MAY-JUN 2017

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Level 1 Predigital plant Level 2 Digital siloes Level 3 Connected plant Level 4 Predictive plant Level 5 Adaptive plant Primarily paper-based processes Predominantly manual processing Low level of automation Basic PLC controls Applications are standalone with minimal or no integration. "Islands of automation" Some manual processes Batch records may be semi-electronic or "paper on glass." Local batch-recipe system interfaced to PLCs Site-specific systems; limited integration across functional siloes Analytics on demand, "Why did it happen?" high manual effort Plants operate independently with little "real-time" supply chain visibility. Vertical integration ERP, LES, MES, and automation layer are fully integrated to support digitized business processes. Full electronic batch record with review by exception Industry standards, such as ISA-88 (recipe) and ISA-95 (material, equipment, and personnel) have been adopted. Standard application platform is adopted across plant network. Analytics semi- automated, "Where else can it happen?" Islands of real-time process analytics Enterprise integration: internal integration of plant to value chain Integration of product development and manufacturing (PLM) Advanced production technologies start to be used. End-to-end supply chain visibility with limited external collaborations (suppliers/CMOs) Enterprise recipe management (ERM) process in place Online/at-line quality testing with real-time release Proactive analytics across plant and internal value chain, "What can happen and when?" Integrated real-time process analytics Simulation used for process modeling and improvements. Full end-to-end value-chain integration from suppliers to patients Modular, mobile, and collaborative manufacturing environment Advanced production technologies used as standard "Plug-and-play everything" from an instrument to a production scale or a CMO Zero system downtime (including upgrades), continuous evolution Inline, real-time, continuous, closed loop, process verification and control with automated real-time quality release Self-aware, continuously adaptive "autonomous" plant; exception conditions handled by remote experts Advanced simulation used across value chain for modeling, testing, and improving manufacturing and supporting business processes. Trusted information insights are freely and securely available. Pervasive use of adaptive analytics and self/ machine learning across value chain SYSTEM INTEGRATION INTECH MAY/JUNE 2017 33 Figure 1. DPMM: Definitions of levels The DPMM covers not only what is possible to- day, but also defines an advanced-level adaptive plant that is currently beyond the capabilities of manufacturing and IT technologies. The content of the model was developed with the BioPhorum Technology Roadmap (due to be published mid- year), as well as with input from some key IT ven- dors and initiatives such as Industry 4.0. The white paper introduces the DPMM and its uses as both a tool for companies to plot their digital journeys and to identify the common challenges for com- panies wishing to increase their maturity level. The model has five levels that characterize the different stages of digital maturity of the plant and its relationship with the wider value chain. These are described at a high level in figure 1. Digital Plant Maturity Model for XYZ Company Trend Level 1 Predigital plant Level 2 Digital siloes Level 3 Connected plant Level 4 Predictive plant Level 5 Adaptive plant Business capabilities Manufacturing execution and process automation Steady Mature Mature Lab execution and quality management Up Mature Mature Emerging Manufacturing support Steady Mature Mature Production planning and supply chain Up Mature Mature Emerging Enabling dimensions People and culture Up Mature Mature Emerging Business insights and analytics Up Mature Mature Emerging End-to-end value chain integration Steady Mature Mature Systems interoperability and governance Steady Mature Mature IT security and operations Up Mature Mature Emerging Figure 2. Simple plant assessment tool

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