM based platforms to produce pharmaceutical dosage forms such as tablets/capsules. Regulatory authorities such as the U.S FDA have mandated that manufacturing be based more on science- based understanding and data-based analytics compared to the traditional manufacturing practices based on heuristics.

Project Goal

Develop an integrated SM platform to improve the energy productivity and reduce energy intensity of a pharmaceutical tablet manufacturing process via wet granulation (WG), whilst maintaining other performance metrics such as product quality.

Technical Approach

  • Real-time measurement and analysis of material attributes
  • Develop hybrid models to perform virtual experiments and to optimize energy consumption
  • SM-enabled model and data integration for efficient manufacturing
  • Demonstrate reduction in energy consumption and re-usability of prototype components

Deliverables/Outcomes/SM Marketplace

  • Delivered baseline for continuous and batch manufacturing energy requirements
  • Developed and delivered hybrid model and flowsheet model
  • Validated optimal batch production run and continuous production run showing decreased energy consumption
  • Completed techno-economic analysis and comparison of batch and continuous processes
  • Wet granulation process predictive models
  • Analytical methods for wet granulation
  • Near-infrared sensing solutions applicable to other manufacturing processes

Potential Impact

  • Process intensification of production which could lead to ~2.5 times reduction in fixed investment
  • Much shorter times for a production of therapeutics, in terms of time-to-market
  • Crosscutting innovations that could directly be adapted to other manufacturing industries like biologics, food, specialty chemicals
  • Will lead to overall energy and cost savings


  • An integrated modeling, sensing, control and data management program leading to improvements in energy productivity and efficiency
  • Reduction in costs compared by implementing SM techniques into current 
    traditional manufacturing​ practices
  • Training students and industrial practitioners on SM techniques and tools
  • Improvement of the pharmaceutical supply chain which are currently complex and inefficient

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