Industry research indicates that using smart maintenance could mean manufacturers and suppliers in the chemical and pharmaceutical industries gain 5–15% in plant up-time and reduce maintenance costs by 18–25%. Reports also suggest a 5–20% downtime reduction and a 10–40% maintenance cost reduction.
Smart maintenance architecture – data-driven approach to smarter maintenance 3.04 MB 260 downloads
Yet, while predictive maintenance technology is already advancing in the chemical industry, especially with retrofit solutions in aging continuous manufacturing plants, its use in our often batch-based biopharmaceutical industry is still in its early days.
If you are considering or at the initial stages of implementing smart maintenance, then our new paper, Smart maintenance architecture – data driven approach to smarter maintenance , will be ideal for you. It describes the architecture requirements for a basic system to enable smart maintenance – and creates a first step, ‘minimum viable product’.
Helping your digital journey
It extends the foundational material in Smart maintenance: digital evolution for biopharmaceutical manufacturing to support biopharmaceutical manufacturers in their digital journey in two key areas:
- Sharing best practices and industry’s collective data to build and use smart maintenance, which includes predictive models and analytics
- Sharing architectural best practices and use cases to access and leverage data for smart maintenance. These address the key challenges related to data identification, access, integration, advanced smart maintenance analytics, GMP environment, and leveraging proprietary systems, cloud technology, etc.
“This paper enables Emerson’s customers in the life sciences industries to make progress in their digital transformation toward more adaptability in plant maintenance and sustainability improvements,” said Dave Imming, Emerson Life Sciences VP Marketing and Sales Enablement. “It helps summarize, navigate, and justify the myriad of reliability solutions required to get to an adaptive plant – starting with automating manual data collection and its interpretation with robust analytics, while preserving GAMP validation and the robustness of the main automation system. These standard technologies and architecture allow plants to plan and deploy solutions to common plant challenges to become more productive and predictive, thereby reducing maintenance and energy costs.”
Smart maintenance architecture – data-driven approach to smarter maintenance 3.04 MB 260 downloads
The paper includes detailed appendices covering maintenance types (triggers and actions), example use cases, and learnings from smart maintenance proofs-of-concept in six member companies.
Our paper applies to existing and new plants and gives you a host of benefits, such as:
- Helping you optimize your system architecture for faster scale-out and replication across multiple plants
- Giving you defined approaches to allow efficient and effective implementation of smart maintenance, helping you move up the maturity model step by step, in short, agile sprints
- Guiding you toward faster and more cost-effective technology implementation without interfering with compliance
- Providing you with recommendations for selecting tools and technology to accelerate your digital technology adoption and realize targeted business capabilities and benefits.
Dr. Andreas Pies, SVP Engineering & Technology, Global Healthcare Operations, Merck KGaA, said the BioPhorum publication is a timely paper about the steps to implement ‘predictive maintenance’ as a key element of smart maintenance. “It was a great collaboration that looked holistically at the topic from asset maintenance through to manufacturing plant digitization. Improving the maintenance of our manufacturing assets will contribute to our wider smart manufacturing and Industry 4.0 initiatives.”
We have aimed this paper at engineers who build and utilize the digital operational infrastructure that enables smart maintenance; therefore, architecture is described using design, engineering, and implementation terminology. It also includes detailed information for automation and maintenance engineers who are responsible for deployment.
The biopharmaceutical industry is making great strides along the digitization pathway and smart maintenance is contributing to that progress. Yet, the outcomes of proofs-of-concept shared by BioPhorum members show there is much more to implement in this area.
“This document helps Roche to better understand what industry is striving for and supports the harmonization and standardization of potential solutions,” said Michael Clever, Director Technology and Facilities at Roche. “For us, it is the starting point of a challenging journey toward the successful implementation of smart maintenance.” By sharing their learnings in this paper, biopharmaceutical manufacturers and suppliers have increased their knowledge and have started removing the mystery associated with smart maintenance.
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