“The devil is in the details, but then, so is our salvation”
There are many industrial applications for the Internet of Things (IoT) technology to deliver useful results and to provide feedback to the users. Now, we are seeing new enhancements to the standard workflows that provide even grander and more meaningful outcomes. These enhancements include:
- Granular micro feedback loops
- Non Destructive Testing (NDT)
- Non Destructive Evaluation (NDE)
Granular Micro Feedback Loops – These systems are found in large scale, complex systems, such as a next generation jetliners from Airbus (designed, engineered, and built by Bombardier) that use many tens of thousands of sensors in the wings and engines. In the Airbus A220 aircraft, there are 5,000 sensors in each wing span, and 5,000 sensors in each of the Pratt & Whitney Geared Turbofan Engines, for a total of over 20,000 sensors before we even get inside the airplane’s cabin.
The wing sensors detect the minutiae of flex and twist in the wing induced by the four principle forces of drag, gravity, lift, and thrust. The data from these sensors is analyzed by a family of computers. Flight decisions are made by these computers on a very granular level to micro manage the engines. The changes are so small that they largely go unnoticed. The pilots supervise and can override these changes. For example, the fuel flow is dynamically adjusted in milliseconds to control thrust to function in collaboration with the three other forces of flight – drag, gravity, and lift. It is a delicate dance between the two intensely sensor laden wing / engine partners. Each acting and reacting to the movements of the other. It is the acute granularity that adds up to realize major fuel savings far outperforming the cost per passenger seat / mile for the operation of Airbus’ major competitor, Boeing who is offering the Boeing 737 MAX (rumoured to soon return to the air after lethal software defects in the autopilot systems).
Non Destructive Testing (NDT) – The field of Nondestructive Testing (NDT) is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. NDT technicians and engineers define and implement tests that locate and characterize material conditions and flaws that might otherwise cause planes to crash, reactors to fail, trains to derail, pipelines to burst, and a variety of less visible, but equally troubling events.
Systems are now designed with IoT sensors transparently woven into the products. Regardless if it is a robot on a factory floor, a bridge crossing a river, or a tractor trailer speeding along a highway, sensors are seamlessly embedded into everything to provide real-time diagnostics, alarm for anomalies, and log events between inspections.
These tests are performed in a manner that does not affect the future usefulness of the object or material. In other words, NDT allows parts and material to be inspected and measured without damaging them. Because it allows inspection without interfering with a product’s final use, NDT provides an excellent balance between quality control and cost effectiveness. Generally speaking, NDT applies to industrial inspections. The technologies that are used in NDT are similar to those used in the medical industry, but nonliving objects are the subjects of the inspections.
Non Destructive Evaluation (NDE) – Nondestructive evaluation (NDE) is a term that is often used interchangeably with NDT. However, technically, NDE is used to describe measurements that are more quantitative in nature. For example, an NDE method would not only locate a defect, but it would also be used to measure something about that defect such as its size, shape, and orientation. NDE may be used to determine material properties, such as fracture toughness, formability, and other physical characteristics.
These levels of advancing IoT innovation with granular insights can only be realized with collaborative developments in the power of compute, storage, analytics, artificial intelligence, and edge computing. All of these platform resources make sense of the data pulled from these micro, NDT, and NDE systems. These platforms transform the data to information, which is aggregated into knowledge and deeper understanding of the systems themselves and the products being made by these systems.
Ultimately, these large scale live sensor grid readings are combined with legacy data from past operations of the same systems to decide upon trends, patterns, and aberrations, all within the confines of the MAX / MIN limitations for optimal performance.
External data is acquired to correlate with the live and legacy data records. From these three sources of data, new derived data is realized to bring even more clarity to the workflows and the governance guiding the process flows.
It is only when we can get ahead of these processes and understand the stability and reliability of our systems can we truly drive costs out, improve repeatability and consistency, and reach for higher process performance levels that were once dreamed to be unimaginable before the advent of IoT.
If knowledge is power, and we can properly harness this power, then we can evolve towards wisdom and proactive behaviours. We need to move away from older loosely coupled, reactive actions, which are delayed typical post of the operations – they are reflective.
Unknown. (2020). What is NDT? Cornell Center for Materials Research, Cornell University Inc. Retrieved on September 30, 2020 from, http://www.ccmr.cornell.edu/wp-content/…/Non-DestructiveTestingReading.pdf
About the Author:
Michael Martin has more than 35 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He offers his services on a contracting basis. Over the past 15 years with IBM, he has worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX). Martin currently serves on the Board of Directors for TeraGo Inc (TGO: TSX) and previously served on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now OntarioTech University] and on the Board of Advisers of five different Colleges in Ontario. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section. He holds three master’s degrees, in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and five certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has earned 20 badges in next generation MOOC continuous education in IoT, Cloud, AI and Cognitive systems, Blockchain, Agile, Big Data, Design Thinking, Security, and more.