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ThingWorx Navigate is now Windchill Navigate Learn More

IoT & Connectivity Tips

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<p>We live in a connected world where we can (want!) to receive instant updates and notifications. ThingWorx leverages the power of Web 2.0 and its Always-On technology to deliver that, but our friendly SMS providers have also provided an easy and powerful way that can be used to deliver SMS notifications right to your phone. Email to Text!</p><div>Set up a 'notification' Thing using our MailServer Template, set up your outgoing e-mail server and you are now ready to invoke the 'SendMessage' service on a given event. All you need now is the email address of your SMS number, which you can find by following this link: <a href="http://sms411.net/how-to-send-email-to-a-phone/" target="_blank"><span style="font-size:8.5pt;line-height:115%;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;">List of e-Mail to SMS  addresses</span></a></div><p class="MsoNormal"><o:p></o:p></p><div><p class="MsoNormal"><o:p></o:p></p></div><p></p>
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Users of ThingWorx Analytics (TWA) may choose to create a predictive model using TWA or import a predictive model that was created using other software. When importing into or exporting out of TWA, this predictive model must be in a PMML (Predictive Model Markup Language) version 4.3+ format. This post describes how to complete the import and export processes. Exporting: The user may create a model in two main ways inside of TWA: using the Builder user interface, or by using ‘Create Job’ service that exists the Training Thing. Whichever method is used, a model Job Id is created automatically by TWA for that model. It is this model Job Id that is used to identify the model inside of TWA, regardless of what is being done with that model.   If a model is trained using Builder, the user may highlight that model, click ‘Job Details’, and then copy the Job ID. This is done as follows:   Next, the user will navigate to Browse --> Things --> …TrainingThing. This is the Training Microservice inside of TWA where all the functionality involved with training a model exists. Within the …TrainingThing, the user will execute the ‘RetrieveModel’ service under Services. When executing the service, the user will paste the model Job ID (ex. 49704f1a-7fcd-4e38-ab53-84ef46517d0a) they copied earlier, and press ‘Execute’. The resulting text can then be highlighted and copied to Notepad or some other text editor, and saved as .pmml format (ex. ‘ModelExport.pmml’).   Importing Through Results Microservice: To import a model that has been saved in PMML 4.3+ format into TWA using the Results Microservice, the user will navigate to Manage --> Repositories (ex. AnalyticsUploadStorage) --> Actions --> Upload, and choose the PMML file. The user will then navigate to Browse --> Things --> …ResultsThing. This is the Results Microservice inside of TWA where all the functionality exists related to previously trained models. Within the …ResultsThing, the user will execute the ‘UploadModel’ service under Services. Alternatively, the user can upload the model from any repository using ‘UploadModelFromRepository” service.   To create a model from the uploaded PMML inside of TWA, the user will fill out the filePath and name then execute the service. Note: This model will not show up in Builder, as that would require model validation information that is not part of the imported PMML file.   The resulting Job Id can be used to make predictions, such as by using the …PredictionThing’s BatchScore or RealtimeScore services. At this point, the uploaded model acts the same way as if the model were created inside of that TWA environment.       Importing Through Analytics Manager: To import a model that has been saved in PMML 4.3+ format into TWA using the Analytics Manager, the user will navigate to Analytics --> Analytics Manager --> Analysis Models, and click the green “New” button. Next the user will choose the provider name (or create a new one by navigating to Analytics --> Analytics Manager --> Analysis Providers). The user will also check the box to “Upload Model”, and click the grey “Choose File” button to find the PMML file. Finally, the user will click the black “Upload” button, then the green “Save” button.     At this point, the model is uploaded into ThingWorx Analytics, and the user may progress through the subsequent steps to set up “Analysis Events” and “Analysis Jobs” that will be powered by the imported model.
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Hello Navigate Community -     In case you haven't heard, Navigate 8.5 was released last Thursday, 9/26 and is now available for download! This release includes a lot of exciting functionality:   1. Improvements to View Apps -  Updated ThingView 3D Viewing Component - which is now documented & supported for use in custom mashups;  Support for distributed vaults;  Display of security labels & values. 2. BETA release of the first Reusable Components for rapid application development  3. First Navigate Contribute App for review & approval of Windchill Change Requests Want to learn more? Read on!   Introducing change can result in higher costs if not fully considered.  That’s why collaboration is a necessity across people and processes from the initial state of product ideation through to manufacturing, device connectivity and field service.  There is a need to not just access product and enterprise data easily, but to participate in strategic product lifecycle processes in order to avoid unintended consequences.   ThingWorx Navigate 8.5 introduces the first App in the Contribute Series. This App allows key stakeholders to be directly involved in the change process by enabling them to voice their opinions. The first of the Contribute apps for Change Management stitches all these voices together within the digital thread.   Inter-operable with Windchill 11.2 and Windchill 11.1 M020 CPS06, this change management app provides a list of open approval tasks and access to full details of the Change Request, along with attachments and affected items.   Configurable by role, this latest Navigate App enables a broad set of users inside and outside of engineering to fully participate in a digital change management workflow. Cross-functional users who review their task list, via “My Tasks”, are best able to complete changes online. These users can then assess change impacts at time of review, resulting in improved quality by eliminating the need to manually capture input and avoiding errors.   Role-based tailoring facilitates faster, clearer decision making and higher quality changes.  Better participation in the change management process adds the value of faster time to market. This Contribute app is the first to be built from reusable components, thus lowering costs and improving efficiency.   The Thingworx Navigate Contribute app for Change Management enables the wider spread of input to realize the best possible design since products are no longer designed in a silo.   If you have any questions about Navigate or want to connect with an account rep, reach out to me at elarkin@ptc.com.
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Connecting to other databases seemed to be a hot desirable from our training feedback. So we've just added a video tutorial in the Wiki for connecting ThingWorx to SQL Server (or SQL Server Express). See topic 7.04 or go to the Video Appendix. In essence connecting to other databases like mySQL or Oracle will work the same way except you will have to change the Database URL and JDBC reference. Also let me take this opportunity to wish everyone a blessed holiday season!
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  After months of development, hours of user interviews and countless coffees, ThingWorx Solution Central is here!   I posted a few weeks ago introducing the new cloud solution management portal, but just as a reminder, ThingWorx Solution Central is a brand-new set of cloud services offered to help you more efficiently manage and deploy your solutions—ow ow!   ThingWorx Solution Central automatically identifies and packages up your dependencies so you can slash your time to deploy. Once you develop your solution in ThingWorx (using the Projects feature), ThingWorx Solution Central will then automatically package up all the artifacts and dependencies required for your solution to run, and then you can publish your “package” up to the cloud, where it will be ready to be deployed to your specified environment(s).     Ready to get started? Request access to ThingWorx Solution Central here and you’ll be on your way to easier solution deployments in no time.   And if you happen to run into any trouble, see the ThingWorx Solution Central Help Center.   Happy deploying!   Stay connected, Kaya
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   Who’s ready for exciting new functionality like smoother integration with Azure, rapid deployment capabilities, flexible KPIs and so much more?   Good news! Yesterday, we released ThingWorx 8.5—equipped with features like a new Azure connector for ThingWorx Flow, new software content management (SCM) capabilities with the Azure IoT Hub Connector, streamlined deployments with Solution Central, flexible KPI calculations with our PTC manufacturing and service apps—just to name a few. Check out the 8.5 release notes to discover all the highlights and goodness of our latest release and hear our CTO of IoT, Joe Biron (who you may recognize from previous Ask Kaya posts) and one of our product experience specialists, Sebastian Bergner, highlight new functionality and share demos in this exciting webcast (please note that we've had a little snafu with the link and the recording should be available later this week).   Play around with our new features by downloading ThingWorx 8.5, and let the good times roll.   Let us know what you think in the comments below and be on the lookout for future Ask Kaya posts highlighting new 8.5 functionality.   Stay connected, Kaya
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One commonly asked question is what are the correct settings for the Configuration Tables tab when creating/setting up a Database Thing to connect to a SQL Server (2005 or later) database.  There are a couple of ways to do this but the tried and true settings are listed below. connectionValidationString - SELECT GetDate() jDBCConnectionURL - jdbc:sqlserver://servername;databaseName=databasename jDBCDriverClass - com.microsoft.sqlserver.jdbc.SQLServerDriver Max number of connections in the pool - 5 (this can be modified based on number of concurrent connections required) Database Password - databaseusername Database User Name - databaseuserpassword <br> The jdbc driver file sqljdbc4.jar is by default installed with the ThingWorx server.  It is located in TomcatDir\webapps\Thingworx\WEB-INF\lib\
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ThingWorx Foundation Flow Enable customers using Azure to take advantage of Azure services Access hundreds of Azure system connectors by invoking Azure Logic Apps from within ThingWorx Flow Execute Azure functions to leverage Azure dynamic, serverless scaling and pay just for processing power needed Access Azure Cognitive AI services for image recognition, text to voice/voice to text, OCR and more Easily integrate with homegrown and commercial solutions based on SQL databases where explicit APIs or REST services are not exposed Automatically trigger business process flows by subscribing to Windchill object class and instance events Provide visibility to mature PLM content (such as when a part is released) to downstream manufacturing and supply chain roles and systems Easily add new actions by extending functionality from existing connectors to create new actions to facilitate common tasks Inherit or copy functionality from existing actions and change only what is necessary to support new custom action Azure Connector SQL Database Connector Windchill Event Trigger Custom Action Improvements Platform Composer: Horizontal tab navigation is back!  Also new Scheduler editor. Security: TLS 1.2 support by default, new services for handling expired device connections New support for InFlux 1.7 and MSSQL 2017 * New* Solution Central Package, publish and upload your app with version info and metadata to your tenancy of Solution Central in the PTC cloud Identify missing dependencies via automatic dependency management to ensure your application is packaged with everything required for it to run on the target environments Garner enterprise-wide visibility of your ThingWorx apps deployed across the enterprise via a cloud portal showcasing your company’s available apps, their versions and target environments to foster a holistic view of your entire IIoT footprint across all of your servers, sites and use cases Solution Central is a brand-new cloud-based service to help enterprises package, store, deploy and manage their ThingWorx apps Accelerate your application deployment Initially targeted at developers and admins in its first release, Solution Central enables you to: Mashup Builder 9 new widgets, 5 new functions. Theme Editor with swappable Mashup Preview Responsive Layout enhancements including new settings for fixed and range sizes New Builder for custom screen sizes, new Widget and Style editors, Canvas Zoom Migration utility available for legacy applications to help move to latest features Security 3 new built-in services for WebSocket Communications Subsystem: QueryEndpointSessions, GetBoundThingsForEndpoint, and CloseEndpointSessions Provide greater awareness of Things bound to the platform Allow for mass termination of connections, if necessary Can be configured to automatically disconnect devices with expired authentication methods Encrypting data-in-motion (using TLS 1.2) is a best practice for securely using ThingWorx For previous versions, the installer defaulted to not configuring TLS; ThingWorx 8.5 and later installers will default to configuring TLS ThingWorx will still allow customers to decline to do so, if desired Device connection monitoring & security TLS by default when using installer   ThingWorx Analytics Confidence Model Training and Scoring (ThingWorx Analytics APIs) Deepens functionality by enabling training and scoring of confidence models to provide information about the uncertainty in a prediction to facilitate human and automated decision making Range Property Transform and Descriptive Service Improves ease of implementation of data transformations required for common statistical process control visualizations Architecture Simplification Improves cost of ownership by reducing the number of microservices required by Analytics Server to reduce deployment complexity Simplified installation process enables system administrators to integrate ThingWorx Analytics Server with either (or both) ThingWorx Foundation 8.5 and FactoryTalk Analytics DataFlowML 3.0.   ThingWorx Manufacturing and Service Apps & Operator Advisor Manufacturing common layer extension - now bundling all apps as one extension (Operator Advisor, Asset Advisor, Production KPIs, Controls Advisor) Operator Advisor user interface for work instruction delivery Shift and Crew data model & user interface Enhancements to Operator Advisor MPMLink connector Flexible KPI calculations Multiple context support for assets   ThingWorx Navigate New Change Management App, first in the Contribute series, allows a user to participate in change request reviews delivered through a task list called “My Tasks” BETA Release of intelligent, reusable components that will dramatically increase the speed of custom App development Improvements to existing View Apps Updated, re-usable 3D viewing component (ThingView widget) Support for Windchill Distributed Vaults Display of Security Labels & Values   ThingWorx Azure IOT Hub Connector Seamless compatibility of Azure devices with ThingWorx accelerators like Asset Advisor and custom applications developed using Mashup Builder. Ability to update software and firmware remotely using ready-built Software Content Management via “ThingWorx Azure Software Content Management” Module on Azure IoT Edge. Quick installation and configuration of ThingWorx Azure IoT Hub Connector, Azure IoT Hub and Azure IoT Edge SCM module.   Documentation ThingWorx Platform ThingWorx Platform 8.5 Release Notes ThingWorx Platform Help Center ThingWorx 8.5 Platform Reference Documents ThingWorx Connection Services Help Center   ThingWorx Azure IoT Hub Connector ThingWorx Azure IoT Hub Connector Help Center   ThingWorx Analytics ThingWorx Platform Analytics 8.5.0 Release Notes Analytics Server 8.5.1 Release Notes ThingWorx Analytics Help Center   ThingWorx Manufacturing & Service Apps and ThingWorx Operator Advisor ThingWorx Apps Help Center ThingWorx Operator Advisor Help Center   ThingWorx Navigate ThingWorx Navigate 8.5 Release Notes Installing ThingWorx Navigate 8.5 Upgrading to ThingWorx Navigate 8.5 ThingWorx Navigate 8.5 Tasks and Tailoring Customizing ThingWorx Navigate 8.5 PTC Windchill Extension Guide 1.12.x ThingWorx Navigate 8.5 Product Compatibility Matrix ThingWorx Navigate 8.5 Upgrade Support Matrix ThingWorx Navigate Help Center     Additional Information Helpcenter ThingWorx eSupport Portal ThingWorx Developer Portal PTC Marketplace The National Instruments Connector can be found on PTC Marketplace  
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This video shows the steps to install ThingWorx Analytics Server 8.5.1 as well as the ThingWorx Analytics Extension.  
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Challenge:&nbsp;Complex Deployments -Today deployment of twx apps is challenging due to manual dependency management; little visibility into apps and environments; complexity and slow speed of deployment Feature Solution Central: -Automated dependency management -Centralized app management portal Value: Rapid scalable deployments -Accelerate application deployment -Simple UI-based environment and solution management -Site-wide visibility of apps and environments Steps involved: -Develop projects locally -Package artifacts and dependencies -Publish App to Cloud -Deliver to your ThingWorx environments -&gt; -Update to latest ThingWorx -Connect to Solution Central -Begin Publishing -No additional licensing &nbsp; Q: Does it also package up prerequisite extensions? A: It doesn’t package or build them, but they are identified as dependencies before publish/deployment. Multiple solutions building modular structure through dependencies Q: Each published project is packaged as an extension? A: That is correct Q: Is it also possible to manage deployment of collection permissions &amp; OOTB entities permission/configuration through Solution Central ? A: Whatever can be member of the project can be packaged and published Q: Can we package locally without publish to cloud A: Yes. Just don't register to Solution Center Q: How to install a solution offline ? A: One can package locally and install them as extensions Q: Is Solution Central a Cloud only application? A: Yes, but the packaging capability is available in ThingWorx Q: Do all customers have access to this solution or do they need to have a cloud contract? A: All customers can access as part of their ThingWorx license Q: Will customers be able to install their own on-prem implementationn of the Solution Central Web? Is using our cloud required? A: The Solution Central portal will only be available in the PTC Cloud, but the ability to package is part of the platform and can be done on prem.
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New Framework in 8.5 -Install Builder produced installers -Installation orchestrated by Chef - UX Improvements - Cosmetic changes - Increased and improved help texts  - Documentation improvements - Changed layout for clarity - Security improvements Prerequisites:  -Install&Setup DB prior to installation -Set up ThingWorx DB User and database -DB command line tools installed & in the path (psql, msqlcmd) -Java 1.8.144 minimum -Clean machine for the install Common Issues -Command line tools not in path -DB user not set up -DB user with incorrect permissions -Java not installed or in path -Not running on a clean machine -Installed java 32bit instead of 64   Contacts: PM Mike Tresh TPM Jennifer Keane Dev Lead Mickey Kimchi   Q: The Windows/RHEL supported OS is just for installers? Running Thingworx on Ubuntu manually, is still supported? A: Yes. The matrix of supported OS for ThingWorx is larger than what we currently support for automated installs. ThingWorx can still run on Ubuntu Q: Is the support of Ubutu dropped completely , or just for the initial release? A: Support of Ubuntu is not there for the automated installers, it is still there for ThingWorx itself. Q: Would the installers provide a scrolling log or a direct link to the log file ? A: We provide the locations of the log files at the end of the install in the summary, and also the locations are noted in the documentation if you need to see log details. We also provide a progress bar with some info while install is running. The ThingWorx session will now be terminated by the Logout sequence yes. We now show a login browser prompt for TWX if they try to go back. Q: How do we upgrade a TWX 8.4 to TWX 8.5? A: For now, it's the manual upgrade process that you will already be familiar with as documented. Q: Is uninstaller available? A: Yes, there is an uninstaller for Foundation available, it should be present for you after running the installer. Q: Is Docker supported? A: We do support Docker and have samples available.
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Remember that when you are calling an external URL to fetch data via an API call to another system that you must encode special characters specifically. For example the URL that you may type into a browser to test may look like this: https://someserver.somwhere.com:443/apicall?parameter1=test string&parameter2=test^number but when scripting that into a string variable you'll need to replace the space and the carrot with the proper encoded values (%20 and %5E) var params = { username : "me", password : "password", url : "https://someserver.somwhere.com:443/apicall?parameter1=test%20string&parameter2=test%5Enumber", ignoreSSLErrors : false, timeout : 60, headers : headers }; var result = Resources['ContentLoaderFunctions'].LoadXML(params); also note that in this instance we're making a secure connection therefore port 443 (typically the default) was explicitly specified...
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Composer Enhancement: -Improved workflow support NG Composer challenging to navigate -> Usability challenges with editing and viewing data Feature: -Tab style editing support -Horizontal tabs -New Grids with Resizing -Resizing in Entity Grids -Schedule Editor Problem: Need modernization of platform visualization toolset -> -New Webcomponent widgets -Responsive layout now GA -Theming now GA -Key messaging -New ability to build responsive modern web applications   Theming and Theme editor -Centralized style management -Easily apply to all Mashups of an applications -Bindable, can be changed dynamically -Set Colors Typography, Lines, Borders, States -Set globally or by group of elements (buttons, grids, inputs) -Mashup Preview can be set   New Widgets in 8.5 -Breadcrumb -Dynamic panel -Icon -Image -List Shuttle -Property Display -Slider -Value Display -Advanced Grid now part of platform Functions: -Confirmation -Event Router -Logout  -Navigation -Status Message   Responsive Layout -New responsive layout editor, based on Flex -Content lays out according to rules, adapts to the screen size and settings -Static and size range support   Migration When you open a mashup containing legacy widgets for which there are web component replacements available OR You open a mashup containing legacy layouts, a banner appears at the top of the design page Clicking Yes will migrate to new widgets and new flex layout -Bindings in the mashup are retained -Recommended to review widgets sizes   Layout Migration -Static layous are migrated to a responsive flex container Q: There is still no Right mouse click support?  A: We don't have a right click context menu yet, but we're looking into what can be included based on the context for a future release. Q: With flex containers, is it still possible to create a mashup with two columns, one covering 1/3 of the screen, the other 2/3 of the screen, when the size of the screen is not known upfront? A: Correct - you can set container rules to grow and shrink (in your case, set one container to use 1/3rd and the other 2/3rd) Q: Do we have the cut/paste function in the responsive containers so we're able to move content around? A: Yes, now you can move the whole container too! You can either use the cut/ copy/ paste from the toolbar, or use keyboard shortcuts (shift for cut/ move and alt for copy). Q: The old layout widget allowed setting column size as percentage, rather than absolute size. How can that be done in containers? A: With containers, it uses the standard flex-grow and flex-shrink css properties. We have Grow Ratio and Shrink Ratio properties available, and you can set the values there. Q: How are we addressing the expand/collapse functions we used to have in the headers/footers/righ&left side bar? A: Each container  will have an option to Expand/ Collapse. Based on where the container is located (left/ right or top/ bottom), it will expand accordingly - so left/ right sidebar or header/ footer. Q: Does it show which widgets are undergoing the changes from legacy to new? A: The legacy widgets are grouped in the 'Legacy' widget category, and are indicated with an icon noting it's a legacy widget. Q: What about migrating from widget from extension (ie advanced grid) ? Those will be replaced also? A: Correct - when you move to 8.5, you won't have to import the extension any longer. If you have any Mashups with the Advanced Grid in place, it'll pick it up. Q: Can we add CSS to the themes? A: Yes, you can add. The Custom CSS tab is available for Themes specifically too. Q: Bindings of containers won't be saved - does that mean that if we use contained mashup with mashup parameters, all bindings will be lost? A: The bindings within the container should not change; the Mashup parameters will be exposed so that you can bind in/ out. The bindings should be retained - when you migrate from the old layout to the new, any bindings you have should not be lost/ broken.
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  Hi everyone,   Today I’m here with a very exciting guest—Janie! Janie recently joined PTC after spending the last two years at a global professional services firm where she held many roles including that of a lead ThingWorx developer. While Janie did do some font-end development work and UI creation, the bulk of her time was spent on the backend writing services that enabled the application’s functionality. In this role, she not only wrote code herself, she also played a large part in the in-platform architectural decisions, determining the best way to utilize the platform in order to satisfy complex business requirements.   Throughout her last two years, she worked on various IIoT projects in the manufacturing industry developing a real-time asset health monitoring and OEE/production tracking application to monitor key metrics like downtime and output. For each customer engagement an assessment of IoT platforms was often undertaken in order to assess strengths and weaknesses based off-of the business requirements of the customer and while she spent time looking into a variety of platforms, ThingWorx always came out on top.   That said, her experience with ThingWorx showed her how much and how quickly that technology can can change the way a manufacturing company operates. She decided that instead of doing implementations of the technology, she wanted to have an impact on the technology itself and have a hand in the direction it goes and the way it continues to change the businesses we know today. This desire is what led her to product management and the role she currently holds at PTC today.   I recently sat down with Janie to hear how it has been moving from a developer on the platform to a PM for it to learn about her past ThingWorx experiences and how those will influence the work she does at PTC.     Here’s how our convo went.   Kaya: In your previous role as an IoT developer at another company, what made you choose ThingWorx over other IoT solution platforms? Janie: We chose ThingWorx over other IoT platforms due to its strong ability to connect such a wide variety of machines using ThingWorx Industrial Connectivity via Kepware, its industry-leading standing in the market and the fact that it did not require its users to have extensive development knowledge given its low-code environment, which enabled non-developers to be successful.   Kaya: Why do you think ThingWorx saved you time over other development platforms/products? Janie: There were three key ways the platform helped to save me time. First, I didn’t have to write code from scratch. For example, when needing to manipulate arrays or parse through uploaded csv files, there were pieces of code readily available for me to do so without having to know how to do it by myself. Second, due to the widgets ThingWorx already had available, I didn’t have to spend time making custom front-end UIs or widgets. And, thirdly, I saved a ton of time during the connectivity phase because connectivity to devices was supported OOTB through Kepware’s extensive suite of drivers available including some of the key ones we utilized such as Allen-Bradley Control Logix, Modbus, Siemens, and user configurable drivers.   Kaya: Along the lines of saving time, how would your experience with the platform have differed had you leveraged one of our manufacturing apps like Production KPIs? Janie: As I talked about previously, having access to a pre-built solution would have evidently saved a ton of development time and accelerated time to value. It also would have reduced the complexity of our completed app, which would have made it more scalable. While I understand the Manufacturing apps are not 100% ready-to-go out of the box but rather configurable stepping stones into a larger and mole holistic solution, if we could have had Production KPI’s as our development starting point, we would have had a more sound and already proven way of tackling Production and OEE tracking and could have added even more value on top of that.   Kaya: What were some of your favorite aspects about the platform? Janie: The code-snippets to get started were a big favorite, as were the OOTB widgets that allowed for quick visualization of important data. The OOTB industrial connectivity with seamless integration to ThingWorx was huge—we were able to connect multiple devices and stream information in real-time with little difficulty, which enabled us to derive even more value from the platform and really focus on becoming a fully smart and connected operation. Finally, the drag-and-drop UI was simple and intuitive.   Kaya: What do you think the top misconception is about IoT? Janie: I would say repeatability. Scaling an IoT solution across an enterprise is not as simple as it is often represented. I know we’re releasing a new functionality to help users more easily deploy their solutions, so I’m excited about that.   Kaya: So, now that you work as PM for the platform, what were a few things you wish you knew as a developer working on ThingWorx? Janie: Seeing everything we’re working on for the platform now is very exciting; I wish I could have been more aware of what’s on the roadmap so I knew what was coming as I was developing on the platform.   Kaya: On a similar note, now that you are working on the ThingWorx PM team, what items are you hoping to drive/change based on your experience? Janie: First, I’d like to drive stronger interaction with our system integrators (SIs) and partners by providing them insights into our roadmaps and allowing for them to provide feedback in a more seamless way. Next, I’d like to improve upon our essential platform developer capabilities, such as CI/CD, debugging, versioning, testing, etc. That said, Solution Central and PTC’s commitment to and integration with Microsoft products are very exciting roadmap features for me.   Kaya: I completely agree. Those are some great points. As I’m sure you’re aware, but our readers might not be aware of, we are working within the platform itself and a new feature, Solution Central, to provide more of that basic functionality so that, in addition to building blocks, low-code and a drag-and-drop UI, we can continue to help you accelerate your time to value.   Readers, I hope you enjoyed hearing from Janie! We’re excited to have her on the ThingWorx team and we look forward to making ThingWorx even stronger.   Let me know what you think in the comments below.   Stay connected, Kaya
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Anomaly Detection (also known as Outlier Detection) is a set of techniques that identify unusual occurrences in data. The premise is that such occurrences may be early indicators of future negative events (e.g. failure of assets or production lines).  Data Science algorithms for Anomaly Detection include both Supervised and Unsupervised methods. In Unsupervised Anomaly Detection, the algorithms make the assumption that most of the data points are "normal" (e.g. normal operation of the asset) and are looking for data points that are most dissimilar to the remainder of the dataset. Supervised Anomaly Detection requires a labeled set of Anomalies, in which case predictive algorithms can be applied directly on this data.   Thingworx employs a number of algorithms in support of Anomaly Detection: Simple threshold alerts. These are easy to setup on Thing properties but require a domain expert to provide such thresholds. Then, the alert will automatically fire when the value of the monitored property goes outside the predefined range of values, often seen as the "bad" side of the threshold. Statistical Process Control (SPC). This can be implemented using Thingworx Analytics Property Transforms. Most companies use a subset of SPC charts and rules to monitor production processes. Examples include the X Bar and R charts, as well as the Western Electric rules (e.g. one point outside the average +/- three sigma range). Explainable and widely accepted, SPC can also provide an earlier warning system compared to simple threshold alerts, in that it captures more complex patterns. Clustering. Using Thingworx Analytics, one can build an optimal clustering for the available data points. Under the assumption that data is representative of mostly normal operation and that there is not a significant pre-defined pattern of anomalies that form their own cluster, one can identify outliers by looking at the distance between points and their corresponding cluster centers. Points that are very far from their corresponding cluster center can be labeled as anomalies. Semi-supervised Anomaly Alerting (formerly known as ThingWatcher). This functionality identifies single property time series behavior that is statistically different than what was seen in a finite window of “known normal operation”. As such, it does not identify a “bad” event, or even a precursor to a “bad” event.  Rather, it points the end user to further investigate a situation which may lead to a “bad” event. Anomaly Alerts can be easily setup like any other Alert on a Thing property. Multiple Anomaly Alerts can be setup on the same or different properties of a Thing. Behind the scenes, the platform builds a time series neural network model for the known normal operation data, which is then applied to incoming data, and, if the errors are significantly different than those on known normal operation over a period of time, then an Anomaly Alert is produced. The techniques mentioned above are either unsupervised or semi-supervised. If the dataset contains labeled anomalies (e.g. asset faults, or suspicious patterns) then supervised predictive techniques (such as regression, decision trees, neural nets, or ensemble methods) are available to model the relationships between such anomalies (dependent variables) and various variables of interest (independent variables). These models can then be employed to monitor assets or production lines for upcoming anomalies. In many real-world use cases, anomalies are relatively rare; care needs to be taken when building such predictive models. Techniques such as up-sampling can prove beneficial in such situations.   What constitutes an Anomaly depends on the observed data and the current context. If only few data points are initially available, then it is possible that a lot of future data is predicted as an Anomaly, despite being normal operation. Also, in terms of context, if an Anomaly Detection is trained on a connected product in the Winter, it is likely to say all Summer operation is anomalous. This can be tackled by having multiple anomaly detection alerts implemented, one for each different context of operation (e.g. season, recipe being manufactured, operation done by a robot).   Another consideration is lead time vs explainability. For example, when a threshold alert fires, it is obvious why, but it may not be early enough to take action. As more advanced methods are employed, more complex patterns can be captured, hence more lead time, but typically at the expense of explainability. For example, semi supervised Anomaly Alerting (formerly known as ThingWatcher) uses time windows, aggregations, and derivatives of up to the third order, resulting in significantly less explainability when an Anomaly is presented to the end user.   Choosing the appropriate Anomaly Detection technique is use case dependent, balancing the desired lead time and explainability. If historical data on failures/anomalies is not available, a good place to start is Statistical Process Control, as it provides a balanced approach between the two dimensions, in addition to being already in use across many manufacturing companies.
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    Raise your hand if you’re ready for seamless, rapid deployment of your ThingWorx applications with visibility into your various environments! It’s time to say goodbye to error-prone deployments with manual dependency tracking and hello to Solution Central!   Releasing this fall as part of 8.5, Solution Central is a brand-new cloud service coming to the ThingWorx platform to enable you to efficiently manage your ThingWorx applications across the enterprise.   With Solution Central, you’ll no longer be caught chasing missing dependencies (like ThingShapes, Mashups, templates or library extensions). Solution Central automatically identifies and packages up the dependencies required for your application. No more manual dependency madness!   Whether you’re managing many apps deployed to a few environments or a single app deployed to hundreds of environments, Solution Central allows you to accelerate your deployment through an intuitive UI or powerful APIs for automation.   Here’s how it works: Begin by creating your application in Composer with a project. Let Solution Central automatically package up all the artifacts and dependencies required for your application. Allow Solution Central to publish your solution package to the cloud. Deploy your application to your various environments (local servers, data centers, cloud systems) directly from Solution Central. It’s like your company has its own private app store. Here’s a sneak peek of the Solution Central UI! Keep an eye out for the release of ThingWorx 8.5 at the end of Sept 2019 and begin accelerating your app deployment! Check out the presentation and demo my fellow PM Chris Baldwin and I delivered at LiveWorx19—and be sure to attend LiveWorx20! To navigate to our session recording, search for “Introducing Solution Central: Your Gateway to Accelerated IIoT Value Across the Enterprise” here.   Sound interesting? Message me directly to discover how you can become part of the Solution Central Private Preview Program!   -Kaya  
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Smoothing Large Data Sets Purpose In this post, learn how to smooth large data sources down into what can be rendered and processed more easily on Mashups. Note that the Time Series Chart  widget is limited to load 8,000 points (hard-coded). This is because rendering more points than this is almost never necessary or beneficial, given that the human eye can only discern so many points and the average monitor can only render so many pixels. Reducing large data sources through smoothing is a recommended best practice for ThingWorx, and for data analysis in general.   To show how this is done, there are sample entities provided which can be downloaded and imported into ThingWorx. These demonstrate the capacity of ThingWorx to reduce tens of thousands of data points based on a "smooth factor" live on Mashups, without much added load time required. The tutorial below steps through setting these entities up, including the code used to generate the dummy data.   Smoothing the Data on Mashups Create a Value Stream for storing the historical data. Create a Data Shape for use in the queries. The fields should be: TestProperty - NUMBER timestamp - DATETIME Create a Thing (TestChartCapacityThing) for simulating property updates and therefore Value Stream updates. There is one property: TestProperty - NUMBER - not persistent - logged The custom query service on this Thing (QueryNamedPropertyHistory) will have the logic for smoothing the data. Essentially, many points are averaged into one point, reducing the overall size, before the data is returned to the mashup. Unfortunately, there is no service built-in to do this (nothing OOTB service). The code is here (input parameters are to - DATETIME; from - DATETIME; SmoothFactor - INTEGER): // This is just for passing the property name into the query var infotable = Resources["InfoTableFunctions"].CreateInfoTable({infotableName: "NamedProperties"}); infotable.AddField({name: "name", baseType: "STRING"}); infotable.AddRow({name: "TestProperty"}); var queryResults = me.QueryNamedPropertyHistory({ maxItems: 9999999, endDate: to, propertyNames: infotable, startDate: from }); // This will be filled in below, based on the smoothing calculation var result = Resources["InfoTableFunctions"].CreateInfoTable({infotableName: "SmoothedQueryResults"}); result.AddField({name: "TestProperty", baseType: "NUMBER"}); result.AddField({name: "timestamp", baseType: "DATETIME"}); // If there is no smooth factor, then just return everything if(SmoothFactor === 0 || SmoothFactor === undefined || SmoothFactor === "") result = queryResults; else { // Increment by smooth factor for(var i = 0; i < queryResults.rows.length; i += SmoothFactor) { var sum = 0; var count = 0; // Increment by one to average all points in this interval for(var j = i; j < (i+SmoothFactor); j++) { if(j < queryResults.rows.length) if(j === i) { // First time set sum equal to first property value sum = queryResults.getRow(j).TestProperty; count++; } else { // All other times, add property values to first value sum += queryResults.getRow(j).TestProperty; count++; } } var average = sum / count; // Use count because the last interval may not equal smooth factor result.AddRow({TestProperty: average, timestamp: queryResults.getRow(i).timestamp}); } } Create a Timer for updating the property values on the Thing. The Timer should subscribe to itself, containing this code (ensure it is enabled as well): var now = new Date(); if(now.getMilliseconds() % 3 === 0) // Randomly reset the number to simulate outliers Things["TestChartCapacityThing"].TestProperty = Math.random()*100; else if(Things["TestChartCapacityThing"].TestProperty > 100) Things["TestChartCapacityThing"].TestProperty -= Math.random()*10; else Things["TestChartCapacityThing"].TestProperty += Math.random()*10; Don't forget to set the runAsUser in the Timer configuration. To generate many properties, set the updateRate to a small value, like 10 milliseconds. Disable the Timer after many thousands of properties are logged in the Value Stream. Create a Mashup for displaying the property data and capacity of the query to smooth the data. The Mashup should run the service created in step 4 on load. The service input comes from widgets on the mashup: Bindings: Place a Time Series Chart widget in the bottom of the Mashup layout. Bind the data from the query to the chart. View the Mashup. Note the difference in the data... All points in one minute: And a smooth factor of 10 in one minute: Note that the outliers still appear, and the peaks are much easier to see. With fewer points, trends become easier to spot and data is easier to understand. For monitoring the specific nature of the outliers, utilize alerts and other types of displays. Alternative forms of data reduction could involve using the mean of each interval (given by the smoothing factor) or the min or max, as needed for the specific use case. Display multiple types of these options for an even more detailed view. Remember, though, the more data needs to be processed, the slower the Mashup will load. As usual, ensure all mashups are load tested and that the number of end users per Mashup is considered during application design.
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  When it’s time to make pizza, most of us head to the fridge for our bag of dough; we don’t head for the flour and yeast to start from scratch. So, why would your ThingWorx apps be any different? Start with pre-built solutions like Asset Advisor to rapidly create health monitoring apps and dramatically reduce your development time.   We previously introduced Asset Advisor on Episode 04 of “ThingWorx on Air.” Today, we dive deeper into Asset Advisor with Greg Huet, Asset Advisor’s technical product manager (aka product owner). Listen to Ep. 06: Rapidly Build IIoT Apps for Service & Monitoring with Asset Advisor to hear Greg share our strategy of studying existing use cases and finding similarities that we can pre-build into solutions so that you don’t have to build them from scratch. Hear how you can use Asset Advisor out-of-the-box with tweaks for your company’s configurations or as an accelerated starting point where you can add as much customization as your use case desires—it’s like building a custom pizza, but starting with pre-made dough, rather than yeast and flour.   Greg also mentions the ThingWorx Application Development Guide. Be sure to check out my previous post, where Ward, one of the document creators, shares four of his top tips from the guide.   Now, sit back, relax and go enjoy some pizza while you listen to Episode 06.   As always, stay connected! Kaya
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Thingworx Analytics is offered through the User interface called Analytics Builder with some pre-configured functionality. However, should you want to create your own jobs and mashups, all features from Analytics Builder and some more are available through the Thingworx Services.  Running most functionality requires that you provide some data to run the Analytics Services. This is where the datasetRef parameter is required.        Data uploaded through Analytics Builder Any dataset uploaded through builder will require have a datasetUri as shown in the image above and format will be parquet (all small letters) datasetUri can be obtained from the list of datasets in builder Passing data as an in-body Dataset If data isn't uploaded through Analytics Builder, data can be supplied as an Infotable in the data parameter of the datasetRef. Metadata will also need to be supplied if a new dataset is being created (create Job of the AnalyticsServer_DataThing) If this data is being supplied for a scoring job, as long as the column names match up to what the model is expecting, TWX Analytics will inference them appropriately. The filter parameter is for parquet datasets already uploaded into TWXA and will take an ANSI SQL statement format to add conditions to reduce number of rows. Exclusions is an single column infotable list of the columns you wish to remove from the job you are trying to submit Example: If you want Profiles to only run on 5 out of 10 columns, you would give a list of 5 columns that you don't want to include in this exclusions infotable. Data may also be supplied as a csv file in the file repo in some cases, in which case you would give the dataseturi parameter the location of the file on the TWX File repo (of the format thingworx://UseCaseFileRepo/tempdata.csv) and the format which would be csv
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Developing Great IoT Solutions Brought to you once again by your EDC team, find attached here a brand-new, comprehensive overview of ThingWorx best practices! This guide was crafted by combining all available feedback, from support cases to PTC Community threads, and tapping all internal resources. Let this guide serve to bridge the knowledge gaps ThingWorx developers most commonly see.    The Developing Great IoT Solutions (DGIS) Guide is a great way to inform both business and technically minded folks about the capabilities of the ThingWorx Platform. Learn how to design good solutions from a high-level, an overview designed specifically with the business audience in mind. Or, learn how to implement good IoT designs through a series of technical examples. Start from very little knowledge of the Platform and end up understanding data structures and aggregation, how to use the collection widget, and how to build a fully functional rules engine for sending and acknowledging alerts in ThingWorx.   For the more advanced among us, check out the Appendix. Find here a handy list of do's and don'ts surrounding ThingWorx best practice in development, with links to KCS, Help Center, and Community content.   Reinforce your understanding of the capabilities of the ThingWorx Platform with this guide, today!   A big thanks to all who were involved on this project! Happy developing!
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OpenDJ is a directory server which is also the base for WindchillDS. It can be used for centralized user management and ThingWorx can be configured to login with users from this Directory Service.   Before we start Pre-requisiste Docker on Ubuntu JKS keystore with a valid certificate JKS keystore is stored in /docker/certificates - on the machine that runs the Docker environments Certificate is generated with a Subject Alternative Name (SAN) extension for hostname, fully qualified hostname and IP address of the opendj (Docker) server Change the blue phrases to the correct passwords, machine names, etc. when following the instructions If possible, use a more secure password than "Password123456"... the one I use is really bad   Related Links https://hub.docker.com/r/openidentityplatform/opendj/ https://backstage.forgerock.com/docs/opendj/2.6/admin-guide/#chap-change-certs https://backstage.forgerock.com/knowledge/kb/article/a43576900   Configuration Generate the PKCS12 certificate Assume this is our working directory on the Docker machine (with the JKS certificate in it)   cd /docker/certificates   Create .pin file containing the keystore password   echo "Password123456" > keystore.pin   Convert existing JKS keystore into a new PKCS12 keystore   keytool -importkeystore -srcalias muc-twx-docker -destalias server-cert -srckeystore muc-twx-docker.jks -srcstoretype JKS -srcstorepass `cat keystore.pin` -destkeystore keystore -deststoretype PKCS12 -deststorepass `cat keystore.pin` -destkeypass `cat keystore.pin`   Export keystore and Import into truststore   keytool -export -alias server-cert -keystore keystore -storepass `cat keystore.pin` -file server-cert.crt keytool -import -alias server-cert -keystore truststore -storepass `cat keystore.pin` -file server-cert.crt     Docker Image & Container Download and run   sudo docker pull openidentityplatform/opendj sudo docker run -d --name opendj --restart=always -p 389:1389 -p 636:1636 -p 4444:4444 -e BASE_DN=o=opendj -e ROOT_USER_DN=cn=Manager -e ROOT_PASSWORD=Password123456 -e SECRET_VOLUME=/var/secrets/opendj -v /docker/certificates:/var/secrets/opendj:ro openidentityplatform/opendj   After building the container, it MUST be restarted immediately in order for recognizing the new certificates   sudo docker restart opendj   Verify that the certificate is the correct one, execute on the machine that runs the Docker environments: openssl s_client -connect localhost:636 -showcerts   Load the .ldif Use e.g. JXplorer and connect   Select the opendj node LDIF > Import File (my demo breakingbad.ldif is attached to this post) Skip any warnings and messages and continue to import the file   ThingWorx Tomcat If ThingWorx runs in Docker as well, a pre-defined keystore could be copied during image creation. Otherwise connect to the container via commandline: sudo docker exec -it <ThingworxImageName> /bin/sh Tomcat configuration cd /usr/local/openjdk-8/jre/lib/security openssl s_client -connect 10.164.132.9:636 -showcerts Copy the certifcate between BEGIN CERTIFACTE and END CERTIFICATE of above output into opendj.pem, e.g. echo "<cert_goes_here>" > opendj.pem Import the certificate keytool -keystore cacerts -import -alias opendj -file opendj.pem -storepass changeit   ThingWorx Composer As the IP address is used (the hostname is not mapped in Docker container) the certificate must have a SAN containing the IP address     Only works with the TWLDAPExample Directory Service not the ADDS1, because ADDS1 uses hard coded Active Directory queries and structures and therefore does not work with OpenDJ. User ID (cn) must be pre-created in ThingWorx, so the user can login. There is no automatic user creation by the Directory Service. Make sure the Thing is Enabled under General Information   Appendix LDAP Structure for breakingbad.ldif cn=Manager / Password123456 All users with password Password123456    
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