Philippines | Thailand

Industrial IoT

IoT is nothing fundamentally new as an invention. It has been there for ages in limited avatar. The closest or easiest examples to pick up will be various equipment’s in thermal power plants monitored and controlled through control systems; Centralized traffic control systems changing signal times based on volume of traffic or capturing shots of traffic law violation. Certainly these use cases were circumventing on industrial or large scale set ups with connections limited to LAN or WAN in the past.

The newer version is to pick up to reach Internet and scale from industries to fields to homes to handheld devices, as we all know. While business pragmatic experts feel that as of today IoT = Smart phones (meaning the scalability and realization of IoT ) in reality, now it is time for integrated industrial and social change for tomorrow to make it more scalable and useful. Look at RFID wave which was touted as big wave 8 years ago, it never picked up momentum because of limited industrial drive to commercialize it at an affordable cost, funding on a long term to drive large scale innovation as it takes years to bring changes and social risk or belief of snatching the privacy.

Why IoT, Why Now?
Modern IoT technology offers multiple advantages and capabilities not easily available to remote diagnostic devices of past decades. Wireless TCP/IP communication is available virtually anywhere around the globe at very low cost, and cloud services offer globally distributed storage and computing resources. Essentially, the entire communication infrastructure is owned by third parties that manage access, devices and data security, allowing service organizations to focus on the content rather than on setting up and manage the conduits.
Not only is the cost of setting up and managing the communication dropping, but also the cost of sensors, data acquisition and communication hardware continues to drop, making instrumentation and communication affordable.

Practically every piece of equipment is becoming a smart data-collecting node in an always-connected network. Secure connectivity and data exchange are no longer a challenge; they are a commodity.

Predictive Diagnostics
Predictive diagnostics models, machine learning and other techniques that attempt to extract knowledge from complex machine data and provide proactive service advice are difficult to build and maintain. One of the more interesting and complex challenges stems from the broad variability in the installed equipment, even among similar pieces of equipment. A couple of examples will illustrate this point.

Consider a fleet of trucks rolling off the assembly line and delivered to different operations. Some of these trucks are used for long distance cargo hauling, covering great distances cruising long hours at highway speed. Other trucks make short trips, some in urban areas and frequently in start-stop traffic. Over time, the different traffic conditions, cargo loads and even the operator’s driving patterns cause these trucks to wear differently. Add to those the inconsistent service and maintenance practices that often do not follow the manufacturer’s recommendations, and the trucks are no longer close facsimiles of the original truck that was used as the model for the predictive data analysis.

Building reliable failure prediction models for highly engineered assets has proven difficult. These models require large data sets that are continually updated to reflect that ongoing changes caused by built-in variability, wear and tear, and configuration changes over the life of these machine.
Manufacturing industry is one of the early adopters of IoT. Philippines and Thailand have already invested USD27.60M and USD 28.44M by 2014 in manufacturing. This number is expected to rise to USD144.06M and USD 327.87M respectively by 2020.

At Asia IoT Business Platform, we focus on bringing together the best-in-case examples of enterprise IoT, and localising the IoT discussion for the needs of the country. Manufacturing is one of the key focus areas for Philippines and Thailand. For the original article click here and for more informative articles on Iot visit Talha at Linkedin.

Sue Yuin Ho

Dec 14, 2015

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