2. Quality Management to Increase Yield and Profits Alex Chia Solution Sales Manager

3. Agenda ► Who is the customer? ► What did the client say they needed? ► What did we discover/conclude they needed? ► The solution ► Implementation sequence  Current status and future plans ► Results ► Keys to success

4. Who is the customer? ► Silicone release liners and specialty papers Extruded and silicone coated papers Medical, Hygiene, tape, specialty paper applications Largest supplier in the industry 1500 Employees worldwide 5 plants in US China, Finland, India, Netherlands and IK ► Industry leaders in innovation & technology State of the art production technology The right release liner product for “every need” = complicated product mix

5. Who is the customer? ► It is a relatively simple process…  Buy paper  Coat it – the key to their process  Slit it  Wrap it  Ship it ► Many examples of product “A” being made in one plant and shipped to another plant where it is further processed into product “B”

6. ► To “implement SPC”…is what they said…  As a first step, we proposed and completed a process assessment to: Document state of existing technology platforms. Determine what “implementing SPC” meant to them. Determine what problems they were trying to address by implementing SPC. Determine if “implementing SPC” would solve these problems. What did the customer want?

7. What did we discover? ► Growth via acquisition  Led to different systems at each plant to collect product and process data.  Systems were never designed to talk to one another.  Loparex wants a common platform to implement at existing plants and to roll out to future acquisitions.

8. What did we discover? ► Lack of standardization across US plants  Cannot make identical product at different plants.  Same product has different testing requirements at different plants.  Testing is performed using different equipment at different plants.  Same product has different specs at different plants.  CoA’s for the same product produced at different plants show different tests/specs/units of measure. ► Opportunity If an identical product could be made at different plants:  Improve capacity/utilization  Reduce order fulfillment time  Reduce shipping/freight costs

9. What did we discover? ► Decision making based on limited, old data  Very limited process data collection (paper only).  Resource-intensive access to quality metrics (product data). Written on paper – Filed in folder – Entered into Access/Excel – Entered into Metrics 1 Day 3-10 Days 30-60 Days30 Days ► Resource utilization  Dedicated headcount at each plant to provide quality metrics to plant management and to corporate management.  Engineers at each plant spend “several days” each month creating reports for customers.  Dedicated headcount at each plant to produce CoAs. ► Opportunity  Reduce overhead costs.  Provide real-time access to data and metrics.  Provide corporate headquarters with real-time visibility into plants.

10. What did we discover? ► Ineffective process improvement efforts  State of process control unknown due to lack of process data collection (and process monitoring via SPC).  Lack of confidence in SQC metrics due to unreliable product data.  Inability to correlate process settings to product characteristics.  “If the product test data is not reliable, how can we determine accurate process settings required to produce quality product?”  “How can we improve our performance today when we won’t see any data until next month?” ► Opportunity  Reduce customer complaints due to product variation.

11. What did we conclude? ► What did “Implementing SPC” mean?  A cosmetic definition is not critical. It is more important to first identify what problems the client hopes to solve with “SPC.” ► What problems were the client trying to address by “Implementing SPC?”  Inability to make product X the same way at any plant.  Poor capacity utilization across the company.  Excessive shipping/freight costs.  Long order fulfillment time.  Customer complaints due to variation in product.  Ineffective process & product improvement efforts.  Excessive headcount costs in the Quality department. ► Will an SPC system solve these problems?  No.

12. Solution Definition ► What are the macro-level root causes for the problems identified?  No process data collection system for the shop floor.  No process monitoring system for the shop floor.  No common product data collection system for the QC Lab.  No common system for testing and specifications management.  No real-time access process and product data. ► Will implementing systems to address these root causes enable the client to solve their problems?  Yes.

13. Solution Definition ► Accordingly, the solution requires:  An infrastructure for system connectivity  An open-architecture database for product data collection.  A QDMS to standardize all aspects of product testing including: Product Specifications management Product data collection (test results) Product dispositioning and certification  A HMI solution for process visualization.  An industrial database for high-speed product data collection  An on-line SPC system for: Efficient equipment set-up and start-up Process monitoring Process variation reduction  An off-line SQC system for: Capacity and Performance metric access & monitoring Product and process data analysis for continuous improvement purposes

14. Solution Definition

15. Where do we begin? ► Step #1: QDMS  The client decided that standardizing the specifications, testing, and certification process was most important.  Immediate benefits: Ensure that product X can be produced to the same standards in any plant with capacity. Eliminate the 1-2 month delay in acquiring data for analysis. Eliminate the headcount dedicated to producing CoAs.

16. What is QDMS? ► Quality Data Management System  Product data collection Common database to collect product test results from all plants.  Product specifications management Define product, operation, customer, and ship-to specific specifications.  Test plan management Define product, operation, customer, and ship-to specific test requirements.  Testing management Tracks the status of all samples taken for testing. Communicates with common lab equipment for automated data collection. Alerts if test results are out of specification. Manages the process of re-testing. Provides test result history for the lot being tested.  Product Dispositioning Auto disposition if all tests are within specification.  Product Certification Automated generation of product, customer and ship-to specific CoAs.

17. The Solution - QDMS

25. The Solution – SQC System ► Step #2: SQC System  Off-line access to the product test results (located in the QDMS database) was determined to be the most beneficial next step.  Benefits: Eliminate the 1-2 month delay in acquiring metrics. Eliminate headcount dedicated to gathering data/creating reports. Provide enterprise-wide visibility into product quality performance as a means to support and guide product improvement efforts.

26. The Solution – SQC System ► Step #2: SQC System  Why choose NWA Quality Analyst for SQC? Client had existing licenses. NWA Quality Analyst comes with the ability to query data stored in Wonderware InSQL. QDMS comes with a “QDMS SQC” module that integrates QDMS with NWA Quality Analyst. –Enables point and click access to desired data, anywhere across the enterprise. –Eliminates the need to maintain QA Run Files.

27. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

28. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

29. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

30. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

31. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

32. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

33. The Solution – SQC System ► QDMS SQC module integration with NWA Quality Analyst.

34. The Solution – Process Data Collection ► Step #3: Process Data Collection System  The system for collecting and storing process data was implemented next.  Benefits: Prepare for SPC implementation. Reduce manual data entry on the shop floor.

35. The Solution – Process Data Collection ► Step #3: Process Data Collection System  Why choose Wonderware Historian for collection of process data? Direct collect from PLC (no need for HMI if process visibility is not required) High speed collection capabilities Compatible with corporate SQC software (NWA Quality Analyst) Compatible with corporate SPC software (Wonderware QI Analyst) Historian

36. The Solution – Process Data Collection ► Step #4: Online SPC System  With process data being collected, the shop-floor SPC system can be put into place.  Benefits: More consistent product. Reduced scrap and rework. –Reduced response delay. –Time lapse: undesirable event to awareness –Enable predictive process control. –Pattern rules to take action before out of control –Eliminate overcontrol.

37. The Solution – Process Data Collection ► Step #4: Online SPC System  Why choose Wonderware QI Analyst for online SPC? Compatible with corporate process historian (Wonderware Historian) Compatible with SCADAlarm (future alarm notification system) Compatible with HMI (Wonderware InTouch) –Can be embedded Historian

38. Implementation Timeline ► 2008 (all plants)  QDMS – Product data collection / specs mgt. / test plan mgt.  SQC – Product quality metrics / quality improvement.  Historian – Process data collection. ► 2009 (all plants)  Wonderware Historian - Process data collection.  QI Analyst - On-line SPC. ► Future opportunities  Application Server.  Down time (in current planning discussions with client).  In Touch (deployment of QI Analyst will provide a platform for taking a critical look at replacing iFix with InTouch).  Web service interface to QDMS for suppliers to submit incoming raw material test results.

39. Current Results ► Total investment = ~$600K ► Headcount reduction (estimated hrs/week/plant)  CoA production 40hrs 6hrs  Data collection 65hrs 10hrs  Report generation 34hrs 3hrs ► Decision making based on reliable data  On the first day of SQC implementation, client discovered why one plant had excessive product returns vs. other plants for a high-volume product. ► Too early to determine effects on capacity utilization, shipping costs, etc.

40. Keys to Success ► Local Wonderware Distributor early in the sales process.  Experts in SPC, SQC, Six Sigma, and QC Laboratories.  Wonderware-centric solution for product testing/specs management/CoA production/SQC (competitors had no such solution to offer). ► Listened to their needs  Uncovered what was beneath the stated objective (implement SPC). Namely: test management, access to performance metrics, and process monitoring. ► Completed a Process Assessment to define specific requirements and to develop a corresponding solution implementation plan.  Coordinated effort between MAP, WW, and client personnel from multiple locations. ► Project sponsor understood that before the process could be improved, a common system to collect product and process data needed to be in place. ► Multi-facility enterprise deployment experience (MAP and WW). ► On-line project management and collaboration

41. Software Solutions for Real Time Success SM