Rutgers CM Seminar - QbD Process Tech 051716-R1

Advanced Process Automation
and Data Management
Solutions for Continuous
Manufacturing
Paul Brodbeck
Chief Technologist
QbD Process Technologies, Inc.
ContinuousPlant™ Software Suite

2
QbD Process Technologies
AgendaAgenda
• QbD Process Technologies Overview
• Process Automation System Supervisory Controller – DeltaV
– Unit Operations Integration for Continuous Manufacturing (CM)
– Process Analytical Technology (PAT) – synTQ
• Process Automation Architecture
– S88 Batch Model for Continuous Manufacturing (CM)
– CM Architecture of the Future (Rutgers)
• Materials Characterization / Database
• Enterprise Master / Network & Recipe Management
– PAT Enterprise Master / Network – synTQ
– Enterprise Master / Network – DeltaV Process Automation System
– Recipe Management – DeltaV
• Data Management for Continuous Manufacturing (CM)
– Statistics Portal – Statistica
– Big Data Platform - Sinequa
– Continuous Data Historians / Dashboards – OSI PI
– QbD Materials Traceability/Batch Reporting
Advanced Process Automation and Data Management Solutions for Continuous Manufacturing

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Continuous Manufacturing (CM)
Continuous Manufacturing (CM)
• Develop and apply innovative real-time
software, applications and integrated solutions
that enable manufacturers to integrally design
quality into the control of their continuous drug
product manufacturing processes
• Integrate advanced process automation
solutions with real-time Process Analytical
Technology (PAT) orchestrations, advanced
process control (APC), and data management
of Critical Process Parameter (CPP) variables
that affect predefined and measured Critical
Quality Attributes (CQA)
• Enable manufacturers to make drug products
more efficiently, reliably and of better quality
than traditional batch manufacturing methods
• Enable the implementation of emerging
technologies in the fields of PAT and
Continuous Manufacturing
Mission Key Objective & Goal

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What is ContinuousPlantTM Software Suite?
• Suite of real-time (RT) software that
enables pharmaceutical and biotech
manufacturers to deploy advanced real-
time continuous manufacturing processes
– Integrates production equipment with
advanced real-time advanced process control
(APC) applications, in-process Process
Analytical Technology (PAT) orchestrations,
continuous process data historian and
material traceability data management
system

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Rutgers Continuous Manufacturing PlantRutgers Continuous Manufacturing Plant

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DeltaV Process Automation System
Supervisory Controller
DeltaV Process Automation System
Supervisory Controller

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Unit Operations Integration
K-Tron Feeder
K-Tron Feeder
• PROFIBUS
– International standard for digital data
transfer in process automation
• DeltaV reads / writes SPs / PVs with K-Tron
Feeders
• Recipe loads formula, SPs and process
parameters and Sequence of Operations to
K-Tron Unit Operations
• DeltaV executes Feeder Sequence of
Operations
• DeltaV Ratio & Mass Balance Control
• QbD ContinuousPlant™ Real-Time (RT)
Throughput Optimization
– Process flow optimizer to control and
maximize plant production flow/feed rate
or throughput and product quality within a
user defined design space
K-Tron Control Parameters in DeltaV
• Hopper Weight (WT)
• Feed Rate (PV)
• Feed Setpoint (SP)
• Controller Output (PV)

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Glatt Blender and Granulators
Glatt Blender and Granulators
• Interface to Glatt equipment using
DeltaV classic IO or Ethernet/IP
• DeltaV starts/stops Blender directly
• DeltaV sets Blender speed directly
• DeltaV recipe loads formula, SPs and
process parameters and Sequence of
Operations to Glatt Unit Operations
• QbD ContinuousPlant™ Real-Time
(RT) Process Optimizer
– Advanced process control (APC)
algorithm used for optimizing blend
uniformity of a continuous blender
– Varies the rotational speed to minimize
Relative Standard Deviation (RSD)
• DeltaV can read and write process
parameters from Glatt Wet and Dry
Granulators

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Fette Tablet Press
Fette Tablet Press
• OPC Server
• DeltaV reads / writes / all OPC Tags
• Fette HMI tags displayed on DeltaV
• Press can be operated from DeltaV
• Recipe loads formula, SPs and process
parameters and Sequence of
Operations to Fette Unit Operation
• Rutgers C-SOPS working on feedforward
and feedback control loops to Press
through DeltaV
• Press speed varied to maintain level

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synTQ Process Analytical Technology (PAT)synTQ Process Analytical Technology (PAT)

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synTQ Process Analytical Technology (PAT)synTQ Process Analytical Technology (PAT)

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Process Automation Architecture
S88 – Process Model
S88 – Process Model
• Common Philosophy/Architecture from
Development Thru Commercialization
• Improved Tech Transfer
• Contextualize Data

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S88 Batch Model − Physical & Software
S88 Batch Model − Physical & Software

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S88 Batch Adapted for Continuous Manufacturing (CM)
EQM
FEEDERS
(PROFiBUS)
EQM EQM
BLENDER
(VSD)
TABLET
PRESS
(PLC)
EQM
RAW
MATERIAL
CoA
EQM
TABLET
TESTER
(OPC)
EQM
DRUMMING
STATION
(OPC)
UNIT UNIT
PLANT
PROCEDURE
(RECIPE)
UNIT
ENTERPRISE
RECIPE/
FORMULA
PROCESS
CELL(s)
COMMUNICATIONS
ETHERNET/IP – MODBUS/TCP – OPC – PROFIBUS
PHASE PHASE PHASE
OPERATION OPERATION OPERATION
PHASE
OPERATION
CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM
DATABASES

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CM Architecture of the Future (Rutgers C-SOPS 2-3 Years)
CM Architecture of the Future (Rutgers C-SOPS 2-3 Years)

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Materials Characterization / DatabaseMaterials Characterization / Database
• Method automation with synTQ
• Materials database (SQL)
• synTQ reads / writes data to
materials database and LIMS
• Raw material testing results in real-
time with bar coding
• Materials data integrated in real-
time Models for feedforward control
• synTQ can control off-line
analyzers / calibrate / read
diagnostics
• Print Certificate of Analysis (CoA)

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Materials DatabaseMaterials Database
• Stores material properties for products used in Continuous
Manufacturing (CM)
• Materials properties used to optimize formulas for CM
• Materials properties used to develop Models
• Models used to design the optimal CM Plant
• Manufacturing
– Raw Material Data captured in real-time is compared to
properties in materials database and used for control models
running in DeltaV

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synTQ Enterprise Master / NetworksynTQ Enterprise Master / Network

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DeltaV Enterprise Master / NetworkDeltaV Enterprise Master / Network
DeltaV
Development
DeltaV
Manufacturing
Plant1
DeltaV
Manufacturing
Plant2
DeltaV
Enterprise
Master
SQL dB Replication
Continuous Data
SQL dB Replication
Manufacturing
Network
Enterprise/Business
Network
Or Cloud
OSI PI
Data
Historian
Continuous Data
Recipe
Control Logic
Recipe
Control Logic

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DeltaV Recipe ManagerDeltaV Recipe Manager

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Data Management
Statistica – Data Analytics Enterprise Server
Data Management
Statistica – Data Analytics Enterprise Server

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Big Data Management
Sinequa – Real-time Big Data Search & Analytics
Big Data Management
Sinequa – Real-time Big Data Search & Analytics

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Data Management
Continuous Data Historian / Dashboards – OSI PI
Data Management
Continuous Data Historian / Dashboards – OSI PI
OSI PI Buffer Subsystem Architecture
Business Intelligence Dashboards
Quickly create web
dashboards using existing PI
Elements

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Data Management
Contextualize – OSI PI Asset Framework
Data Management
Contextualize – OSI PI Asset Framework

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• Process Prediction
– Analytical measurements for real-time quality information
– “Soft Sensors” to back-up analyzers and predict other hard to
measure process parameters
– Provide real-time predicted values to help Operator improve
process control
• Process Fault Detection
– Fault detection indicates a “statistically abnormal” operating
condition
– Provide operators with information on which inputs are root cause
of problems
• On-line Operations Interface
– On-line quality predictions and fault detection help operator prevent
quality incidents and downtime
DeltaV Embedded AnalyticsDeltaV Embedded Analytics

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Data Management
Advanced Data Management & Control
Data Management
Advanced Data Management & Control
PAT Orchestrations at Runtime
Spectral Data

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Data Management – Material Tracing for CM
ContinuousPlant™ RT Materials Traceability Model
Data Management – Material Tracing for CM
ContinuousPlant™ RT Materials Traceability Model
Recalculated Every Second

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SummarySummary
• Objective - Apply real-time software,
applications and advanced process control
solutions that enable pharmaceutical and biotech
manufacturers to integrally design quality into the
control of continuous manufacturing processes
• Deploy a process automation integration model
that enables manufacturers to deploy advanced
real-time continuous manufacturing processes
– Integrates production equipment with advanced real-
time advanced process control (APC) applications, in-
process Process Analytical Technology (PAT)
orchestrations, continuous process data historian and
material traceability data management system
• Goal - Enable production of drug products more
efficiently, reliably and of better quality than
traditional batch manufacturing methods
Paul Brodbeck
Chief Technologist
QbD Process Technologies, Inc.
paul.brodbeck@qbdprocess.com
http://www.qbdprocess.com/
Advanced Process Automation and Data Management Solutions for Continuous Manufacturing

Rutgers CM Seminar - QbD Process Tech 051716-R1

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