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ThingWorx Analytics enables enterprises to find the true value in their IoT data – to learn from past data, understand and predict the future, and make decisions that will enhance outcomes.

Watch
Monitor edge devices and provide real-time pattern and anomaly detection on real-time data streams.

Predict
Provide automated predictive modeling and operationalization for a variety of different outcomes. Pattern and anomaly detection on real-time data streams.

Adapt
Deliver prescriptive and simulative intelligence that identifies factors that contribute to an outcome and explains how to change a predicted outcome.

Optimize
Automatically operationalize and maintain predictive and simulative intelligence to deliver to end-users.
ThingWorx Analytics is an integrated capability of the ThingWorx IoT technology platform that enables developers to quickly and easily add real-time pattern & anomaly detection, predictive analytics and simulation to the solutions they build.

ThingWatcher
Finds anomalies from edge devices in real-time. Automatically observes and learns the normal state pattern for every device or sensor. It then monitors each for anomalies and delivers real-time alerts to end users.

ThingPredictor
Automatically predicts future outcomes. Subscribes “Things” to relevant outcome-based predictions (time to failure, errors per hour, etc). Displays results in context to end users through any ThingWorx powered solution or experience.
*Requires ThingWorx Analytics Server.

ThingOptimizer
Improve future performance and results with automated prescriptions and simulations. ThingOptimizer automatically identifies the key factors causing a given outcome.
*Requires ThingWorx Analytics Server

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  • SUPPLIER
  • ThingWorx (PTC)
    The ThingWorx IoT Technology Platform. One Platform. Limitless Possibilities. ThingWorx is the only enterprise-ready technology platform that enables innovators to rapidly develop and deploy smart, connected solutions for the Internet of Things. Build Fast Connectivity and development tools made for IoT enable developers to quickly create, test and deploy solutions faster than ever thought possible. Build Smart Integrated capabilities of the platform enable developers to create more feature-rich solutions in a fraction of the time of other platforms. Build for Enterprises Developers quickly and easily create IoT solutions that are scalable, secure, and meet the needs of the largest of enterprises.
  • SNAPSHOT
  • Open website
  • Application Industries
  • Equipment & Machinery
    Mining
  • Application Functions
  • Discrete Manufacturing
    Maintenance
    Product Development
    Quality Assurance
  • USE CASES
  • Continuous Emission Monitoring Systems (CEMS)
    Continuous emission monitoring systems (CEMS) are used to monitor flue gas for oxygen, carbon monoxide and carbon dioxide to provide information for combustion control in industrial settings.For example, operators use gas detection devices to monitor and prevent gas leaks. Detection of gas levels and leakages in industrial environments, surroundings of chemical factories and inside mines involves significant costs and is of crucial importance for operating safety. While preventive maintenance could provide for another IIoT solution, at remote sites it is costly and sometimes ineffective. 
    Track and Trace for Industrial Tools & Assets
    Track and trace for industrial tools refer to systems capable of recognizing and reporting the location and status of tools in a facility. Today's production of industrial and consumer goods requires exacting work. Precise application of pressure or torque is required in many industries and operator errors can cause costly defects. Track and trace technology can improve production safety, quality, and productivity.The goal of ‘Track and Trace’ is to manage handheld power tools in manufacturing and maintenance environments more efficiently.Asset tracking is currently done via barcode and a variety of manual steps in most cases. However, new solutions leveraging smart tags, near-field communication (NFC), and RFID are coming to market to globally track all varieties of objects in real time. 
    Process Control & Optimization (PCO)
    Process Control and Optimization (PCO) is the discipline of adjusting a process to maintain or optimize a specified set of parameters without violating process constraints.The PCO market is being driven by rising demand for energy efficient production processes, safety and security concerns, and the development of IoT systems that can reliably predict process deviations.Fundamentally, there are three parameters that can be adjusted to affect optimal performance:- Equipment optimizationThe first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks.- Operating proceduresOperating procedures may vary widely from person-to-person or from shift-to-shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual.- Control optimizationIn a typical processing plant, such as a chemical plant or oil refinery, there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important. It has been well documented that over 35% of control loops typically have problems. The process of continuously monitoring and optimizing the entire plant is sometimes called performance supervision.
    Factory Operations Visibility & Intelligence
    Visualizing factory operations data is a challenge for many manufacturers today. One of the IIoT initiatives some manufacturers are pursuing today is providing real-time visibility in factory operations and the health of machines. The goal is to improve manufacturing efficiency. The challenge is in combining and correlating diverse data sources that greatly vary in nature, origin, and life cycle.Factory Operations Visibility and Intelligence (FOVI) is designed to collect sensor data generated on the factory floor, production-equipment logs, production plans and statistics, operator information, and to integrate all this and other related information in the cloud. In this way, it can be used to bring visibility to production facilities, analyze and predict outcomes, and support better decisions for improvements.  
    Precision Farming
    Precision farming enables farmers to increase production (yield), lower their operational costs and economize their applications of chemicals and fertilizers. Precision Conservation Management (PCM) focuses on improving crop yield through the analysis of real-time data from a variety of environmental sensors and other data sources located in commercial crop fields or throughout the enterprise.The five core components or processes of precision farming are: measuring variability, analyzing variability, decision-making, differential actions, assessment of results and measuring. 
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