15079 1
- 1. A Hybrid Approach for Leveraging ERP (SAP)
and MES Functionality within
Integrated Biopharmaceutical Manufacturing
Environments
Presented by Farukh Naqvi
SAP/MES Consultant
EnteGreat, Inc.
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 2. Problem Statement
• Today, Pharmaceutical companies face a wide assortment of
problems concerning Plant-Manufacturing IT systems, Supply chain
applications and quality requirements that are unique to “growing”
Biologics manufacturing.
• In an Integrated Manufacturing Organization with Various Levels of
Manufacturing Complexity:
• Taking a one size fits all approach is both short sighted and limiting
• Implementing customized solutions for each area of manufacturing encourages
complexity which quickly becomes extremely difficult to sustain
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 3. Goal of this Presentation
• The goal of this presentation is to provide a holistic view of both the
problems and potential solutions which leverages SAP investments
to address the complexity of the biologic’s manufacturing operations
(Fill, Finish and Biochem) by synchronizing the functionality with
shop floor execution systems based on ISA S.88 standards.
• Observations are Based on the Analysis of Three (3)
Biopharmaceutical Organizations
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 4. Agenda
The Expanding and Evolving Biologics Market
“Shop Floor Granularity”
Overview of Manufacturing Complexity in Biopharmaceuticals
High Complexity Processes (Biochem and API Manufacturing)
– Functional Assessment of Planning, Scheduling and Execution in
High Complexity Manufacturing
– Lessons Learned and Benefits
Low Complexity Processes (Filling and Finish)
– Functional Assessment of Planning, Scheduling and Execution in
Low Complexity Manufacturing
– Lessons Learned and Benefits
Conclusions
Question and Answer
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 5. The Evolving Pharmaceutical Value Chain
The Expanding Role of Biologics in the
Pharmaceutical Industry
– Monoclonal Antibody – 12 - 13% Growth
– Vaccines – 13 -14% Growth
– Therapeutic Protein - 6 – 7 % Growth
– Small Molecule – 1 -2 % Growth
Molecule Size and its Supply Chain
Impact
– Freeze and Thaw / Time Out of
Refrigeration (TOR)
– Tank Management
– Campaign Planning
– Fill and Finish “3rd Party Logistics”
– Material Planning& Maintenance Planning
Enterprise Goal vs. Manufacturing Goal
– Granularity and Visibility Objectives
Manufacturing Validation & Standards
– ICH 09 / 10
– ISA 88 / ISA 95
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 6. Visibility and Goals: Enterprise vs. Plant Level
Enterprise Goals vs. Manufacturing Goals
– Example: Sensitivity for the Requirements and Technologies “While a
10 second delay for posting to the ERP may not be an issue, it could
spell disaster for manufacturing (i.e. lost product, safety issues, etc)”
• Shop floor Granularity is a Denominator to Define the Variability of
Manufacturing Processes
• S88 is a Vehicle for Establishing Common Denominators
(Granularity)
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 7. S88 Model: Procedure, Physical, Process Model
Information Plant Result
combined achieves
with
Procedural Physical Process
How Using What
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 8. Example: Unit Operation and Unit Procedure
Charge
Liquid 1 Material
Charge
Material
Liquid 2
Reactor 1 Reactor 2
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 9. Definition of Shop Floor Granularity
Unit Operation (Process Cell)
• A logical grouping of equipment that includes the equipment
required for a batch.
• May contain more than one grouping of equipment needed to
make a batch.
• The grouping is referred to as a Train, which may contain a flexible amount of equipment:
Equipment Modules and Control Modules.
• Can be defined as a part of a recipe that defines the strategy for
producing a batch within a Process Cell.
Unit Procedure (Phase at Equipment)
• The lowest level Equipment in the physical model that can
carry out basic function
• Usually centered around a piece of process equipment such as a filtration
column or fermentation tank Containing all equipment and control functions necessary to
perform its process function.
• Can be defined as a Phase is the lowest level of procedural control in the procedural control
model. A Phase is an individual step in a recipe at a process equipment level.
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 12. High-Complexity Processes
(Biochem and API Manufacturing)
• Multi stage sequential manufacturing
• Long lead times
• High shop floor automation with multiple systems
• High variability due to non–deterministic routing
• High analytical monitoring
• Multi stage batch release
• Multi level batch and equipment hierarchy
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 13. High-Complexity Processes:
Planning in SAP Scheduling and Execution in MES
Demand and Production Planning:
• Campaign Planning based on Forecast
• Capacity Planning based on Demonstrated Capacity
• Unconstrained Material & Labor Plan
• Bottom-up Planning
Finite Scheduling in MES Layer
• Unit Operation and Procedure Level
• Unique Constraints to be Modeled: Labor, Equipment, Environment, Material
Manufacturing Execution in MES
• Multi Stage Sequential Manufacturing
• Very High Deterministic Dependencies between Operations
Standard SAP MRP or enterprise-level APS (APO) has the capability to
do the production planning across the biopharmaceutical manufacturing
at the Unit Operation Level
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 14. High-Complexity Processes:
Planning in SAP Scheduling and Execution in MES
Planning in SAP , Scheduling and execution in the MES Application
Order / Forecast
Supply – Demand Match
Recipe / Routing
Advanced Multi-Site Long - term
Planning Capacity /Material
&
Scheduling
SAP - APO Production Plan Production Plan Production Plan
Plant Long - term Plant Long - term Plant Long - term
Planned Demand (APS or MRP)
Enterprise Plant Mid - term
Resource
Planning Champaign Plan Process Order 1 Process Order 2 Process Order 3
Plant Mid - term
SAP R/3
Phase 1 - 1 Phase 1 -2 Phase 1 - m Phase n - 1 Phase n -2 Phase n - m
Finite Scheduling Data Historain DCS / PLC
Plant Short - term Work Center Real-time
Manufacturing Manufacturing Order 1 Manufacturing Order 1 Manufacturing Order 1
Execution
Shop floor Shop floor Shop floor Shop floor Shop floor Shop floor
Order 1 - 1 Order 1 -2 Order 1 - m Order n - 1 Order n -2 Order n - m
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 15. High-Complexity Processes: Lessons Learned
Campaign Planning in SAP or SAP - APO
• Have the limited ability to do procedure level constraint based
campaign planning & scheduling.
• Well suited to do campaign planning at operation level
Resource and Material Qualification Planning:
• Limited inheritance in SAP
Finite Scheduling
• Plant level or Procedure level localized Finite Schedule is
best for Biochem Manufacturing
• Not well suited for Non-deterministic routing environments
Execution
• Limited ability to handle freeze and thaw “time out of freezer” applications and
times used “Ex: filtration column & chromatography column”
• Limited ability in execution of sequential upward child – parent relation of a
process order
• Data processing granularity limitations
• Although it has not performed any Finite Scheduling or actual Execution of the
process order on its own, it has been updated with this information in real time by
the MES. To this regard, SAP is the “slave” system
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 16. High Complexity Processes: Benefits
Improves Control and visibility on non-deterministic operations
Improved response time to the changing dynamics on the
floor
Reduces in error due to non–availability of equipment
Improves the batch release time
Improves batch first-time pass
Provides enough granularity and visibility to the enterprise
systems by providing Real time update of the SAP process order on the
WIP status at process cell level and improves customer service.
Relieves SAP from the task of detailed Finite Scheduling – depending on
the order volume, this could mean significant improvement on system
performance in SAP.
Since only the planned order is required for finite scheduling in MES, there
is less dependence on the uptime of SAP for execution purposes. (“Thin”
planned order to planned order interface from SAP to MES).
“Thick” shop order to process order interface from MES to SAP
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 17. Low Complexity Processes (Filling and Finishing)
• Single Step Manufacturing
• Low lead times with cold storage constraints
• Medium shop floor automation with multiple systems
• Medium Variability
• Single Step batch release
• Freeze and Thaw “Time Out of Refrigeration”
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 18. Low Complexity Processes: Planning, Scheduling, and
Execution All in SAP (PI Sheet)
Demand and Production Planning
• Demand – Focused
• Cold Chain Focused
• Top-Down Planning
Scheduling
• MRP
Manufacturing Execution in SAP
• SAP PP-PI / PP Module (PI-Sheet)
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 19. Low Complexity Processes: Planning, Scheduling and
Execution All in SAP (PI-Sheet)
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 21. Low Complexity Processes: Lessons Learned
Demand planning needs a sophisticated planning tool (APO)
Production planning can be handled with simple MRP
Scheduling could be handled with the SAP functionality
Manufacturing execution can be done using SAP PP-PI Module and
Pi-Sheets
Packaging is good process to extend SAP foot-print to
manufacturing execution and leverage SAP investment
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 22. Low Complexity Processes: Benefits
Investments have been made in SAP – that can be leveraged for
fill & finish execution in a practical manner
Provides “One Version of Truth”
Improves Supply Chain Management visibility
Improves batch disposition and improves Quality processes
Improves the Inventory management
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 23. Co-Existence of MES and ERP
High Complexity Low Complexity
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 24. Conclusions
Centralized Demand Planning in Hybrid Complexity
Environment can be done in SAP-APO-DP Providing:
• Push target for Biochem / API Manufacturing (0 -3 years
forecasting)
• Pull target for fill/finish/Packing Manufacturing (0 -3 Months
based on actual demand)
Demand – Supply based Synchronized Enterprise-
wide Planning can be done in SAP APO-SNP
• Improve Planning synchronization and Plant Utilization across
the enterprise
• One Drum – Beat across the enterprise, which results is better
customer service
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 25. Conclusions
Plant-Level Production & Execution Plan is Based on
Manufacturing Complexity
• Campaign Planning based on forecasting can be done in APO- PPDS at the
Process Cell level for high-complex manufacturing
• A MRP Solution will be feasible for low –complex manufacturing
• Enterprise level master data “Recipe” can be maintained at process cell
level to facilitate detailed product costing
• Material Planning for Packaging and Filling can be done using SAP-MRP or
SAP-SNP
Primary Goal of Finite Scheduling is to Optimally and Successfully
Respond and Plan According to Actual Conditions in Execution
• Finite Scheduling is not really required for Packaging or filling and can be
planned and executed directly using PI-Sheet and APO
• Biochem manufacturing, finite scheduling is done better in within MES at
unit procedure level.
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
- 27. Questions
Farukh Naqvi
E-mail: farukh_naqvi@entegreat.com
Phone: 205-968-3050
www.entegreat.com
Copyright © 2007, EnteGreat, Inc. All Rights Reserved.
