As the Industrial Internet of Things enables more and more wireless instrumentation, the ability to transform maintenance practices to become more predictive grows. While companies in several industries have moved to predictive maintenance practices, companies in other sectors have been somewhat slower to adopt them.
In a new paper published by the BioPhorum organization, Smart Maintenance Architecture: A Data-Driven Approach to Smarter Maintenance, Emerson’s Jonas Berge joined with experts from Applied Materials, Bristol Myers Squibb, GSK, Merck, Roche, and members of the BioPhorum team to collaborate and publish this paper. Here is the executive summary opening.
This paper describes use cases and their technical solutions for implementation of predictive maintenance solutions in the biopharmaceutical manufacturing environment. Predictive maintenance is a significant component of smart maintenance which comprises extra elements such as smart use of computerized maintenance management software (CMMS), digital twin technology etc.
Potential measurements to quantify the value of a shift to predictive maintenance include:
- Better safety
- Increased capacity
- Reduced unplanned downtime
- Reduced time for preventive maintenance
- Increased equipment reliability and plant availability
- Reduced deviations and related investigations along with a reduction in product discards
- Reduced maintenance cost
- Deeper process knowledge and use of data
- Increased energy efficiency.
The authors cite statistics from a McKinsey study showing:
…that manufacturers and suppliers of technology in the chemical and pharmaceutical industry have the potential to gain 5–15% in plant uptime and to reduce maintenance costs by 18–25%.
Also, at the Achema Pulse 2021 event, Telstar shared:
…a return on investment (ROI) of 5–20% downtime reduction and 10–40% maintenance cost reduction.
The authors conclude the Executive Summary section by highlighting that:
BioPhorum members are developing smart maintenance capabilities in a variety of ways, from wholly outsourced to third parties, through blends and collaborations, to wholly in house. The smart maintenance workstream recognizes the value of using the digital plant maturity model (DPMM)6 to baseline the capabilities of the organization/plant to help target investment and plan accordingly.
Visit the Smart maintenance architecture – data-driven approach to smarter maintenance page to download the whitepaper. Key content areas include:
- Introduction and background
- Scale of types of smart maintenance
- Scope
- Current landscape
- Basic system architecture and components
- Expected result
- Conclusion
- Appendices including use case examples and learning from smart maintenance proof of concept (POCs) in BioPhorum member companies.
You can find other excellent papers to improve biopharmaceutical manufacturing practices on the BioPhorum website and in posts tagged with BioPhorum here on the blog.
