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  GUIDE CONCEPT   This guide introduces connecting an Allen-Bradley PLC to ThingWorx Kepware Server.   YOU'LL LEARN HOW TO   Create and run a simple ladder logic application on an Allen-Bradley PLC Connect the PLC to ThingWorx Kepware Server   NOTE: The estimated time to complete this guide is 30 minutes.      Step 1: Learning Path Overview   Assuming you are using this guide as part of the   Rockwell Automation Learning Path, then you have now completed each of the following installations:        1. Connected Components Workbench       2. ThingWorx Kepware Server       3. ThingWorx Foundation (for Windows)   In this continued step, you'll now connect an   Allen-Bradley PLC   to   Connected Components Workbench   and then to   ThingWorx Kepware Server.   In a later guide, we'll propogate that information further from ThingWorx Kepware Server into ThingWorx Foundation.   NOTE: Both Rockwell Automation's Connected Components Workbench and ThingWorx Kepware Server are time-limited trials. If significant time has passed while persuing this Learning Path, you may need to reinitialize them. Consult the Troubleshooting step of this guide for more information.       Step 2: Setup PLC   This guide uses an inexpensive Allen-Bradley Micro820 PLC as a demonstration.   ThingWorx Kepware Server offers drivers for hundreds of devices, making this step the only one that contains device-specific instructions.   Read and understand installation instructions before making any electrical connections to the PLC.   1. Connect the postive lead of a 24V power supply along with a 6" test lead to Terminal 1 of the output terminal block.   2. Connect the negative lead of the power supply to Terminal 2.     3. Confirm the test lead is secure from making contact with anything conductive; it will be  connected to +24V. Power on the supply and confirm the LEDs briefly light.       4. Carefully touch the test lead to the Input 1 terminal and confirm the indicator LED for Input 1 turns on.     5. Power off the supply before continuing to the next step.       Step 3: Create PLC Project   In this step, you will create a simple PLC application. This application will connect to a ThingWorx Mashup in subsequent guides in the Learning Path.    1. After opening Connected Components Workbench, click New... in the Project section.   2. Enter ThingWorxGuide in the Name field and click Create.   3. Browse to the PLC model you are using and click Select, then Add to Project.     4. Right-click Program, then left-click Add > New LD: Ladder Diagram     5. Double-click Prog1 to open the ladder window.     Ladder Logic   You will create a simple application that will turn on output 2 when there is a signal on input 2.    1.. Right-click in the box to the left of the rung, hover over Insert Ladder Elements, then click on Direct Coil   .     2.  Click the  I/O - Micro820 tab  towards the right and select an  output coil  - this guide uses  _IO_EM_DO_02 . Then click  OK                  3. Add an input contact by right-clicking in the   box to the left of the rung, hover over   Insert Ladder Elements, then click on   Direct Contact.   4.  Click the  I/O - Micro820 tab  and scroll down to select an  input  - this guide uses  _IO_EM_DI_02 . Then click  OK .        5. The program window should now look like this:     Upload   Next, you will propagate the program to the PLC.   1. Secure the test lead then apply power to the PLC.   2. Connect an ethernet cable directly between the PLC and your Windows computer.   3. Click Device > Connect to connect to the PLC; a pop-up will appear saying the project does not match the program in the controller.     NOTE: When either your PLC or computer are restarted, they may be assigned a new IP address, requiring you to reconfigure the connection. Click the tab labled with your PLC, then click the pencil icon next to connection path, click Browse, expand the Ethernet driver, highlight the active controller, and click OK. Click Close and then Connect.       4. Click Download current project to the controller   5. Confirm overwriting any program in the controller by clicking Download.   6. After your project is downloaded, run it on the controller by clicking Yes.     7. Touch the test lead to the I-02 terminal, and your program will turn on the #2 output. You can confirm your project is working by both hearing the soft click from the PLC and seeing the output indicator turn on.       Step 4: Configure ThingWorx Kepware Server   Now that you have a simple project running on the PLC, you need to configure ThingWorx Kepware Server to monitor it.   1. Open   ThingWorx Kepware Server, right-click on   Connectivity, and click   New Channel.   2. Select   Allen-Bradley Micro800 Ethernet   from the drop-down, then click   Next.       3. Click Next to accept the defaults, and click Finish to create Channel2.   4. Click Click to add a device below Channel2, enter myPLC in the name field, and click Next.   5. Enter the IP address of your PLC, then click Next. The IP address of your PLC is shown in Connected Components Workbench in Device > Configure.       NOTE: The IP address of the PLC may change when it is power cycled and must be updated in ThingWorx Kepware Server to match   6. Click Next to accept default values for each pop-up, and click Finish to create the myPLC device.       7. Click the Click to add a static tag message.   8. Enter Coil2 in the Name field, _IO_EM_DO_02 in the Address field, change the Data Type drop-down to Boolean, and click OK.  The address must exactly match a variable name in the PLC.       9. Create a second tag by right-clicking on myPLC again and clicking New Tag.   10. Enter Coil3 in the Name field, _IO_EM_DO_03 in the Address field, select Boolean from the Data Type drop-down, and click OK.         Step 5: Troubleshooting   1. If the connection to the PLC stops working and there is a   Thumbs Down   icon next to your Properties, the   ThingWorx Kepware Server   trial edition drivers are not connected to your PLC. The trial edition stops running after 2 hours and must be stopped and restarted. Right-click on ThingWorx icon in system tray.     Click Stop Runtime service. Wait a minute for the process to stop, then click Start Runtime service.   2.  If Connected Components Workbench does not connect to PLC, check the IP address of the PLC using RS Linx Classic software that was installed as part of Connected Components  Workbench. RS Linx Classic is located Start > All Programs > Rockwell Software > RSLinx > RSLinx Classic Click AB_ETHIP-1, Ethernet and IP addresses of connected PLCs will be discovered   NOTE: A changed PLC IP Address (typically seen through Connected Components Workbench) will require an IP Address change in ThingWorx Kepware Server settings.       Step 6: Next Steps   Congratulations! You've successfully completed the   Connect to an Allen-Bradley PLC   tutorial. You've learned how to:   Create and upload a simple ladder logic application to a PLC Connect a PLC to ThingWorx Kepware Server   The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Create an Application Key.   Learn More   Capability Resource Analyze Monitor an SMT Assembly Line     Additional Resources   For additional information on ThingWorx Kepware Server:   Resource Link Website Connecting & Managing Industrial Assets Documentation Kepware documentation Support Kepware Support site
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Pre-built apps for manufacturing operations that rapidly deliver value.   Overview   Think Big, Start Small, Scale Fast   Getting started on an industrial IoT project can be daunting, especially deciding where and how to begin. After collecting the experiences gained by working with over 1500 companies on IIoT applications, PTC has made the process to get up and running easier. By grouping IIoT capabilities together in functionally oriented programs, PTC built out-of-the-box applications that rapidly deploy and scale across new or existing system infrastructure. Instead of starting from scratch, you can use ThingWorx ready-to-configure apps to quickly lay the foundation for industrial transformation and implement IIoT solutions in as little as 90 days. ThingWorx Apps offer a comprehensive, basic IIoT scheme to connect to your equipment, collect real-time data, create notification work flows, deliver role based dashboards, and more. Need something more tailored to your operation? No problem. You can iteratively extend and customize ThingWorx Apps into additional use cases for continuous innovation.     Manufacturing Apps   Manufacturers are under constant pressure to minimize downtime, improve quality, and respond faster to individual customer requirements, all while lowering costs. The ThingWorx Manufacturing Apps are pre-built solutions that can be tried in less than 60 minutes without disrupting production. These apps provide manufacturers with real-time visibility into factory floor operations, from individual PLCs to assets to plants to enterprise-wide operations.   ThingWorx Connected Work Cell   Connected Work Cell streamlines how information is delivered to frontline workers by aggregating critical data from multiple data siloes into a simplified visual application. It presents step-by-step work instructions with accurate, up-to-date information to drive efficiency, links instructions to work orders, assigns resources, and validates proper execution to ensure quality. Capabilities Lite work instruction authoring with multiple step types and versioning Workpiece routes editor and work order scheduling Step-by-Step tracking of operator execution  Smart tool configuration Work station dashboard display File storage and document management Benefits Present accurate, up-to-date work instructions using 3D models Aggregate work requirements from multiple sources into one simplified display at the work station Increase workforce flexibility by reducing upfront training before being assigned to a new work cell Improve quality by collecting actual tool use data Rapid implementation and fast time to value   ThingWorx Real-Time Production and Performance Monitoring   Real-Time Production and Performance Monitoring provides manufacturing executives and plant managers with top-down, real-time visibility into consistent KPIs such as overall equipment effectiveness, mean time between failure, and mean time to repair.   Capabilities Connect existing assets and gather real-time data View overall equipment effectiveness (OEE), mean time between failure (MTBF), and mean time to repair (MTTR) in real-time  Compare geographically separated assets, lines, or products based on date, time, shift or crew Benefits Improve operational performance of existing assets by increasing throughput and decreasing waste Balance labor vs. capital expenditures to meet production needs Determine true overall equipment effectiveness for multiple facilities   ThingWorx Asset Monitoring and Utilization   Asset Monitoring and Utilization helps manufacturers connect to existing assets, remotely monitor them in real-time, generate alerts based on abnormal conditions, and deliver critical insights with data trending and analysis tools.   Capabilities Performance Dashboards with real-time access to open alarms Email and SMS distribution rules for messaging and alarm acknowledgment Integration to maintenance systems Detailed screens showing asset health, configuration parameters, and sensor trends  Benefits Quickly identify anomalous data trends and perform Root Cause Analysis Maximize asset uptime and availability with alerts on critical issues before they impact performance Rapidly connect to and catalog existing assets Quickly Identify Anomalous Data Trends and perform Root Cause Analysis  
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Build an Equipment Dashboard Guide Part 1   Overview   This project will introduce you to the principles of ThingWorx Foundation by creating an eqipment dashboard. Following the steps in this guide, you will create the building blocks of your first IoT application, including Things and Streams. We introduce the basics for creating an IoT application. NOTE: This guide's content aligns with ThingWorx 9.3 .  The estimated time to complete ALL 2 parts of this guide is 30 minutes.    Step 1: Learning Path Overview   This guide explains the steps to create an Industrial Eqipment Dashboard, and is part of the Connect and Monitor Industrial Plant Equipment Learning Path. You can use this guide independently from the full Learning Path. If you want to learn the basics of creating an eqipment dashboard with ThingWorx, this guide will be useful to you.When used as part of the Industrial Plant Learning Path, you should already have ThingWorx Kepware Server installed, and it should be sending data to ThingWorx Foundation. You also need to have previously created the Thing Shape and Thing Template used for this dashboard. We hope you enjoy this Learning Path.   Step 2: Create Thing   A Thing is used to digitally represent a specific component of your application in ThingWorx. In Java programming terms, a Thing is similar to an instance of a class. In this step, you will create a Thing that represents an individual Pump using the Thing Template we created in the previous guide. Using a Thing Template allows you to increase development velocity by creating multiple Things without re-entering the same information each time. In ThingWorx Foundation, navigate to Browse > Modeling > Things. Click + New. In the Name field, type MyPump. NOTE: This name, with matching capitalization, is required for the data display created in a later step.       4. If Project is not already set, click the + in the Project text box and select the PTCDefaultProject.       5. In the Base Thing Template field, search for and select the previously-created PumpTemplate.       6. At the top, click Save.          Manage Property Bindings At the top, click Properties and Alerts. At the top, click Manage Bindings. In the top-left Local > Search Things field, search for and select IndConn_Tag1. Drag-and-drop Simulation_Examples_Functions_Random3's + symbol onto the watts Property on the right. At the bottom-right of the pop-up, click Done. Note how the Tag from ThingWorx Kepware Server is now bound to the the watts Property. Click Save. Click Refresh repeatedly to confirm the watts Property value is changing.     Step 3: Store Data in Value Stream   Now that you have created the MyPump Thing to model your application in ThingWorx, you need a storage Entity to record changing Property values. This step shows how to save time-series data in a Value Stream already created in a previous guide. To learn more, refer to the Methods for Data Storage guide. Navigate to Browse > Modeling > Thing Templates. Click the previously-created PumpTemplate Thing Template to open it. Confirm you are on the General Information tab. If necessary, click Edit to allow changes. In the Value Stream field, search for and select IndConn_ValueStream. Click Save.   Step 4: Create Application UI   ThingWorx Foundation is used to create customized web applications that can display and interact with data from multiple sources. These web applications are called Mashups and are created using the Mashup Builder. The Mashup Builder is where you create your web application by dragging and dropping Widgets such as Grids, Charts, Maps, and Buttons onto a Canvas. All of the user interface elements in your application are Widgets. We will build a web application with three Widgets: Image showing a picture of the pump Value Display showing the pump serial number Line Chart showing the value of watts Property trend over time.   Create New Mashup   Navigate to Browse > Visualization > Mashups.   Click + New.   Keep the defaults and click OK.   In the Name field, type pump-dashboard. If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. Click Save.   At the top, click Design.   Define Mashup Areas   At the top-left, ensure the Layout tab is selected. Click Add Bottom to split your UI into two halves.   Click the newly-created bottom-half to select it. Click Add Left.   Click the bottom-left container to select it. In the top-left Layout section, scroll down and select Fixed Size.   Type 200 in the Width text box that appeared, then press your keyboard’s Tab key to record your entry.   Add Widgets   In the top-left, click the Widgets tab.   In the Filter field, type image.   Drag-and-drop an Image Widget onto the lower-left area of the central Canvas. This Widget will show an image of the pump in use. 4. In a similar manner to what was just done with the Image Widget, drag-and-drop a Value Display Widget onto the top area. 5. Likewise, drag-and-drop a Line Chart Widget onto the lower-right area.   6. Click Save.          Click here to view Part 2 of this guide. 
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Learning Paths combine guides into one experience to teach related skills efficiently from start to finish. Begin your learning journey to reduce time to proficiency to get up and running with ThingWorx quickly.   Featured Learning   Utilizing ThingWorx to Secure Your Aerospace and Defense Systems Connect and Monitor Industrial Plant Equipment Vehicle Predictive Pre-Failure Detection with ThingWorx Platform   Industry Solutions   Complex and Automatic Food and Beverage Systems Connect and Configure Industrial Devices and Systems Medical Device Service Monitor Factory Supplies and Consumables Using an Allen-Bradley PLC with ThingWorx   Learn ThingWorx   Getting Started on the ThingWorx Platform Design and Implement Data Models to Enable Predictive Analytics Customize UI and Display Options to Deploy Applications Azure MXChip Development Kit    
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Use the Edge MicroServer (EMS), Foundation, and Analytics to engineer a Smart, Connected Products play for the Automotive segment.   NOTE: Complete the following guides in sequential order. The estimated time to complete this learning path is 240 minutes.   1. Use the Edge MicroServer (EMS) to Connect to ThingWorx  Part 1 Part 2 Part 3 2. Use the EMS to Create an Engine Simulator  Part 1 Part 2 Part 3 Part 4 3. Engine Simulator Data Storage  Part 1 Part 2 4. Build an Engine Analytical Model  Part 1 Part 2 Part 3 5. Manage an Engine Analytical Model  Part 1 Part 2 6. Engine Failure-Prediction GUI 7. Enhanced Engine Failure Visualization  Part 1 Part 2 Part 3
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Challenges Manufacturers of factory equipment often rely on manual processes to maintain adequate supply levels of consumables in equipment at customer sites. But a clipboard-and-pen process for ordering supplies are error prone, and can quickly grow wrought with problems that often go unreported until they affect assembly line production, resulting in unexpected costs—such as overnight shipping charges—and risking downtime, which ultimately leads to customer dissatisfaction.   Solution One such manufacturer implemented ThingWorx to connect to equipment installed at customer sites, and created a custom web application using ThingWorx Foundation to remotely monitor supply levels. ThingWorx Industrial Connectivity provides the bi-directional connection to send data that is displayed in graphs on the web application created using ThingWorx Mashup Builder. Features of ThingWorx Analytics were used to generate alerts before maintenance problems affected production.   Outcomes The manufacturer is able to monitor supply levels to more effectively anticipate when consumables will need to be replenished. Supplies are now consistently ground shipped on time to meet assembly line demand, reducing interruptions to operations and allowing expansion to multiple plants with improved service level.   NOTE: Complete the following guides in sequential order. The estimated time to complete this learning path is 120 minutes.   1. Implement Services, Events, and Subscriptions  Part 1 Part 2 2. Build a Predictive Analytics Model  Part 1 Part 2
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Build a Predictive Analytics Model Guide Part 2   Step 5: Profiles   The Profiles section of ThingWorx Analytics looks for combinations of data which are highly correlated with your desired goal. On the left, click ANALYTICS BUILDER > Profiles. Click New....The New Profile pop-up will open. NOTE: Notice the Text Data Only section which is new in ThingWorx 9.3.         3. In the Profile Name field, enter vibration_profile. 4. In the Dataset field, select vibration_dataset. 5. Leave the Goal field set to the default of low_grease. 6. Leave the Filter field set to the default of all_data. 7. Leave the Excluded Fields from Profile field set to the default of empty. 8. Click Submit. 9. After ~30 seconds, the Signal State will change to COMPLETED. The results will be displayed at the bottom.                 The results show several Profiles (combinations of data) that appear to be statistically significant. Only the first few Profiles, however, have a significant percentage of the total number of records. The later Profiles can largely be ignored. Of those first Profiles, both Frequency Bands from Sensor 1 and Sensor 2 appear. But in combination with the result from Signals (where Sensor 1 was always more important), this could possibly indicate that Sensor 1 is still the most important overall. In other words, since Sensor 1 is statistically significant both by itself and in combination (but Sensor 2 is only significant in combation with Sensor 1), then Sensor 2 may not be necessary.     Step 6: Create Model   Models are primarily used by Analytics Manager (which is beyond the scope of this guide), but they can still be used to measure the accuracy of predictions. When Models are calculated, they inherently withhold a certain amount of data. The prediction model is then run against the withheld data. This provides a form of "accuracy measure", which we'll use to determine whether Sensor 2 is necessary to the detection of a low grease condition by creating two different Models. The first Model (which you will create below) will contain all the data, while the second Model (in the next step) will exclude Sensor 2. On the left, click ANALYTICS BUILDER > Models.   Click  New… . The New Predictive Model pop-up will open.   3. In the Model Name field, enter vibration_model. 4. In the Dataset field, select vibration_dataset. 5. Leave the Goal field set to the default of low_grease. 6. Leave the Filter field set to the default of all_data.         7. Leave the Excluded Fields from Model section at its default of empty.       8. Click Submit. 9. After ~60 seconds, the Model Status will change to COMPLETED.   View Model   Now that the prediction model is COMPLETED, you can view the results. Select the model that was created in the previous step, i.e. vibration_model. Click View… to open the Model Information page.   Review the visualization of the validation results. Note that your results may differ slightly from the picture, as the automatically-withheld "test" portion of the dataset is randomly chosen. Click on the ? icon to the right of the chart for details on the information displayed.   The desired outcome is for the model to have a relatively high level of accuracy. The True Positive Rate shown on the Receiver Operating Characteristic (ROC) chart are much higher than the False Positives. The curve is relatively high and to the left, which indicates a high accuracy level. You may also click on the Confusion Matrix tab in the top-left, which will show you the number of True Positive and True Negatives in comparison to False Positives and False Negatives.     Note that the number of correct predictions is much higher than the number of incorrect predictions.     As such, we now know that our Sensors have a relatively good chance at predicting an impending failure by detecting low grease conditions before they cause catastrophic engine failure.     Step 7: Refine Model   We will now try comparing this first Model that includes both Sensors to a simpler Model using only Sensor 1. We do this because we suspect that Sensor 2 may not be necessary to achieve our goal. On the left, click ANALYTICS BUILDER > Models.   Click New…. In the Model Name field, enter vibration_model_s1_only. In the Dataset field, select vibration_dataset. Leave the Goal field set to the default of low_grease. Leave the Filter field set to the default of all_data.   On the right beside Excluded Fields from Model, click the Excluded Fields button. The Fields To Be Excluded From Job pop-up will open. 8. Click s2_fb1 to select the first Sensor 2 Frequency Band. 9. Select the rest of the Frequency Bands through s2_fb5 to choose all of the Sensor 2 frequencies. 10. While all the s2 values are selected, click the green "right arrow", i.e. the > button in the middle. 11. At the bottom-left, click Save. The Fields To Be Excluded From Job pop-up will close.           12. Click Submit. 13. After ~60 seconds, the Model State will change to COMPLETED. 14. With vibration_model_s1_only selected, click View....   The ROC chart is comparable to the original model (including Sensor 2). Likewise, the Confusion Matrix (on the other tab) indicates a good ratio of correct predictions versus incorrect predictions.     NOTE: These Models may vary slightly from your own final scores, as what data is used for the prediction versus for evaluation is random. ThingWorx Analytics's Models have indicated that you are likely to receive roughly the same accuracy of predicting a low-grease condition whether you use one sensor or two! If we can get an accurate early-warning of the low grease condition with just one sensor, it then becomes a business decision as to whether the extra cost of Sensor 2 is necessary.   Step 8: Next Steps   Congratulations! You've successfully completed the Build a Predictive Analytics Model guide, and learned how to:   Load an IoT dataset Generate machine learning predictions Evaluate the analytics output to gain insight    This is the last guide in the Getting Started on the ThingWorx Platform learning path.   This is the last guide in the Monitor Factory Supplies and Consumables learning path.   The next guide in the Design and Implement Data Models to Enable Predictive Analytics learning path is Operationalize an Analytics Model.     Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Support Analytics Builder Help Center    
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  Step 5: Create Services   Below shows how we can create the GetCustomerPackages Service for the PTCDeliversBusinessLogic Thing.   Create Service Definition   On the home page, filter and select the PTCDeliversBusinessLogic Thing. Switch to the Services tab. Click + Add.   Enter the name of the Service, GetCustomerPackages. Switch to the Output tab of the Service. Select InfoTable from the list as the Base Type. When prompted for the DataShape, select CustomerDataShape. Switch to the Inputs tab of the Service. Click the + Add button.   Enter the name CustomerId. Check the Required checkbox. Click Done.   Add Service Functionality   Switch to the Me/Entities tab. Switch the radio option to Other Entity. Filter and select PackageDataTable as the Entity. A list of all accessible Services for the PackageDataTable will appear. In the search bar for Services, enter QueryDataTableEntries in the Services section and click the arrow next to it. Update the inserted code to use the input parameter, CustomerId, in the query. An example is below and more information can be found on queries on our Query Help Page. Click Done and save your work.           / Provide your filter using the format as described in the help topic "Query Parameter for Query Services" var query = { "filters": { "type": "EQ", "fieldName": "CustomerId", "value": CustomerId } }; // result: INFOTABLE dataShape: "" var result = Things["PackageDataTable"].QueryDataTableEntries({ maxItems: undefined /* NUMBER */, values: undefined /* INFOTAB           After saving changes and closing the Service edit view, you can test the method by selecting the Execute play button.   The Service we created will query PackageDataTable for any packages with the CustomerId you entered. If no data has been added to the DataTable as yet, open PackageDataTable's Services tab and execute the AddDataTableEntries Service with test data.       Step 6: Create Subscriptions   Subscriptions are based on tracking the firing of an Event. When the Event is triggered or fired, all entities with a Subscription to the Event will perform the script as defined. The JavaScript interface and script tabs are the same as those utilized for the Services interface.   Subscriptions are a great resource for making updates in other Entities, Databases, or even just logging this information to your liking. On the home page, filter and select the PTCDeliversBusinessLogic Thing. Switch to the Subscriptions tab. Click + Add.   For Source, select *Other Entity. Filter and select PackageStream. Check the Enabled checkbox. Using a Stream to track events in the application allows for one source to watch for activity. The source for a Subscription can be other Entities if a single Entity is wanted. In order to capture all source data from the PackageStream, you will need to set it as the Stream for the Entity you would like to track. Switch to the Inputs tab. Select the Event drop-down and pick the PackageDelivered Event. This PackageDelivered Event only exists in the completed download. If you are not using that download, create your own Event based on the PackageDataShape. Update the script area of the Subscription using the below code. This JavaScript code will take the information from the triggered Event and add it to the DeliveryDataTable.         / tags:TAGS var tags = new Array(); // values:INFOTABLE(Datashape: PackageDataShape) var values = Things["DeliveryDataTable"].CreateValues(); values.Customer = eventData.Customer; // THINGNAME values.Content = eventData.Content; // STRING values.ID = eventData.ID; // INTEGER [Primary Key] values.Weight = eventData.Weight; // NUMBER // location:LOCATION var location = new Object(); location.latitude = 0; location.longitude = 0; location.elevation = 0; location.units ="WGS84"; var params = { tags : tags, source : me.name, values : values, location : location }; // AddOrUpdateDataTableEntry(tags:TAGS, source:STRING("me.name"), values:INFOTABLE(DeliveryDataTable), location:LOCATION):STRING var id = Things["DeliveryDataTable"].AddOrUpdateDataTableEntry(params);               Step 7: Next Steps   Congratulations! You've successfully completed the Implement Services, Events and Subscriptions guide.   In this guide you learned how to to create Events, Services and Subscriptions you can utilize to monitor and optimize your IoT applications.   The next guide in the Design and Implement Data Models to Enable Predictive Analytics learning path is Build a Predictive Analytics Model.    The next guide in the Monitor Factory Supplies and Consumables learning path is Build a Predictive Analytics Model.   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Build Create Custom Business Logic Guide Secure Configure Permissions Connect SDK Reference   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Help Center  
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    Step 7: Add Grid   It might also be helpful to display the data you've used to build the ThingWorx Analytics model.   In the future, this might be split out into an entirely separate page/Mashup that is exclusively devoted to backend model creation, but that would be beyond the scope of this guide.   For now, we'll simply display that collected data via the Grid Widget      1. On the EEFV_Mashup, drag-and-drop a Grid Advanced Widget onto the bottom-left Canvas section..     2. On the top-right Data tab, click the green </> button beside Things_EdgeThing. Note that this will open the Add Data pop-up, but with EdgeThing pre-selected.   3. In the Services Filter field, type getproperties.   4. Click the right-arrow beside GetProperties to add it to Selected Services on the right.   5. Check Execute on Load.     6. Click Done.   7. Under the Data tab, expand GetProperties to reveal the options.     8. Drag-and-drop Things_EdgeThing > GetProperties > infoTableProperty onto the Grid Advanced Widget.     9. On the Select Binding Target pop-up, click Data.     10. Click Save.   11. Click View Mashup.         Step 8: Add Controls   Throughout this Learning Path, it has been recommended that you stop Analysis Events when not actively using their functionality.   However, this requires going into the backend of ThingWorx Analytics to disable the event, which is not ideal.   Instead, let's enable or disable the Analysis Event from inside the Mashup by adding some Button Widgets to directly interface the Analytics backend for us.       1. Click the bottom-right Canvas section to select it.         2. In Mashup Builder top-left, click the Layout tab.         3. Under Positioning, click the Static radio-button.         4. Click the Widgets tab.       5. Drag-and-drop a Button Widget onto the bottom-right section.         6. Drag-and-drop another Button Widget onto the bottom-right section.       7. Drag-and-drop a Text Field Widget onto the bottom-right section.       8. Click Save.       Bring in More Data   Now that we have Buttons to trigger enable/disable, as well as a Text Field to display information, we now need to bring in some additional Mashup Data Services to interact with the ThingWorx Analytics backend.       1. Click the green + button at the top of the Data tab.       2. In the Entity Filter field, search for and  select TW.AnalysisServices.EventManagementServicesAPI.       3. In the Services Filter field, search for and add QueryAnalysisEvents by clicking the right arrow.       4. Check Execute on Load.         5. In Services Filter, search for and select EnableAnalysisEvent by clicking the right arrow. Note that you should NOT check "Execute on Load", as we'll trigger this Service only when the Button is clicked.     6. In Services Filter, search for and select DisableAnalysisEvent by clicking the right arrow. Likewise, do NOT check "Execute on Load" here either.       7. Click Done.         8. Click Save.     Display Event Key   To enable or disable Analytics Events, we need to know the eventId, which is returned by QueryAnalysisEvent Service as the parameter labeled key.   We'll bind that to the Text Field Widget for later usage in enabling/disabling.        1. Change the top-button's Label Property to Enable Analytics Event.       2. Change the bottom-button's Label Property to Disable Analytics Event.         3. Under the Data tab, expand QueryAnalysisEvents > Returned Data > All Data to reveal the options. .       4. Drag-and-drop QueryAnalysisEvents > Returned Data > All Data > key to the TextField Widget.         5. On the Select Binding Target pop-up, click Text.         6. Click Save.     Enable/Disable Analytics Events   Now that we know the key/eventId, we can call the EnableAnalysisEvent and DisableAnalysisEvent services.       1. Under the Data tab, expand EnableAnalysisEvent > Parameters to reveal eventId.       2. Click the Text Field Widget to select it, and then click the top-left drop down to reveal the options.         3. Drag-and-drop the Text Field's Text Property onto EnableAnalysisEvent > Parameters > eventId.         4. Repeat steps 1-3 for DisableAnalysisEvent.         5. Click the Enable Analytics Event Button Widget to select it, then click the top-left to reveal the drop down option .       6. Drag-and-drop the Clicked Event onto the EnableAnalysisEvent Service under the Data tab.         7. Repeat steps 5-6 for DisableAnalysisEvent, using the other Button Widget.         8. Click Save     Step 9: View Mashup   Throughout this guide, we've added various additional functionality to our MVP Mashup. At this point, you could continue to update the Mashup as you see fit.   For instance, you could change the background color of the top-left section to better match the header. Or you could further modify the original Mashup shown in the Contained Mashup Widget so that it better fits in the allowed space. You could add another Label Widget to the Header section to also display the company's motto / tag-line.   Regardless, when you are done with modifications, Save and click View Mashup.     Note that you can left-click-and-drag on the Time Series Chart to select particular time ranges. Or you could add a Time Selector Widget to the bottom-right section to control it there.   Similarly, you could add controls for the Grid Widget to only show the Identifier ranges in which you were interested.   Or you could split out the Model-creation values to a completely separate Mashup as previously discussed.   The extent to which you develop your Mashup is entirely up to you.        Step 10: Next Steps   Congratulations. You've completed the   Enhanced Engine Failure Visualization   guide. In this guide, you learned how to:   Create a Mashup with a Header Divide your Mashup into Sub-sections Use a Contained Mashup to reuse development Store historical data in a Value Steam Display historical data in a Line Chart Show spreadsheet data via a Grid Advanced Widget Tie Mashup controls into the ThingWorx backend   This is the last guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path.   Learn More   We recommend the following resources to continue your learning experience:   Capability  Guide Build Implement Services, Events, and Subscriptions Guide   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Analytics Manager Help Center
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  Create an Engine Failure Prediction GUI to warn about customer issues.   GUIDE CONCEPT   This guide will use ThingWorx Foundation's Mashup Builder to create a Graphical User Interface (GUI) to display results from Analytics Manager comparisons of your analytical model to real-time data.   Following the steps in this guide, you will learn how to utilize Widgets and backend data to quickly visualize customer failure conditions.     YOU'LL LEARN HOW TO   Create a Mashup Add Widgets to represent different data Bring Backend Data into the Mashup Tie data to Widgets View Analytical Results in a convenient GUI   NOTE:  The estimated time to complete all parts of this guide is 30 minutes.     Step 1: Scenario   In this guide, we're finishing up with the MotorCo scenario where an engine can fail catastrophically in a low-grease condition.   In previous guides, you've gathered and exported engine vibration-data from an Edge MicroServer (EMS) and used it to build an engine analytics model. You've even put that analytical model into service to give near-immediate results from current engine-vibration readings.   The goal of this guide is to   create a GUI   to visualize those predicted "low grease" conditions to facilitate customer warnings.     GUI-creation to visualize analytical model deployment can be extremely helpful for the automative segment in particular. For instance, each car that comes off the factory line could have an EMS constantly sending data from which an analytical model could automatically detect engine trouble.   This could enable your company to offer an engine monitoring subscription service to your customers.   This guide will show you how to visualize the results of an engine analytic model for a "smart, connected products" play.     Step 2: Create Mashup   Mashups are ThingWorx Foundation's method of creating Graphical User Interfaces (GUIs).   Mashups are created through the Mashup Builder interface.   Before you can use this drag-and-drop interface, you must first create a new Mashup.      1. In ThingWorx Foundation Composer, click Browse > Visualization > Mashups.      2. Click + New.        3. Leave the defaults and click OK.        4. In the Name field, type EFPG_Mashup.      5. If Project is not already set, search for and select PTCDefaultProject.        6. At the top, click Save.        7. At the top, click Design. You are now in the Mashup Builder interface, where you can drag-and-drop graphical elements (Widgets) to create your GUI.      8. At the top-left, click the Layout tab.        9. Change Positioning to Static. This removes any auto-positioning or dynamic-sizing from our Mashup, so that we can place and size Widgets manually.      10. At the top, click Save again.       Step 3: Add Widgets   We now want to add several   Widgets   to our Mashup by dragging-and-dropping them into the central   Canvas   area.   Return to the   Widgets   tab in the top-left.       2. In the   Filter Widgets   field, type   label.        3. Drag-and-drop five (5) Label Widgets onto the central Canvas area.      4. Select the Label Widgets, go to the Properties in the bottom-left, and change the Label's LabelText to s1_fb1 through s1_fb5.         5. Filter Widgets for text field, and then drag-and-drop five (5) Text Field Widgets onto the central Canvas area.        6. Drag-and-drop two (2) more Label Widgets onto the central Canvas area.      7. Change their LabelText Properties to Result_low_grease and Result_low_grease_mo.        8. Drag-and-drop two (2) more Text Field Widgets onto the central Canvas area.        9. In the top-left Widget's tab, change Category to Legacy.      10. Drag-and-drop an Auto Refresh Widget onto the Canvas.        11. At the top, click Save.         Step 4: Add Data   Now that we have a rough set of Widgets in place to display Data in our Mashup, we need to bring in backend Data from Composer.      1. In the top-right, ensure the Data tab is active.      2. Click the green + button.        3. In the Entity Filter field, search for and select EdgeThing.      4. In the Services Filter field, type getprop.      5. Click the right-arrow beside GetProperties.      6. On the right, check Execute on Load.        7. In the bottom-right, click Done.      8. On the right, expand GetProperties.        9. At the top, click Save.       Step 5: Bind Data   Now that backend Data is accessible inside Mashup Builder, we need to bind it to the various Widgets.   Drag-and-drop Data > Things_EdgeThing > GetProperties > s1_fb1 to the top-left Text Field under the s1_fb1 Label Widget.           2. On the Select Binding Target pop-up, click Text.         3. Repeat for s1_fb2 through s1_fb5 on the 2nd-5th Text Field Widgets.       4. Drag-and-drop Data > Things_EdgeThing > GetProperties > Result_low_grease to the top-right Text Field under the Result_low_grease Label Widget, and select Text on the Binding pop-up.       5. Repeat for Result_low_grease_mo on the Text Field just below.       6. Click the Auto Refresh Widget to select it.       7. In the bottom-left Properties, set RefreshInterval to 1.         8. With the Auto Refresh Widget still selected, click the top-left corner to reveal a drop-down.       9. Drag-and-drop the Refresh Event onto Things_EdgeThing > GetProperties.       10. On the right, click the GetProperties Mashup Data Service to reveal all of its interactions in the bottom-center Connections window.              11. At the top, click Save.       Step 6: View Mashup   In the last guide, we disabled the Analysis Event after confirming that appropriate analytical jobs were being created and completed whenever new data from our EMS Engine Simulator entered Foundation.   We now need to re-enable that Event so that we can see the results in our Mashup.       1. Return to Analytics > Analytics Manager > Analysis Events.       2. Select the Event, and click Enable.   View Analytical Results   With the Analysis Event enabled, we can now view our Mashup to watch engine-failure-predictions be displayed in real time.       1. Return to EFPG_Mashup.       2. At the top, click View Mashup.       3. Wait and notice how the refresh occurs every second, including both true and false analytics results for the "low grease" condition.      4. When you are satisfied that you have observed enough true/false results, return to Analytics > Analytics Manager > Analysis Events and Disable the event.   Through this Learning Path, you have done all of the following:   Connect a remote device to Foundation using the Edge MicroServer (EMS) Fed relevant product-data to the Foundation backend Formatted and exported that data in a manner which Analytics could understand Imported that data and used it to build an Analytics Model of your remote device Started feeding real-time remote data into the model to achieve immediate failure-prediction results Create a GUI to easily visualize those results   You now have a completed Minimum Viable Product (MVP) for a Service Play with MotorCo's new engines.   These new engines may have a known-failure condition, but (because you've instrumented those engines to provide constant data) you can monitor them and predict failures before they actually happen.   This could easily be an up-sell scenario for MotorCo's customers. They could simply purchase the engine. Or they could both purchase the engine and enroll in a service contract where you notified them of impending issues.   What was originally a single-point source of income is now ongoing        Step 7: Next Steps   Congratulations. You've completed the   Engine Failure-Prediction GUI   guide. In this guide you learned how to:   Create a Mashup Add Widgets to represent different data Bring Backend Data into the Mashup Tie data to Widgets View Analytical Results in a convenient GUI   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Enhanced Engine Failure Visualization.   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Build Implement Services, Events, and Subscriptions Guide   Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Analytics Manager Help Center
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    Step 6: Map Data   Now that the event is created, we need to map the Properties of EdgeThing to the fields required to invoke an Analysis Job.   We'll start with the Inputs.   Select the previously-created Event, and click Map Data....   Click Inputs Mapping.   In Source Type, select Thing. In Source, search for and select EdgeThing.   On the left, scroll down and select s1_fb1. Note that you do NOT want the s1_fb1 that is part of the InfoTable Property, because the Info Table Property only stores recorded data, not live data. On the right, select _s1_fb1, the first frequency band required for the Model to make a prediction.   Click the Map button in the center.   Repeat this mapping process for for s1_fb2 through s1_fb5.   Map causalTechnique to causalTechnique in the same manner. This is a String Property in EdgeThing with a Default Value of "FULL_RANGE". Map goalField to goalField in the same manner. This is a String Property in EdgeThing with a Default Value of "low_grease".   Map Results   Now that the Inputs are mapped, we also want to map the Results.   Click Results Mapping on the left.   Map _low_grease to Result_low_grease. Map _low_grease_mo to Result_low_grease_mo.   Click Close to close the mapping pop-up.   Enable Event   Now that we've done the mapping from Foundation to Analytics, let's Enable the Analysis Event so that it can automatically generate and process Analysis Jobs. Select the mapped Analysis Event. Select Enable.   Now that you have enabled the Analysis Event, the new data will be submitted to Analytics Manager whenever EdgeThing's s1_fb1 Property changes.   An Analysis Job will automatically run, with a predictive score sent back and stored in EdgeThing's Result_low_grease (Boolean) and Result_low_grease_mo (Number) Properties.     Step 7: Check Jobs   In this step, we'll confirm that the automatic analysis of information coming from remote devices is operational.   On the ThingWorx Composer Analytics tab, click Analytics Manager > Analysis Jobs.   Uncheck Filter Completed Jobs.   Select a Job and click View.... Click Results.   NOTE: You will see true or false, corresponding to either a low grease or no low grease condition. Using this technology, you could create a paid customer service, where you offered to monitor remote engines, in return for automatically shutting them down before they experience catastrophic engine failure.   For that example implementation, you would utilize the EdgeThing.Result_low_grease BOOLEAN Property to trigger other actions.   For instance, you could create an Alert Event which would be triggered on a true reading.   You could then have a Subscription which paid attention to that Alert Event, and performed an action, such as sending an automatic shutdown command to the engine when it was experiencing a likely low grease event.   NOTE: We recommend that you return to the ThingWorx Composer Analytics > Analytics Manager > Analysis Events tab and Disable the Event prior to continuing. Since the simulator generates an Event every ~1 seconds, this can create a large number of Events, which can fill up your log.       Step 8: Next Steps   Congratulations. You've completed the Manage an Engine Analytical Model guide. In this guide you learned how to:   Define an Analysis Provider that uses the built-in Analytics Server Connector Publish a Model from Analytics Builder to Manager Create an Analysis Event which takes data from ThingWorx Foundation and decides whether or not a failure is likely   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Engine Failure-Prediction GUI.   Learn More   We recommend the following resources to continue your learning experience:    Capability     Guide Build Implement Services, Events, and Subscriptions Guide   Additional Resources   If you have questions, issues, or need additional information, refer to:    Resource              Link Community Developer Community Forum Support Analytics Manager Help Center      
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  Step 7: Real World Model   We’ll now rerun model creation with the Real World data.   Even though Signals and Profiles are possibly telling us that only Sensor 1 is needed, the   first Model   you’ll create will contain   all the data, while the   second Model   will   exclude Sensor 2. We’ll then compare the Models to see which one is going to work the best for predicting engine failures.   On the left, click   Analytics Builder > Models. Click   New….   In the   Model Name   field, enter   vibration_model. In the   Dataset   field, select   vibration_dataset.   Click   Submit. After ~60 seconds, the Model Status will change to   COMPLETED. Select the model that was created in the previous step, i.e.   vibration_model. Click   View…   to open the Model Information page. Note that your model may differ slightly from the picture below, as the automatically-withheld "test" data is randomly chosen.       Unlike our simulated dataset, this real-world data is not perfect. However, it’s still pretty good, and is much more representative of what a real-world scenario would indicate.   The   True Positive Rate   shown on the Receiver Operating Characteristic (ROC) chart are much higher than the False Positives.   The curve is relatively high and to the left, which indicates a high accuracy level.   You may also click on the   Confusion Matrix   tab in the top-left, which will show you the number of True Positive and True Negatives in comparison to False Positives and False Negatives.     NOTE: The number of correct predictions is much higher than the number of incorrect predictions.   As such,   we now know that our Sensors have a relatively good chance at predicting an impending failure   by detecting low grease conditions before they cause catastrophic engine failure.   Refined Model   We can now compare this   first Model   that includes   both Sensors   to a   Model using only Sensor 1, since we suspect that   Sensor 2 may not be necessary   to achieve our goal. On the left, click   Analytics Builder > Models. Click   New…. In the   Model Name   field, enter   vibration_model_s1_only. In the   Dataset   field, select   vibration_dataset.   On the right beside   Excluded Fields from Model, click the   Excluded Fields   button.   Select   s2_fb1   through   s2_fb5.   While all the s2 values are selected, click the green "right-arrow", i.e. >   button, in the middle.   At the bottom-left, click   Save.   Click   Submit. After ~60 seconds, the Model State will change to   COMPLETED. With   vibration_model_s1_only   selected, click   View….     The ROC chart is comparable to the original model (including Sensor 2).   Likewise, the Confusion Matrix (on the other tab) indicates a good ratio of correct predictions versus incorrect predictions.     NOTE: These Models may vary slightly from your own final scores, as what data is used for the prediction versus for evaluation is random.   ThingWorx Analytics’s Models have indicated that you are likely to receive roughly the same accuracy of predicting a low-grease condition whether you use one sensor or two!   If we can get an accurate early-warning of the low grease condition with just one sensor, it then becomes a business decision as to whether the extra cost of Sensor 2 is necessary.     Step 8: Next Steps   Congratulations! You've successfully completed the   Build an Engine Analytical Model   guide, and learned how to:   Load an IoT dataset Generate machine learning predictions Evaluate the analytics output to gain insight   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Manage an Engine Analytical Model.   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Analyze Operationalize an Analytics Model Build Implement Services, Events, and Subscriptions Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Analytics Builder Help Center
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  Step 5: Import Extension   Now that we have a valid dataset, we want to export it as a   .csv file, which can be imported into ThingWorx Analytics in a future guide to generate an analytical model.   An easy way to do this is with the   CSV Parser Extension, which you’ll now import.       1. Download the CSV Parser Extension from our third party provider IQNOX.   Note:  An account is required but the download is free.     2. At the bottom-left, click Import/Export.       3. On the drop-down, click Import.       4. For Import Option, select Extension.       5. Click Browse and navigate to the extension you downloaded above.       6. Click Open.       7. Click Import.       8. Click Close.       9. On the Refresh Composer? pop-up, click Yes.      Step 6: Create File Repository   ThingWorx Foundation uses File Repositories to read and write files from disk (including .csv files created by the CSV Parser Extension).   In this step, we’ll create a File Repository Entity.       1. Return to Browse > All.       2. Click MODELING > Things.       3. Click + New.       4. In the Name field, type ESDS_File_Repository.       5. If Project is not already set, search for and select PTCDefaultProject.       6. In the Base Thing Template field, search for and select FileRepository.      7. At the top, click Save.        Step 7: Create .csv Export Service   We have imported an Extension which gives us tools to manipulate .csv files. We have created a File Repository to which the export can save the file. We'll now make use of some of this new functionality.    We’ll do so by creating a   Service   which calls built-in functions of the CSV Parser Extension.       1. Return to EdgeThing.       2. Click Services.       3. Click + Add.       4. On the drop-down, select Local (JavaScript).       5. In the Name field, type exportCSVservice.       6. In the blank JavaScript field, copy-and-paste the following code:         var sFile = "vibrationCSVfile.csv"; var paramsCSV = { path: sFile, data: me.infoTableProperty, fileRepository: "ESDS_File_Repository", withHeader: true }; Resources["CSVParserFunctions"].WriteCSVFile(paramsCSV);             7. Click Save and Continue. Note that you should NOT click the top Save button, as that will erase your Service.         Step 8: Export the Engine Data   We now have all the tools in place to export the infoTableProperty as a .csv file to our new File Repository.   All that’s left is to call the appropriate functions.       1. Ensure that you’re still on the Services tab of EdgeThing, and have the exportCSVservice open.       2. At the bottom, click Execute.       3. Return to ESDS_File_Repository.       4. Click Services.       5. Scroll down and find the GetFileListingsWithLinks Service.       6. Click the “Play” icon for Execute service.       7. At the bottom-right, click Execute.       8. On the right, click Thingworx/FileRepositories/ESDS_File_Repository/vibrationCSVfile.csv.     9. The .csv export of the vibration data will now be in your local folder to which your browser saves downloads.       Step 9: Next Steps   Congratulations! You've completed the   Engine Simulator Data Storage   guide, and learned how to:   Create a Timer Subscribe to a Timer to Trigger a Service Generate Mass Amounts of Test Data Import the CSV Parser Extension Create a File Repository Export the Test Data as a Comma-Seperated Values (.csv) file Download from a File Repository   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Build an Engine Analytical Model   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Analyze Build a Predictive Analytics Model Build Implement Services, Events, and Subscriptions   Additional Resources   If you have questions, issues, or need additional information, refer to:        Resource Link Community Developer Community Forum Support Analytics Builder Help Center
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  Step 6: Record Data   Now that we have a place to permanently store the values coming from the EMS engine simulator, we'll write a   Service   to take samples and place them within the Info Table.   Part of that Service, though, will be incrementing the   identifier, so we'll need to create one last Property.   Ensure that you're on the   Properties and Alerts   tab of   EdgeThing. At the top-left, click   + Add.     In the   Name   field of the slide-out on the right, type   identifier. Change the   Base Type   to   NUMBER. Click   Persistent. Click   Has Default Value. In the   Has Default Value   field, type   0.   At the top-right, click the "Check" button for   Done. At the top, click   Save.   Store the Property Values   With all the pieces in place, we can now create our Service to add entries to our Info Table Property.   At the top of   EdgeThing, click   Services.   At the top-left, click   + Add.   On the "+ Add" drop-down, select   Local (JavaScript). In the   Service Info > Name   field, type   recordService.     Expand   Me/Entities > Properties.     Click the   arrow   beside   infoTableProperty.     Type   .AddRow({   after me.infoTableProperty to being the process of calling the "AddRow()" function.     We now have called the function which will add a row of information to the Info Table Property, one entry for each column of the formatting Data Shape.   We just need to specify which values go into which column.   Add the following lines to store the individual Identifier count into the first column of the Info Table Property: identifier:me .identifier , Because we want the identifier in the stored data to increment on each run, and we want to start the count at   1   (and the Default Value is 0), add the following line to the top of the Service: me .identifier= me .identifier+ 1 ;       Add the low_grease value with the following line: low_grease:me .low_grease , Add the following lines to store the five frequency bands of the first sensor: s1_fb1:me .s1_fb1 , s1_fb2:me .s1_fb2 , s1_fb3:me .s1_fb3 , s1_fb4:me .s1_fb4 , s1_fb5:me .s1_fb5 , Add the final lines to store the five frequency bands of the second sensor and close out the AddRow() function: s2_fb1: me .s2_fb1, s2_fb2: me .s2_fb2, s2_fb3: me .s2_fb3, s2_fb4: me .s2_fb4, s2_fb5: me .s2_fb5 }); You completed Service should look like the following: me .identifier= me .identifier+ 1 ; me .infoTableProperty.AddRow({ identifier: me .identifier, low_grease: me .low_grease, s1_fb1: me .s1_fb1, s1_fb2: me .s1_fb2, s1_fb3: me .s1_fb3, s1_fb4: me .s1_fb4, s1_fb5: me .s1_fb5, s2_fb1: me .s2_fb1, s2_fb2: me .s2_fb2, s2_fb3: me .s2_fb3, s2_fb4: me .s2_fb4, s2_fb5: me .s2_fb5 });     At the top, click   Done. At the top, click   Save.       Run the Service   With our Service completed, let's run it to store a sampling of the data coming from our EMS Engine Simulator.   Under the   Execute   column in the center, on the   recordService row, click the "Play" icon for   Execute service. At the bottom-right, click   Execute.     At the bottom-right, click   Done. At the top, click   Properties and Alerts.   Under the   Value   column, on the   infoTableProperty   row, click the "Pencil" icon for   Set value of property.   Note that the Service has captured a snap-shot of the vibration data and grease condition and permanently stored it within the Info Table Property. You now have not only an Engine Simulator that is constantly sending data from a remote EMS, but a way to permanently record data at points that you deem significant.   Feel free to return to the Service and call it several more times. Each time, the values coming from the Engine Simulator will be stored in another entry in the Info Table Property.       Step 7: Next Steps   Congratulations! You've successfully completed the   Use the EMS to Create an Engine Simulator   guide, and learned how to:   Modify an EMS Template Provision Thing Properties and Values from an EMS rather than Foundation Send information from an EMS to Foundation Store large amounts of data in an InfoTable Property Create a simulator for testing   The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Engine Simulator Data Storage. Learn More We recommend the following resources to continue your learning experience: Capability Guide Build Engine Simulator Data Storage Build Implement Services, Events and Subscriptions Additional Resources If you have questions, issues, or need additional information, refer to: Resource Link Community Developer Community Forum Support Analytics Builder Help Center  
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    Step 5: Verify Connectivity    The EMS is now attempting to talk to the ThingWorx platform.   However, ThingWorx does not have detailed information about the Edge device that is attempting to connect to it, so it will show up in the   Unbound   category.   Open   ThingWorx Composer.     On the left, click   Monitoring.     Click   STATUS > Remote Things.     Click   Unbound.     Confirm that you see the   EdgeThing   listed in the Unbound section. NOTE : The name   EdgeThing   comes from the config.lua script. EdgeThing is simply the name that is in that script, hence the name that you see in ThingWorx. To change the name of the device, you could stop both wsems.exe and luaScriptResource.exe, edit config.lua to use a different Thing name other than EdgeThing, and then restart both of the WSEMS programs. At that point, the Thing showing up in   Remote Things -> Unbound   would be whatever name you changed to in config.lua.   Create a Remote Thing   Now that the EMS is communicating with Foundation, let's create a Remote Thing to which Foundation can tie said connection.   In   ThingWorx Composer, click   Browse > MODELING > Things, + New.     In the   Name   field, enter   EdgeThing. Note that the name   must   match the spelling and capitalization of the Thing's name that you entered in the EMS's config.lua for it to auto-connect.  If Project is not already set, search for and select PTCDefaultProject. In the   Base Thing Template   field, search for and select RemoteThingWithTunnelsAndFileTransfer.   At the top, Click   Save. Note the status-indication pop-up indicating that EdgeThing is now connected.   Use Services to Explore EMS Files   Now that your Remote Thing is Saved and Connected, we can use some of the built-in Services to explore the EMS folders and files which we previously created for testing purposes.   At the top of   EdgeThing, click   Services.   Under the   Execute   column, click the   Play Symbol   for   BrowseDirectory.   In the top-left   path   field, type   /   and click the bottom-right   Execute   button. Note the   other   and   tw   folders which we previously created for testing.     In the top-left   path   field, type   /tw   and click the bottom-right   Execute   button. Note the   tw_test_01.txt   file which we previously created for testing.     As the   tw_test_01.txt   file (and its parent folder) were items which we custom-created for this guide, you should now be 100% convinced that connectivity between Foundation and the EMS is dynamically working.   If so desired, you could explore into other folders (or even add additional files to these folders), run the   BrowseDirectory   Service again, and confirm that Foundation is now aware of the EMS and actively communicating.     Step 6: Next Steps   Congratulation! You've completed the   Install the Edge MicroServer (EMS)   guide.   In this guide, you learned how to:   Install the EMS Configure the EMS Connect the EMS to ThingWorx Foundation   The next guide in the Medical Device Service learning path is Setup a Raspberry Pi as an IoT Device.    The next guide in the Vehicle Predictive Pre-Failure Detection with ThingWorx Platform learning path is Use the EMS to Create an Engine Simulator.   Learn More   We recommend the following resources to continue your learning experience:   Capability Guide Connect Connect Industrial Devices and Systems   Additional Resources   If you have questions, issues, or need additional information, refer to the:   Resource Link Community Developer Community Forum
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Use Rockwell Automation's Connected Components Workbench to connect an Allen-Bradley PLC for use with the ThingWorx Platform. This Learning Path will guide you through installation of Rockwell Automation and ThingWorx applications, connecting ThingWorx to the Allen-Bradley PLC, and how to configure, monitor, and control the PLC from ThingWorx.   NOTE: Complete the following guides in sequential order. The estimated time to complete this learning path is 240 minutes.   This learning path assumes that ThingWorx has already been installed   1, Install Rockwell Connected Components Workbench 2. Install ThingWorx Kepware Server 3. Connect to an Allen-Bradley PLC 4. Create An Application Key 5. Model an Allen-Bradley PLC 6. Visualize an Allen-Bradley PLC  Part 1 Part 2
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    Step 5: Tie Data to Widgets   The Mashup now has access to the backend data via get/set Data Services.   In this step, you will tie these Data Services to the Checkbox Widgets to pull and push information.   Click the Data tab in the upper right   Under   GetProperties, click and drag the arrow next to   Channel2_myPLC_Coil2   onto the   Left Checkbox. On the   Select Binding Target   pop-up, click   State.   Click the Data tab again Drag   Channel2_myPLC_Coil3   onto the   right Checkbox. On the   Select Binding Target   pop-up, click   State.   Enable Automatic Updates   The   GetProperties   Mashup Data Service will now propagate the State of Coil2 and Coil3 from the PLC onto these   Checkbox   Widgets.   The GetProperties Service will be called automatically when the Mashup loads, so the Checkboxes states will be accurate on initial viewing.   However, the backend data state changes, you will need the GetProperties Service to be automatically called again to update the Checkbox Widgets.   Fortunately, it is simple to trigger this behavior.   Click the   Data   tab Click   GetProperties   to select it.   On the right of the Mashup Builder, Click the   Data Properties   tab     Click the   Automatically Update Values   checkbox   Allow Bidirectional Sets   You also want to enable bi-directional communication, not only displaying the current value of the PLC, but also setting it via the Mashup GUI.   The SetProperties Mashup Data Service can accomplish this.   Click the   Right Checkbox   to select it.   Click   the Checkbox Widget's top-left   drop-down menu   to expose the available options.   Drag State over the Data tab to expand it. Drop onto SetProperties > Channel2_myPLC_Coil3.   Click   the right Checkbox   drop-down menu   again.   Click   Configure Bindings.   Click the down arrow to the right of   Changed.   Click   Add Trigger Service. Click the   Data   tab. Select the   setProperties   check box.   Click   Next   to close the   Trigger Services   window. Click   Done   to close the   Configure Bindings   pop-up. At the top, click   Save.     Step 6: View Mashup    Your Mashup is now complete with two   Checkbox   Widgets and connections from those Widgets to the backend data.   The left Checkbox represents Coil2, and will change its state depending on whether you have touched the lead to the appropriate input on the PLC.   The right Checkbox represents Coil3, and will display the current status as well as allow you to set the status of   Output Coil 3   via checking or unchecking the box.   At the top, click   View Mashup   to display your web application. You may need to set your browser to allow pop-ups.     Select   the   right   checkbox. Note how the PLC's Output Coil 3 will immediately turn on.   Touch the lead to the PLC's   I-02, i.e. Input 2. The left checkbox will indicate the status of Input 2 within a couple of seconds. Step 7: Troubleshooting   If the connection to the PLC stops working and there is a   Thumbs Down   icon next to your properties, the   ThingWorx Kepware Server   trial edition drivers are not connected to your PLC. The trial edition stops running after 2 hours and must be stopped and restarted. Right-click on ThingWorx Kepware Server icon in system tray.     Click   Stop Runtime service. Wait a minute for the process to stop, then click   Start Runtime service. If   Connected Components Workbench   does not connect to PLC, check the IP address of the PLC using   RS Linx Classic   software that was installed as part of Connected Components Workbench. RS Linx Classic is located   Start > All Programs > Rockwell Software > RSLinx > RSLinx Classic Click   AB_ETHIP-1, Ethernet   and IP addresses of connected PLCs will be discovered NOTE: A   changed PLC IP Address   (typically seen through Connected Components Workbench) will require an IP Address change in ThingWorx Kepware Server settings.     Step 8: Next Steps   Congratulations! You've successfully completed the   Visualize an Allen-Bradley PLC   guide.   In addition, assuming you have been utilizing this guide as part of the   Rockwell Automation   Learning Path, this represents the end of your journey.   You've learned how to:   Create a Mashup Add Widgets Access backend data via Mashup Data Services Tie data to Widgets Create a simple web application that monitors and controls a PLC   This is the last guide in the Using an Allen-Bradley PLC with ThingWorx learning path. Learn More   Capability Resource Analyze Monitor an SMT Assembly Line Additional Resources   For additional information on ThingWorx Kepware Server:   Resource Link Documentation Kepware documentation Support Kepware Support site
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  Create An Application Key Guide   Overview   In order for a device to send data to the Platform, it needs to be authenticated. One authentication method is to use an Application Key. Application Keys, or appKeys, are security tokens used for authentication in ThingWorx. They are associated with a given User and have all of the permissions granted to the User with which they are associated. This is one of the most common ways of assigning permission control to a connected device. NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 30 minutes.    Step 1: Learning Path Overview   This guide explains the steps to create a ThingWorx Application Key, and is part of a Learning Path. You can use this guide independently from the full Learning Path. If you want to learn to create a ThingWorx Application Key, this guide will be useful to you. When used as part of the Industrial Plant Learning Path, you should already have installed ThingWorx Kepware Server. We will use the Application Key to send information from ThingWorx Kepware Server into ThingWorx Foundation. Other guides demonstrate Foundation's Mashup Builder to construct a website dashboard that displays information from ThingWorx Kepware Server. We hope you enjoy this Learning Path.   Step 2: Create Application Key   Application Keys are assigned to a specific User for secure access to the platform. Using the Application Key for the default User (Administrator) is not recommended. If administrative access is absolutely necessary, create a User and place the User as a member of the SecurityAdministrators and Administrators User groups. Create the User the Application Key will be assigned to. 1. On the Home screen of Composer click + New. 2. In the dropdown list, click Applications Key. 3. Give your application key a name (i.e. MyAppKey). 4. If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. 5. Set the User Name Reference to a User you created. 6. Update the Expiration Date field, otherwise it will default to 1 day. 7. Click Save. A Key ID has been generated and can be used to make secure connections.   IP Whitelisting for Application Keys   One of the features of an Application Key is the ability to set an IP whitelist. This allows the server to specify that only certain IP addresses should be able to use a given Key ID for access. This is a great way to lock down security on the platform for anything that will maintain a static IP address. For example, connected Web-based business systems may have a static IP from which all calls should be made. Similarly, you can use wildcards to specify a network to narrow the range of IP addresses allowed while still offering some flexibility for devices with dynamic IP addresses. Extremely mobile devices should likely not attempt to implement this, however, as they will often change networks and IP addresses and may lose the ability to connect when the IP whitelist feature is used.   Interact with Application Keys Programmatically Service Name Description GetKeyID Returns the ID of this Application Key GetUserName Get the username associated with this Application Key IsExpired Returns if this Application Key is expired ResetExpirationDateToDefault Resets the expiration date of the Application Key to the default time based on configuration in the UserManagement subsystem SetClientName Sets the client name for this Application Key SetExpirationDate Sets the expiration date of this Application Key to a provided date SetIPWhiteList Sets the values for the IP whitelist for this Application Key SetUserName Sets the associated user name for this Application Key   Tip: To learn more about Application Keys, refer to the Help Center   Step 3: Next Steps   Congratulations! You have successfully created an application key. We hope you found this guide useful.     The next guide in the Connect and Monitor Industrial Plant Equipment learning path is Install ThingWorx Kepware Server.    The next guide in the Azure MXChip Development Kit learning path is Connect Azure IoT Devices.   The next guide in the Medical Device Service learning path is Use the Edge MicroServer (EMS) to Connect to ThingWorx.   The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Model an Allen-Bradley PLC.
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Install ThingWorx Kepware Server Guide    Overview   This guide will walk you through the steps to install ThingWorx Kepware Server. NOTE: This guide's content aligns with ThingWorx 9.3 .  The estimated time to complete this guide is 30 minutes.    Step 1: Learning Path Overview   This guide is the first on the Connect and Monitor Industrial Plant Equipment Learning Path, and it explains how to get up and running with ThingWorx Kepware Server. If you want to learn to install ThingWorx Kepware Server, this guide will be useful to you, and it can be used independently from the full Learning Path. In the next guide on the Learning Path, we will create an Application Key which is used to secure the connection between Kepware Server and ThingWorx Foundation. Later in the Learning Path, we will send information from ThingWorx Kepware Server into ThingWorx Foundation. In other guides in this Learning Path, we will use Foundation's Mashup Builder to construct a website dashboard that displays information from ThingWorx Kepware Server. We hope you enjoy this Learning Path.   Step 2: Install ThingWorx Kepware Server   ThingWorx Kepware Server includes over 150 factory-automation protocols. ThingWorx Kepware Server communicates between industrial assets and ThingWorx Foundation, providing streamlined, real-time access to OT and IT data — whether that data is sourced from on-premise web servers, off-premise cloud applications, or at the edge. This step will download and install ThingWorx Kepware Server. Download the ThingWorx Kepware Server executable installer. Select your Language and click OK 3. On the "Welcome" screen, click Next.        4. the End-User License Agreement and click Next.   5. Set the destination folder for the installation and click Next.   6. Set the Application Data Folder location and click Next. Note that it is recommended NOT to change this path. 7. Select whether you'd like a Shortcut to be created and click Next. 8. On the "Vertical Suite Selection" screen, keep the default of Typical and click Next. 9. On the "Select Features" screen, keep the defaults and click Next. 10. The "External Dependencies" screen simply lists everything that will be installed; click Next. 11. On the "Default Application Settings" screen, leave the default of Allow client applications to request data through Dynamic Tag addressing and click Next. 12. On the “User Manager Credentials” screen, set a unique strong password for the Administrator account and click Next. Note that skipping setting a password can leave your system less secure and is not recommended in a production environment. 13. Click install to begin the installation. 14. Click finish to exit the installer.     Step 3: Open ThingWorx Kepware Server   Now that ThingWorx Kepware Server is installed, you will need to open it. In the bottom-right Windows Taskbar, click Show hidden icons. 2. Double-click on the ThingWorx Kepware Server icon. 3. ThingWorx Kepware Server is now installed. 4. For additional information on ThingWorx Kepware Server, click Server Help on the Menu Bar.   Step 4: Next Steps   Congratulations! You've successfully completed the Install ThingWorx Kepware Server guide. In this guide, you learned how to:   Download, install, and open ThingWorx Kepware Server   The next guide in the Connect and Monitor Industrial Plant Equipment learning path is Connect Kepware Server to ThingWorx Foundation.    The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Connect to an Allen-Bradley PLC. . 
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  Learn how to connect ThingWorx Kepware Server to Foundation.   Guide Concept   This guide will teach you how to create a backend Data Model in ThingWorx Foundation that works with ThingWorx Kepware Server to collect data from an Allen-Bradley PLC and send it to ThingWorx Foundation.   You'll learn how to   Create a Data Model in ThingWorx Foundation that accepts information from ThingWorx Kepware Server   NOTE:  The estimated time to complete this guide is 30 minutes       Step 1: Learning Path Overview   Assuming you are using this guide as part of the Rockwell Automation Learning Path, then you have now completed each of the following installations:   Connected Components Workbench ThingWorx Kepware Server ThingWorx Foundation (for Windows)   You’ve also connected an Allen-Bradley PLC to Connected Components Workbench and then to ThingWorx Kepware Server.   In this guide, we’ll propagate that information further from ThingWorx Kepware Server into ThingWorx Foundation.     Step 2: Create Gateway   To make a connection between ThingWorx Kepware Server and Foundation Server, you must first create a Thing. WARNING: To avoid a timeout error, create a Thing in ThingWorx Foundation BEFORE attempting to make the connection in ThingWorx Kepware Server. In ThingWorx Composer, click Browse. On the left, click MODELING -> Things.   Click + NEW. In the Name field, enter IndConn_Server, including matching capitalization. In the Description field, enter an appropriate description, such as Industrial Gateway Thing to connect to ThingWorx Kepware Server.   If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. In the Base Thing Template field, enter indus, then select the IndustrialGateway Thing template from the sorted list. Click Save.     Step 3: Connect to Foundation   Now that you’ve created an Industrial Gateway Thing and an Application Key, you can configure ThingWorx Kepware Server to connect to ThingWorx Foundation. Return to the ThingWorx Kepware Server Windows application. Right-click Project. Select Properties.   In the Property Editor pop-up, click ThingWorx. In the Enable field, select Yes from the drop-down. In the Host field, enter the IP address of your ThingWorx Foundation server. Enter the Port number. If you are using the “hosted” Developer Portal trial, enter 443.   In the Application Key field, copy and paste the Application Key you just created. In the Trust self-signed certificates field, select Yes from the drop-down. In the Trust all certificates field, select Yes from the drop-down. In the Disable encryption field, select No from the drop-down if you are using a secure port. Select Yes if you are using an http port. Type IndConn_Server in the Thing Name field, including matching capitalization. If you are connecting with a remote instance of ThingWorx Foundation and you expect any breaks or latency in your connection, enable Store and Forward. Click Apply in the pop-up. Click Ok. In the ThingWorx Kepware Server Event window at the bottom, you should see a message indicating Connected to ThingWorx.   NOTE: If you do not see the “Connected” message, repeat the steps above, ensuring that all information is correct. In particular, check the Host, Port, and Thing name fields for errors.     Step 4: Bind Industrial Tag   Now that you’ve established a connection, you can use ThingWorx Foundation to inspect all available information in ThingWorx Kepware Server.   This step will create a new Thing in ThingWorx Foundation representing two output coils of the PLC.   Create Thing for PLC coils   In ThingWorx Foundation Composer, on the left, click MODELING -> Industrial Connections, then click IndConn_Server.   At the top, click Discover. Expand Channel2, then click myPLC. Select check-boxes next to Coil2 and Coil3, then click Bind to New Entity.   Scroll to select RemoteThing, then click OK.   Enter the name PLCcoils, If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. then click Save.   Test ThingWorx Foundation to PLC Communication   Click the Properties and Alerts tab. Confirm that the isConnected Property has a check in the Value field, indicating a good connection between ThingWorx Kepware Server and the PLC. Click the pencil icon in the Coil3 line to open the edit panel, click the True radio button, then click the save checkmark button.   You should here a soft click from the PLC and the Output 3 indicator will illuminate. ThingWorx Foundation is now controlling the PLC through its connection to ThingWorx Kepware Server.     Step 5: Troubleshooting   If the connection to the PLC stops working and there is a Thumbs Down icon next to your properties, the ThingWorx Kepware Server trial edition drivers are not connected to your PLC. The trial edition stops running after 2 hours and must be stopped and restarted. Right-click on ThingWorx Kepware Server icon in system tray.   Click Stop Runtime service. Wait a minute for the process to stop, then click Start Runtime service. If Connected Components Workbench does not connect to PLC, check the IP address of the PLC using RS Linx Classic software that was installed as part of Connected Components Workbench. RS Linx Classic is located Start > All Programs > Rockwell Software > RSLinx > RSLinx Classic Click AB_ETHIP-1, Ethernet and IP addresses of connected PLCs will be discovered NOTE: A changed PLC IP Address (typically seen through Connected Components Workbench) will require an IP Address change in ThingWorx Kepware Server settings.       Step 6: Next Steps   Congratulations! You've successfully completed the Model an Allen-Bradley PLC guide. You've learned how to:   Create a data model that can accept information from ThingWorx Kepware Server Connect ThingWorx Kepware Server to Foundation   The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Visualize an Allen-Bradley PLC.   Learn More     Capability      Resource Analyze Monitor an SMT Assembly Line   Additional Resources   For additional information on ThingWorx Kepware Server:     Resource              Link Documentation Kepware documentation Support Kepware Support site
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    Install a Connected Components Workbench to program an Allen-Bradley PLC   Guide Concept   In this guide, you'll install Rockwell Automation's Connected Components Workbench, which facilitates programming of an Allen-Bradley PLC.   You'll learn how to   Create a Rockwell Automation Account Download software from Rockwell Automation's website Install Connected Components Workbench   NOTE: The estimated time to complete this guide is 60 minutes       Step 1: Learning Path Overview   Welcome to the Rockwell Automation Learning Path!   This first guide explains the steps to get up and running with Rockwell's Connected Components Workbench, a software program to facilitate connecting to and configuring Programmable Logic Controllers, i.e. PLCs.   PLCs are commonly used in factories and other automation scenarios to control minor aspects, such as turnning particular devices on or off based on a particular situation.   Note that you don't necessarily have to run through this guide as part of the Learning Path. If you simply want to learn how to install Connected Components Workbench, this guide can still be useful to you.   But assuming you are using this guide as part of the Rockwell Automation Learning Path, then the first elements will be to install your software, i.e.:   Connected Components Workbench ThingWorx Kepware Server ThingWorx Foundation (for Windows)   You'll then connect an Allen-Bradley PLC to Connected Components Workbench and then to ThingWorx Kepware Server.   Next, we'll propogate that information further from ThingWorx Kepware Server into Foundation. Finally, we'll use Foundation's Mashup Builder to construct a GUI which can both receive and send information to the PLC.   We hope you enjoy this Learning Path.       Step 2: Signup   To access Rockwell Automation software, you first have to create an account on the Rockwell Automation website.   Go to the Rockwell Automation site.   In the top-right, click the "person symbol" for Account.   On the right, click Create an Account.   Enter a valid email address which you control and click Continue.   Enter your first and last names, your country, and click Continue.   Enter your job information and click Continue.   Enter and re-enter a password, check the EULA agreement box, and click Create Account.   Rockwell will send a verification email to the address you previously entered.   Locate the email and click Verify My Email Address.   A new browser tab will open with your verification; click Proceed to Sign In.   Sign-in with your verified email address.       Step 3: Download   Now that you have a verified Rockwell account, you will download Connected Components Workbench.   This download is a little different in that it actually has two parts.   You have to download both, and then run a built-in combiner to get access to the actual installation files.   Go to the Connected Components Workbench download site. Click Select Files. On the pop-up, check Connected Components Workbench and click Downloads. On the new pop-up, click DOWNLOAD NOW. On the download Software End-User License Agreement page, click Accept and Download. Move the download into a separate folder. Right-click on the download and select Run as administator. Agree to let the program make changes to your computer.   The download-manager will then begin the download of the actual software. Click Close when the download has completed.   Notice that there is now a new C:\RA\CCW folder.   Right-click  on  part1.exe  and select  Run as administator .   On the WinRAR self-extracting archive window, click  Extract .   Notice that there is now a new "DVD" folder.   Navigate into the "DVD" folder.   Notice the Setup.exe file, which will be used to install Connected Components Workbench.       Step 4: Install   Now that you have Connected Components Workbench properly downloaded and extracted, you can begin the installation.   Right-click on Setup.exe and select Run as administrator. Click Yes to allow the program to make modifications to your computer.   Click Install now.   On the EULA screen, click Accept all.   Allow the installer to run to completion. This may take ~30 minutes..   Click Restart now to reboot and complete the installation.   After restarting, you may be asked to set your Country/Territory.   Click OK to confirm.   In the Windows "Start" menu, navigate to and expand the Rockwell Automation folder.   Click Connected Components Workbench.       Step 5: Next Steps   Congratulations! You've successfully completed the Connected Components Workbench installation guide.   In this guide, you learned how to:   Create a Rockwell Automation Account Download software from Rockwell's website Install a Connected Components Workbench   The next guide in the Using an Allen-Bradley PLC with ThingWorx learning path is Install ThingWorx Kepware Server.    Learn More    Capability Resource Manage Install ThingWorx Kepware Server   Additional Resources   For additional information on Rockwell:    Resource Link Documentation Rockwell Literature Library Documentation Connected Components Workbench
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