Webinar series 24th march 2014 ams2750 e


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Heat Treatment standard AMS2750E.

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  • Given this information displayed on a furnace instrument with an Temperature reading of 289.2 – how confident are you that this is the actual temperature seen by the parts being processed?… well I suggest we need to ask some questions…
  • 1. What is the Thermocouple Type, Position within the furnace (is this detecting the right temperature) when was it last changed, what is the calibration accuracy? Are correction factors added?2. Do you have a proper connection to the instrument (correct lead-wire and connector type – limiting errors) What is the accuracy of the Cold junction compensation and instrument input accuracy – when was the instrument last calibrated and what was the accuracy recorded? Any offsets used within the instrument?3. Assuming the above is all ok, still need to know the whether the Conversion of mV to temperature scale is precise.
  • If we know this process is Nadcap accredited and follows the rules of AMS2750E – how confident are we now that the temperature is real? I would suggest we now have high confidence in this temperature reading. In my early days as a heat treaters this was brought home to me by an F1 Racing Team – the customer audited my process and questioned our confidence level of temperature measurement. We were currently working to the intent of BS2M54 (before my time with the AMS2750 specification). He was very rigorous in his auditing and it really did help my operation pick up its quality performance which led to a direct business improvement.It wasn’t a surprise to me that in later life this auditor became a nadcap auditor.
  • It is amazing the effect of poor data, generic researchindicated that between 10-25% of total company revenues can be taken up with dealing with bad data – that’s an incredible waste of money. If AMS2750E can help avoid this level of expense then there is a huge benefit for the business.Bad data = bad decisions – not many can argue with this statement
  • This is a typical definition for High quality data – yes, linked to Database records, typically used for CRM’s and similar products – however, we will use these common terms to discuss AMS2750E and Data quality.For a Heat Treat example:Complete – no gaps in process dataAccurate – true record of the temperature measuredAvailable – how to access both real-time & historical process dataTimely – full information when you need it e.g. do you know a TUS is passed or failed as soon as it ended potentially saving a time through a miss step of heating it back up for production when you need to potentially resurvey.
  • Lot’s of current news about Big Data – but does this apply to Heat Treat.Example of a quick big data story – my wife and I are finally catching up and watching the netflix US version of House of Cards. Apparently big data was used in order to give the series the best chance of success – Netflix dived into and mined the petabytes of information (1million GB) to give them information on the most popular series type – which was the Political Thrillers – the most popular director – and the most popular Actor – Kevin Spacey (he is also one of my favorite actors!).In Heat Treat we don’t have as much data – typically in the MB or GB’s and I would suggest we need to concentrate on Meaningful data.We should only collect and analyze relevant data – data that will ultimately be used to make decisions either by you or your customers or auditors (Process Charts etc.) Analysis can help us with process control and details such as Output % that can help lead to predictive analysis helping maintenance issues.We also need to make sure this data can be collected and presented in a format that is usable for action to be taken.
  • Data Accuracy is the first section to look at.This slide is a generic list of sections in the AMS2750E standard.Equipment class specifies the temperature uniformityThe quality and accuracy of Thermocouples is prescribed.I am more concerned with Instrument Calibration because this leads to a larger discussion.The instrument selection is governed by the accuracy required – in AMS2750E this is 0.2% in AMS2750D is was 0.1% at higher temperatures. This leads us to select a Precision Controller and Recorder. This level of instrument then opens up better characteristics of control:Better Noise rejection, Multiple PID sets, Overshoot inhibition, higher accuracy TUS instruments, drift control, better SAT & Recording results. Over the next few slides we will dive into some of this detail.
  • Simple chart specification for temperature uniformity.The better the class – the tighter the temperature uniformity. Simple!
  • Thermocouples are more accurate in certain ranges, this is why we would typically select:Type T for subzero treatmentsType J for low to mid temperature ovensType K, N for mid temperature furnaces (carburizing, neutral hardening)Type R, S for high temperature furnaces (vacuum furnaces etc.)By the way - the screen shows a Thermocouple App available both in PC format and on the Appstore.
  • Let’s look at noise, and more importantly noise rejection – with a 0.2% or better accuracy instrument then signal interference is minimized by circuit design and choice of terminal materials.This graph shows a comparison of actual results when testing different manufacturers products –the tight red band is the Eurotherm result, with competitor products illustrated by the variable green and blue signals.
  • Generally the 0.1 to 0.2% accurate instruments also come with advanced control strategies including multiple PID sets.This helps you accurately tune a furnace that has different personalities at different temperatures:Oven with a single burner for low temperatures and multiburner for high temperatures – the control characteristics will change with temperature.Vacuum furnace with low temperature convection heating compared to high temperature radiation heating will require different PID constants to give the most accurate performance.
  • One of the primary issues in running a TUS is minimizing any overshoot in the control sensor.A properly mapped furnace with multiple TUS sensors in the extremities of the workzone will magnify a 1degree overshoot in the control thermocouple by 5 or 10x across the TUS sensors - for certain furnace setups.Using overshoot inhibition features available on higher accuracy instruments (named cutback for Eurotherm controllers) helps with avoiding overshoot.This is the secret sauce in Eurotherm control and other instruments – when I first used Eurotherms as a customer (over 15 years ago) I benefitted from these features without even realizing what was helping me with my control accuracy.
  • Moving to the Field Instruments for a TUS – these instruments are held to a higher accuracy standard of 0.1% or better (Process Recorders are 0.2%).Some of these units now have a special CJC block build into the recorder to enable higher accuracy and provide what is termed as instant on capability.No more waiting for a recorder for 30 – 60 minutes to stabilize in ambient conditions to give you accurate results.
  • Calibration applies equally to Process Instrumentation and Field Instruments.In Process instruments, AMS specifies intervals between 1 month (Class1 Furnaces) to 6 months (Class5 and 6 furnaces)Apart from the theoretical calculations of drift we also put our devices through laboratory tests, cycling ambient conditions over a period of time to evaluate the drift characteristics.Ambient temperature cycling within 25degF can lead to drift results at 60-70% of theoretical levels – keeping a control cabinet at a constant temperature really helps with calibration results over time.
  • Another smart way to ensure the controller and recorder read the exact same temperature – helping SAT results – is to take advantage of digital retransmission available in the higher precision controllers. What you see on the controller is what you capture on the recorder – no slight deviations due to non-digital retransmission, separate thermocouples or scaling issues.
  • Now moving to the section on Complete data.The next few slides illustrate the issues with missing data. It really doesn’t matter how accurate your system is if you don’t have a complete record of your process – a blip in the network could cause a SCADA system to provide missing results.
  • We assume this might be the results – and some SCADA systems will back fill missing data with a straight line.
  • But what if the network blip also had an affect on the control system – shown here a dip in temperature – could create non-conforming parts.Even with increased inspection you might not find all the non-conforming parts and if these get out into service, they could fail prematurely and create issues with expensive product recalls.
  • Some ways to counteract this issue is to ensure you capture the information at source – have local memory and storage as well as redundant methods of archiving.
  • Now moving to the next section – Data Availability.Today there are more choices than ever to be able to display and view current process data at, or remote from the Process equipment.Controllers with better displays or Large screen HMI’s at the machine and for remote viewing, use of smartphones, tablets, or large screen TV’s covering multi processes.
  • Not only do you want to see the instant process information and comparing this against setpoints, but you also want to be able to see trends and history – this is commonly available in most SCADA and Process Recorder systems.
  • When performing TUS surveys it is important to be able to review numerical information as well as trends – this provides useful information when needing to diagnose issues with surveys.
  • Having multiple archiving strategies helps you never lose that critical process run. Storing the final information on a server (with data backup) ensure the data is available for review at any time in the future.
  • The final mini-section is looking at Timely Data.The ability to quickly access historical information easily is very important for the quality department and production/maintenance troubleshooting issues.Having a way to pull up Batch data quickly – available on higher end data historians – is one method to provide this quick access.
  • Excel has offered a quicker way to produce reports from data but requires manual input, manipulation of base data, is time consuming and the accuracy is dependent on the person creating the report.Using pre-canned reporting software can offer the quickest way to create AMS conforming reports without needing to manipulate or disturb the virgin data.
  • I hope this presentation has been able to detail how AMS2750E helps to create meaningful quality data.This data truly helps the heat treat operation allowing you to Sell moreSpend LessBuild better relationshipsAl through a consistent quality performance.
  • 3 new guides are nearly complete (just waiting review in the UK) that coverBeginners guide to Heat Treat control – maybe for a new sales engineer with no background in heat treat, and wants the basicsAnd 2 intermediate guides:Understanding CQI9 Version 3Understanding AMS2750E
  • A sneak preview of some of the information – in CQI9 ver3 – these are the areas as an instrument supplier we can help out. I will just quickly go through this list.
  • Webinar series 24th march 2014 ams2750 e

    1. 1. Webinar Series 24th March 2014 © Peter Sherwin | March | 2014 AMS2750E is not just a regulatory standard practical ways of using AMS2750E to benefit your Business Peter Sherwin Eurotherm Marketing & Business Development
    2. 2. Schneider Electric 1© Peter Sherwin | Eurotherm | 2014 Contents 1. Data Source 2. Data Quality & Type 3. AMS2750E & Data 4. Final Thoughts
    3. 3. Schneider Electric 2© Peter Sherwin | Eurotherm | 2014 1. Data Source
    4. 4. Schneider Electric 3© Peter Sherwin | Eurotherm | 2014 • Q. How hot is my furnace/oven? • A. 289.2 °F • Q. How Confident? (Scale 1-10, 10=certain) Data Source Temp °F
    5. 5. Schneider Electric 4© Peter Sherwin | Eurotherm | 2014 Data Source 1 2 3 Temp °F
    6. 6. Schneider Electric 5© Peter Sherwin | Eurotherm | 2014 • Q. How hot is my furnace/oven? • A. 289.2 °C • Q. Now how Confident? (Scale 1-10, 10=certain) Data Source Temp °F
    7. 7. Schneider Electric 6© Peter Sherwin | Eurotherm | 2014 • System failures, human errors and bad business processes can all lead to generating incorrect data. • This can cost an estimated 10-25% of total company revenues to rectify these mistakes (source: data warehousing) • Only thing worse than no data is bad data. • Bad data = Bad decisions. Data Statistics
    8. 8. Schneider Electric 7© Peter Sherwin | Eurotherm | 2014 2. Data Quality & Type
    9. 9. Schneider Electric 8© Peter Sherwin | Eurotherm | 2014 High-quality data is: • Complete: All relevant data —such as accounts, addresses and relationships for a given customer—is linked. • Accurate: Common data problems like misspellings, typos, and random abbreviations have been cleaned up. • Available: Required data is accessible on demand; users do not need to search manually for the information. • Timely: Up-to-date information is readily available to support decisions. Source: IBM http://www-01.ibm.com/software/data/quality/ Data Quality
    10. 10. Schneider Electric 9© Peter Sherwin | Eurotherm | 2014 Meaningful Data (versus Big Data?) What you do: • Only collect relevant data • Analysis (from simple counts/averages to predictions of future trends) • Presented in the right design for decision makers to understand. • Avoid data overload. To provide: • Help solve business problems • Optimize performance • Ability to provide Accurate Predictions Source: http://www.brightnorth.co.uk Meaningful Data
    11. 11. Schneider Electric 10© Peter Sherwin | Eurotherm | 2014 3. AMS2750E & Data • Accurate • Complete • Available • Timely
    12. 12. Schneider Electric 11© Peter Sherwin | Eurotherm | 2014 • Equipment Class • Thermocouples • Instrument Calibration • System Accuracy Test (SAT) • Temperature Uniformity Survey (TUS) Accuracy and AMS2750E
    13. 13. Schneider Electric 12© Peter Sherwin | Eurotherm | 2014 Accuracy (equipment class) Class Number Temperature Uniformity • Class 1 +/-5°F • Class 2 +/-10°F • Class 3 +/-15°F • Class 4 +/-20°F • Class 5 +/-25°F • Class 6 +/-50°F
    14. 14. Schneider Electric 13© Peter Sherwin | Eurotherm | 2014 Accuracy (thermocouples)
    15. 15. Schneider Electric 14© Peter Sherwin | Eurotherm | 2014 Accuracy (noise)
    16. 16. Schneider Electric 15© Peter Sherwin | Eurotherm | 2014 Accuracy (PID control)
    17. 17. Schneider Electric 16© Peter Sherwin | Eurotherm | 2014 Accuracy (overshoot)
    18. 18. Schneider Electric 17© Peter Sherwin | Eurotherm | 2014 Accuracy (TUS)
    19. 19. Schneider Electric 18© Peter Sherwin | Eurotherm | 2014 Accuracy (Drift)
    20. 20. Schneider Electric 19© Peter Sherwin | Eurotherm | 2014 Accuracy (SAT & Recording)
    21. 21. Schneider Electric 20© Peter Sherwin | Eurotherm | 2014 Complete (data)
    22. 22. Schneider Electric 21© Peter Sherwin | Eurotherm | 2014 Complete (data) Assumed Result
    23. 23. Schneider Electric 22© Peter Sherwin | Eurotherm | 2014 Complete (data)
    24. 24. Schneider Electric 23© Peter Sherwin | Eurotherm | 2014 Complete (data) • Multiple Archive strategies – Local Memory – Local Storage (e.g. USB) – Store & Forward – Remote Storage (e.g. FTP)
    25. 25. Schneider Electric 24© Peter Sherwin | Eurotherm | 2014 Available (Current view) • PID Controller • Paperless Recorder • HMI • Smartphone • Tablet • TV
    26. 26. Schneider Electric 25© Peter Sherwin | Eurotherm | 2014 Available (Process view) • Input accuracy • Secure Recording • Viewing Options • Analysis • Archiving
    27. 27. Schneider Electric 26© Peter Sherwin | Eurotherm | 2014 Available (TUS Recorder) • Portable • Input accuracy • Secure Recording • Viewing Options • Analysis • Archiving
    28. 28. Schneider Electric 27© Peter Sherwin | Eurotherm | 2014 Available (History view) • Archiving Options • Access to secure database • Search • Analysis • Output options
    29. 29. Schneider Electric 28© Peter Sherwin | Eurotherm | 2014 Timely (Data Records) • Multiple access to secure database • Historic search date/time
    30. 30. Schneider Electric 29© Peter Sherwin | Eurotherm | 2014 Timely (Auto Report) • Manual Report Excel • Auto Report Generator
    31. 31. Schneider Electric 30© Peter Sherwin | Eurotherm | 2014 4. Final Thoughts
    32. 32. Schneider Electric 31© Peter Sherwin | Eurotherm | 2014 Successful Business Optimization is grounded in understanding (through data and information analysis). Source: http://www.brightnorth.co.uk/ AMS2750E and other standards help us create meaningful quality data. This data ultimately allows us to: • Sell More • Spend Less • Build Better Relationships Data & Business Performance
    33. 33. 32 Make the most of your energy™ www.eurotherm.com Questions?
    34. 34. Schneider Electric 33© Peter Sherwin | Eurotherm | 2014 New Heat Treat Guides (overview)
    35. 35. Schneider Electric 34© Peter Sherwin | Eurotherm | 2014 New Heat Treat Guides (detail)