The Netherlands are well-known for their inland waterways, canals, sluices and of course port activities. The Dutch Ministry of Infrastructure indicates that there are thousands of buoys and fixed items in and near water environments that would profit from IoT monitoring. One of the problems with buoys for example, is that they get hit by ships and the anchor cable breaks. Without connectivity, it takes quite some time to find out that something has happened with that buoy. Not to mention the costs of renting a boat to go to the buoy to fix it. Another important issue, is that there is no real-time monitoring of the buoys at this moment. Only by physically visiting the object on the water, one gains insight in its status.

To reduce maintenance costs and delay-causing failures for Deutsche Bahn. They need manual measurements by a position measurement system based on custom-made MEMS sensor clusters, which allow autonomous and continuous monitoring with wireless data transmission and long battery. They were looking for data pre-processing solution in the sensor and machine learning algorithms in the cloud so as to detect critical wear.

London Underground serves 1.7 billion passengers per year and the Victoria Line accounts for 213 million of those journeys. The line carries 89.1 million passengers per year in the peak service, offering the most intensive service on the underground network. Over the past eight years, a £1 billion investment programme upgraded and replaced the Victoria Line’s rolling stock and signaling and control systems to deliver a service capable of running more than 33 trains per hour. The new signalling system uses 385 Jointless Track Circuits (JTCs) to detect train position, maintain safe train separation and deliver train headways capable of meeting an extremely demanding timetable. Track circuits are the sole means of train detection and play a critical role in the safe and reliable operation of the railway; however, no provision was made for any condition monitoring during the design and installation. Because of the critical nature of the asset, a failed track circuit has a major impact on the service and constitutes the biggest cause of passenger disbenefit on the Victoria Line, amounting to £1.5 million since their introduction (London Underground CuPID database for Track Circuit failures since 2012). The Victoria Line Condition Monitoring Team, made up of six professional engineers with rail, software, electrical, mechanical, network and engineering backgrounds, delivered the solution. National Instruments Silver Alliance Partner Simplicity AI supported the project by providing additional software consulting services. We used the company’s enormous breadth of expertise to deliver the system onto an operational railway within one year of the concept design. The scope of this project consisted of designing, integrating and installing an intelligent remote condition monitoring system that could perform real-time analysis of voltage and frequency for all 385 JTCs across a 45 km of deep tube railway to predict and prevent failures and subsequent loss of passenger service. We took advantage of the accuracy, reliability and flexibility of NI hardware and software to implement an innovative system to reduce the lost customer hours experienced on the Victoria Line. The system is forecast to reduce lost customer hours by 39,000 per year—an estimated £350,000 savings per year in passenger disbenefit.

Field engineers and service teams often lack data and digital insights needed to assess, troubleshoot, and determine work scope for the large industrial assets in performing corrective and preventative maintenance activities. QA engineers many times need to understand why a particular problem in the part is happening recurrently or why parts from suppliers don’t stack up well in the assemblies due to mismatch. The root cause is usually hidden in design, manufacturing processes, supply chain logistics or production planning. But without the right data and digital insights, it's hard to pinpoint. GOAL To collect information in the design, manufacturing, service, supply-chain setup and provide access to and intelligent analytics for industrial manufacturing and performance data, to identify the root cause easier. Such insights can improve not only service and owner/operator productivity, but also provide critical feedback to the design engineering and manufacturing operations teams for continuous improvement.

Problem: Inefficient vehicle fleet management hinders business efficiency, employee productivity, and revenue growth opportunities. - Difficult to manage fleet operations, particularly in tracking their daily activities- Challenge for business owners to monitor their drivers’ behavior and daily productivity. Business owners need to ensure that their drivers are following business rules and policies. 

5678 SMRT needed a fast, modern, scalable web reporting solution that could be accessed by numerous operators over many and diverse divisions. They wanted to extend and enhance their current HMI system, in which they had invested significant time and money, without having to replace it.

A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.

The O&M division of an aerospace and global security company was using spreadsheets to manually track more than 3,000 assets assigned to students and staff. Maintaining audit trails for this high volume of equipment became increasingly time-consuming and challenging. The chore involved knowing precisely what equipment was on hand, what had been issued, its location and the name of the custodial owner of each item. Every aspect of this task was carried owner of each item. Every aspect of this task was carried out by individuals with spreadsheets. Manually documenting the full lifecycle of each asset added to the burden. This included tracking maintenance requirements and records, incidents and damages, repairs, calibrations, depreciation, and end-of-life data.

The client needed a new solution based on a fleet management system to track its vehicles’ locations around Europe and provide real-time analytics that allowed a more efficient exploitation of its valuable fleet and personnel resources and calculation of the amount of fees to be paid by different types of vehicles based on route distances. The main challenge was to boost the system’s performance, enable multi-tenant architecture, support the program in hosted/on-premise mode and provide availability in multiple languages.