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Today’s Production Management Systems Enable Lean, Demand-Driven Supply Chains
By Charlie Gifford Director of Lean Production Management GE Fanuc Automation
Current Progress of Production Management applications to meet needs
of Lean supply Chain:
ISA-95-based production management applications enable adaptable lean supply chains
by analyzing and aggregating production data (capacity, capability, inventory,
order and equipment scheduling) and then exchanging information with ERP, APS
and SCM systems.
Developing standards and best practices provide consistency and flexibility by
working interactively in real-time within the supply chain. The resulting framework
enables decision making based on measurable and specific manufacturing constraints,
abnormal conditions (alarms) and events. Adaptable manufacturing is important
to Life Sciences industries to compete in the global markets.
Manufacturing integration standards and methodologies are now endorsed by innovative
end users and enterprise software vendors (IBM, Oracle, and SAP).
Production Management applications are now designed for the larger, interactive
supply chain role.
Vertical industry libraries of production use cases and business processes are
being characterized using ISA-95 and the Open Application Group Integration Specification
(OAGIS). Resulting Production Management software tools are more configurable
and interoperable. Software vendors are developing large libraries of use cases
with configurable components, XML schemas, and templates towards configurable
interoperability framework that support Services Oriented Architectures (SOA).
ISA-95 based B2MML interfaces require much less custom development between production
and supply chain systems.
The required skill set for integrated Production Management systems is now recognized
as a mixture of business process, IT and manufacturing process skills.
Return on investment for Production Management systems has been quantified and
accepted due to a large increase in repeatable applications at a lower cost. |
Life sciences industries are moving to global manufacturing utilizing both contract
and internal production resources. In parallel, manufacturers are figuring out
how to incorporate radio frequency identification (RFID) technology for supply
chain traceability and process analytical technology (PAT) solutions for production
quality assurance and improved manufacturing efficiency. A major benefit of this
dual challenge is that the same production management technologies required for
RFID and PAT solutions are the tools required to optimize globally distributed
manufacturing and supply chains.
Currently, manufacturers are attempting to utilize a wide range of lean supply
chain processes that only function correctly when made accurate by real-time production
information. Consequently, these production management systems provide the lean
triggers for the business process of the lean supply chain.
Life Sciences manufacturing in the 21st Century is fundamentally different than
the 20th Century make-to-stock (MTS) form. The customer base is undergoing a dramatic
shift from countries in North America and Europe to developing economies in India,
China, Africa and South America. As the customer and manufacturing bases become
truly global, large centralized drug inventories must also be continually shifted
to the area of changing demand. Product inventories must then be reduced by the
business by moving to a “pull,” as opposed to “push” supply chain that relies
on smaller, more distributed inventories.
In order to enable demand-driven distributed supply chains, companies are combining:
lean manufacturing techniques, a supply chain management (SCM) system utilizing
RFID product tracking across the supply chains, and an integrated production management
system utilizing PAT product quality tracking and electronic batch recording (EBR)
across production.
The role of a production management system is to aggregate and analyze plant floor
processes, PAT and EBR data into operations metrics. These operations metrics
are reported in near real-time as production capability information and utilized
as lean pull triggers by SCM systems that distribute the customer orders into
an available, cost effective single piece flow through the supply chain.
Contrary to the lean techniques applied to the localized linear 20th century supply
chains that were a 100 percent make-to-stock form, the partial make-to-order lean
supply chains require access to large amounts of real-time production capability
information from all suppliers, contract manufacturers and in-house production
sources. Companies’ SCM systems must be able to determine the most cost-effective
method of global delivery while keeping inventories low and responsive to demand.
Standards-Based Manufacturing Application Framework (MAF)
By supplying production management software technologies to accelerate lean manufacturing,
life sciences companies are able to balance 1) resource availability, 2) profit
margins available in supply chains, 3) quality requirements and 4) end-to-end
operating cost against each other to make the decision on a 100 percent on-time
delivery commitment. Managers execute this commitment decision by evaluating the
state of: The value chain (lowest cost path to customer)
to drive maximum profits The value stream (value-added
path to meet customer’s expectation and quality) Total
end-to-end cost of product throughout available supply chain alternatives Manufacturing
integrations standards such as ISA-95, enterprise-control integration standard,
provide the basis for combining PM systems with lean techniques. Integration standards
establish the lean technique of “Standard Work” which is the foundation for any
lean transformation and single piece/order flow across a pull supply chain. For
example, ISA-95 defines a common Manufacturing Application Framework consisting
of terminology, functions, tasks, and data exchanges for companies to establish
the “Standard Work” component.
Production data based on standard work dramatically simplifies and lowers the cost of information exchanges and business processes between all parties in a lean supply chain. Production management applications based on ISA-95 are easily structured to support single piece flow and allow life sciences companies to quickly transform their large batch make-to-stock manufacturing. These production management applications perform near-real-time manufacturing operations analytics by utilizing online/off-line data collection of plant floor and real-time PAT applications that comply with manufacturing schema standards.
Manufacturing operations are made up of three major data sets: 1) equipment process, 2) product quality, and 3) production operations (routing and recipe) data. PAT systems monitor and correlate the real-time process and quality of work-in-process (WIP) products. To enable lean standard work, this PAT data set is then correlated to production operations data in production management applications for analysis and reporting of available production resources and state of work orders to the supply chain systems.
Production management systems can map and aggregate PAT time-based, event-driven
data into production-use cases characterized by ISA-95 models for manufacturing
analytics that produce the necessary supply chain metrics. Plants need to develop
and establish a consistent canonical plant model by applying “Standard Work” across
the production management and supply chain management systems schema and business
rules.
The Standardization Effect graph further illustrates how a Manufacturing Application Framework combined with lean practices allows a company to adapt to the market changes by quickly stabling a new single piece flow business process in manufacturing or a supply chain.
The development of a MAF system allows a manufacturer to standardize on a single
set of terminology, workflow processes, metrics, analysis techniques, and reports.
The framework acts as change management function by maintaining this single production
schema as the production environment changes over time.
PAT and RFID data enable the following supply chain functions: Define customer
value stream: Benchmarking and fine-tuning production activities and customer
order quality status; Just-in-time (JIT) transportation and distribution by coordinating
“pull” logistics with accurate data;
Value-added engineering and design by refining product characteristics to reduce
waste; Made-to-order sales by mapping customer specifications and due dates directly
to the most cost effective suppliers and production facilities by order; Procurement
triggering based on JIT inventory levels for replenishment and fulfillment; and
Total Productive Maintenance (TPM) methods by preventing equipment breakdowns
with OEE methods such as equipment wear profiles based on quality and product
data.
PAT plant floor data only enables supply chain processes if, first, contextualized
into a production operations data model using the common ISA-95 definitions for
work units, orders, route, and production resources. This canonical operations
data model is applied across all production and supply chain systems to “Lean
Out” business processes for supply chain optimization.
Lean production techniques enabled by common data definitions and schemas include:
Single piece flow and line balancing Analytics, metrics,
alarms and events for reporting Method comparisons of
activities and work Standard costing or activity-based costing metrics
Labor performance measurement and control Manpower and
production requirements Payment by results (incentives)
Business cost justification Standard product design and
planning for methods for manufacturing & quality Standard work flow practices
across manufacturing activities: Production, Quality, Maintenance, & Inventory
Operations Common work definition for operations and resources A single XML production
canonical schema across manufacturing applications simplify interfaces and data
exchanges
The first step to optimize the 21st Century manufacturing enterprise is to recognize
that production process, use cases (transaction sequence), and data exchanges
must be identified and characterized by utilizing lean manufacturing and/or Six
Sigma characterization techniques. In manufacturing analytics, supply chain key
performance indicators (KPIs) need to be mapped to standards-based operations
metrics that are based on cause/effect relationships (compromises) for production
use cases. The ISA-95 standard is the enabling tool for executing the functional
system design efficiently and evolving lean production management applications
allow currently optimized lean workflows to quickly adapt and respond to demand
changes in global markets.
Examples of Lean Production Management include:
“Standard Work” for single schema product tracking, electronic batch record, and
performance reporting;
Finite Capacity Scheduling enforcing single piece flow and “Theory of Constraints”
for line balancing;
Utilization management such as OEE with resource benchmarking to accelerate Lean
cultural change;
Quality and operations statistical analysis using statistical process control
online, at-line, offline) and laboratory information management systems (LIMS);
and
Role-based manufacturing portals for interdepartmental communication of real-time
situations with defined event management sequences (rules) and canonical metrics.
The global economies of today will require Life Sciences companies to evolve their
current manufacturing business model, support systems, and existing organizational
practices simply to survive. The ability to share data and information in a totally
secure environment so decisions are completed more rapidly and reliably to save
time and money is crucial to success.
Pharmaceutical Processing
Advantage Business Media
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