1 MUST HAVE SHOULD HAVE COULD HAVE Module # 130b

2 maintaining your material delivery system (feed measurement & cut-off controller)  Objectives Understand the application, components and functions of a material delivery system Understand the importance of deploying a maintenance plan for a material delivery system Gain insight into the 3 categories of maintenance services required for GMP Know how Mettler Toledo offers and deploys these services

3 Application – material transfers (feeds) MMT PW D 1 2 M 3 B C A 1. application, components & functions

4 Ethernet TCP/IP Fieldbus 1 Batch Control Software PAM & CPM Services Measurement Devices - Scales & Flowmeters FBM integrated material delivery system components – batch, blending, formulation or filling 1. application, components & functions

5 functions for a material delivery system Must-have functions for all processes  Material transfer type (GIW, LIW, flowmeter)  Control target management (fixed bias)  Setpoint type (absolute, additive)  Dump to empty management (cut-off approach & setpoint)  Pre-feed condition checks (stable scale)  Post-feed check and report (for accurate & reliable data)  Drain time management  Instrument zero shift management  Interface driver for data between instrument and controller  Abnormal situation management 1. application, components & functions

6 Should-have functions for most processes  Adaptive spill-only (control target management)  Reasonable checks  Slow Step Timer  Command handler (status, error handling)  Material transfer handler (status, error handling, overflow)  Weigh/flow digital filtering  Built-in diagnostics for material transfer system  Manual/Operator control  Automatic/System control  Reset on instrument base and system base  Predictive abuse or potential failure alarms functions for a material delivery system 1. application, components & functions

7 Beneficial functions for many processes  Adaptive predictive control target management (instantly compensate for process changes)  Low flow alarm management  Instrument cross check  Estimated time to complete  Overlapping feed management  Data logging  Performance Monitoring Real time productivity reporting  Performance Evaluation via Data Analysis (Local or Remote) Real Time SPC reporting Predictive rule based alarming functions for a material delivery system 1. application, components & functions

8 achieve & sustain maximum production performance Maintenance goals… Maintain best possible quality Minimize reworks Maximize throughput Minimize system downtime 2. the importance of maintenance

9 good manufacturing practice (GMP) deploys 3 categories of services 1. Preventative services Maintain equipment in good physical working order 2. Performance services Maintain whole system within the designed operating specification 3. Predictive services Prevent potential identifiable problems from impacting budgeted production throughput, quality or running cost 3. catagories of services

10 Preventative  Measurement (per channel) – visual/physical inspection of… Load cells and flow meters Constraining tools Cables Junction Boxes External influences – physical binding, pipe work, new additions to tanks, vents, socks Environmental influences – moisture, corrosion, electrical noise, mechanical noise Provide management report on above  Control (per material path) – visual/physical inspection of… Repeatability check of FCE’s (Final Control Elements) for repeatable shut-off time Materials for reasonable granular consistency Material handling systems for reasonable operational speed and variability Routine replacement of any memory back up batteries Back up of all DMT files Provide management report on above 3. catagories of services

11 Performance  Measurement (per channel) – physical check and calibration of Zero Span Resolution Repeatability of measurement Scale Run up / Run Down Load Symmetry Provide management report on above  Controller (per material path) – inspection of logged data Review SPC results Check theoretical performance versus actual performance Check calculated efficiency against benchmarks and/or baseline Review configurations of (channels and material paths) Review change log Review use of correct algorithm based on feed type Tune material paths Provide management report on above 3. catagories of services

12 Predictive  Measurement (per channel) – analysis of abnormal conditions (Asset Management) Shock loading Over loading Zero drift Calibration drift Provide management report on above  Controller (per material path) – analysis of data (Collaborative Production Management) Identify a list of problematic material paths based on most efficient to least efficient material path Review process parameters Analyze data for abnormalities/changes(+-50 variables per material path/feed) e.g. feed times spill values constants error messages etc..etc. Set rules based on any abnormalities Monitor alarms Collaborate to investigate upsets and causes of upsets Provide management report on above 3. catagories of services

13  The Problem Overlapping feeds of a small Pre-weigh system with a Gain-In-Weight feed into the making system (crutcher) was seeing periods of failure and then normal operation. This inconsistency caused significant upsets which required operator intervention to help recover when the system was failing.  Service Tools Used Q.i365 acquired process information over time.  Services – Data Analysis (Performance & Predictive) The data was exported to an evaluation team for detailed analyses. Material movement information such as amount of material moved and the time it took to move it for all systems involved.  Discovery & Conclusions - root cause The data indicated a variation in the performance of the dumping of a single Preweigh. Though slight this variation caused the overlap to periodically fail. Originally blame was place on the control system but field measurements verified the variations. Upon farther analyses it was discovered a chemical phase shift was occurring causing the material to react differently.  Time of Impact on Manufacturing prior to discovery & Corrective Action taken On and off for over 6 months. This phase shift was random and is still being analyzed. The material causing it is being moved to another delivery system to correct the issue.  Value to production, operations and quality Operators are free to focus on other process issues. Production was improved and variations reduced. benefits of performance & predictive analysis….case study #1 Procter & Gamble

14 benefits of performance & predictive analysis….case study #2  The Problem As a significant data set was collected and analyzed it was noticed that the material feed errors varied, but curiously the feed errors were at two distinct levels i.e. for many feeds the error would be x and then it would jump to y and stay at this level and then return to x.  Service Tools Used Q.i365 acquired process information over time. This allowed the viewing of various parameters such as: Final Spill, Feed Error, Start Weight, End Weight, Feed Time, to name a few.  Discovery & Conclusions Reviewing the data, a pattern emerged. The Final Spill changed in sympathy with the larger feed errors. It was then noticed that this increased error only occurred when the material was added when the start weight was greater than x. This led to the discovery that the material feed pipe extended deep into the vessel, as a result, once the exit was covered by the material, the pipe did not drain when the feed was stopped.  Impact on Manufacturing prior to discovery & Corrective Action taken Over 5 materials fed into a common manifold which was not draining once its outlet was below the surface of the material. This resulted in an overfeed of 70 lbs of material (average of 5% of target). In addition this extra material was never recorded. By venting the manifold proper drainage of the materials was achieved.  Comments This error and loss of material had existed for sometime. The value of this lost material was calculated to be in excess of $ per annum.  Payback period Less than 1 month!

15 Deployment of Services  Measurement services are typically deployed at the local level via a the local MT office OR MT Distributor  Control services are typically supplied from a remote location either by the Q.i team or a locally trained MT Systems Group using one of the following methods usually dictated by the manufacturing sites preference. Each method has its pro’s and con’s in regards to security and depth of support a permanent internet link with VPN security to the manufacturing site a temporary internet link with VPN security, connectivity controlled and monitored at the manufacturing site or by receipt of data files sent by or on CD from the manufacturing site 4. Deployment of services