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Today’s Production Management Systems Enable Lean, Demand-Driven Supply Chains

Tue, 01/02/2007 - 11:48am
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.

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