Remote Site & Equipment Management 2016 - (Page 20)

Feature Article Applying Remote Monitoring and Predictive Analytics to Satisfy Customers and Tenants While Keeping Costs Down Jonathan Quint, CEO, Ontegrity In this new world of constant connection, businesses can no longer afford to be "off." Users of facilities, networks, equipment, and software, whether they be customers, tenants or employees, demand access to data, applications, funds, games and entertainment 24 hours a day, every single day of the year. It falls to facility and operations managers to keep critical facility infrastructure systems powered on and running efficiently. But how to ensure service continuity for customer satisfaction and/or tenant comfort without breaking the bank? To do so requires predicting and preventing equipment failures, while keeping a lid on operational and energy costs. Fortunately, advances in technology have given companies the tools they need to manage facilities intelligently. Facility and operations teams can use the Internet of Things (IoT) to monitor systems and predictive analytics software to analyze and manage critical facility infrastructure. IoT sensors gather real-time information about equipment performance and environmental conditions. Predictive analytics transforms this big data into actionable information that can be used to identify trends, predict and prevent operational failure, lower energy, labor and operational costs and reduce downtime. The end result is increased customer satisfaction at a manageable price. Research Bears Out Theory Evidence of IoT's usefulness can be found in a 2016 research report by James Brehm & Associates entitled "Redefining the Connected Conversation: IoT Trends, Challenges, and Experiences Survey." The firm reported that 45 percent of respondents used IoT for industrial monitoring and 36 percent for building automation. However, as indicated above, the data provided by IoT systems alone is not enough to enable organizations to predict and prevent problems. The same study bears this out, showing that 87 percent of respondents linked improved data analytics to the increased ROI of IoT projects. The Following are three practical examples of how IoT applications combining remote monitoring with predictive analytics can help organizations achieve operational continuity while minimizing costs. HVAC System for Efficient, Continuous Functionality One example of a real-time remote monitoring application with predictive analytics is an HVAC monitoring and control system that collects actual operating-condition data (e.g., line pressure, temperature and humidity) and processes it through analytical models to produce information critical to technicians, facility and operations managers, and capital investment planners. Sensors, which may already be embedded in the equipment or can be easily deployed, collect raw data that is ultimately converted into maintenance tasks to improve performance and unit longevity. Analysis and intelligence recognize that units are running in one of four operational states: (1) functioning as they should, (2) functioning, but would benefit from specifically targeted maintenance activities, (3) malfunctioning and running as a single unit, or (4) not performing optimally in the environment (singly, or in combination with other HVAC units). Data-driven maintenance and repairs lead to increased mean time between failure (MTBF) and longer equipment life. A predictive analytics system also helps an organization understand and manage energy usage, ensuring that equipment is running within predetermined temperature parameters and avoiding situations where equipment runs unnecessarily. For example, if one HVAC unit is operating in heating mode while another runs in cooling mode, a facility or site can appear to be normal. With remote monitoring and predictive analytics, the facility or operations manager can determine the reason why the HVACs are running almost continuously, rather than cycling on for just a few hours a day, and make timely and cost-saving repairs. Automatically generated alarms alert managers and technicians to predefined abnormal conditions. With 24/7/365 data access via the Web, these professionals can efficiently troubleshoot and set priorities for repairs. Moreover, an advanced, prescriptive 20 www.RemoteMagazine.com http://www.RemoteMagazine.com

Table of Contents for the Digital Edition of Remote Site & Equipment Management 2016

Editor's Choice
Integrating Local HMI with the Cloud
Managing Distributed Energy Resources with IoT and Cloud Technologies
Three Considerations for M2M/IoT Connectivity
Creating Value from IIoT Data
Wireless Sensor Networks - Applications in Oil & Gas
Applying Remote Monitoring & Predictive Analytics to Satisfy Customers While Keeping Costs Down
M2M & IoT Products
Industry News

Remote Site & Equipment Management 2016