Before working with Ayla Networks, Ozner was already using cloud connectivity to identify and solve water-filtration system malfunctions as well as to monitor filter cartridges for replacements.But, in June 2015, Ozner executives talked with Ayla about how the company might further improve its water systems with IoT technology. They liked what they heard from Ayla, but the executives needed to be sure that Ayla’s Agile IoT Platform provided the security and reliability Ozner required.

For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.

The customer prides itself on excellent engineering and customer centric philosophy, allowing its customer’s minds to be at ease and not worry about machine failure. They can easily deliver the excellent maintenance services to their customers, but there are some processes that can be automated to deliver less downtime for the customer and more efficient maintenance schedules.

It is not a matter if a hydraulic hose will fail, but a matter of when. When hydraulic hoses fail on a garbage truck or on heavy machinery, Eaton's customers spend millions of dollars on hydraulic fluid cleanup, fines, remote service and medical costs that result from injuries.

Manufacturing plants are running at a much higher capacity utilization than ever before. Often, it is a 24 hour a day, seven days a week operation. With downtime costing plants up to US$20,000 a minute, they cannot afford disruption to their processes. In fact, a single occurrence can cost a plant upwards of US$2 million.FANUC was struggling with lack of visibility into how their customers were leveraging FANUC equipment on the factory floor. The only insight was gained after a problem had already occurred resulting in costly downtime for the customer.

Oseco were completely new to Industry 4.0, Oseco needed to find a lean and quick method for successfully implementing condition monitoring.

Common paper breaks consequently lead up to 60 minutes of downtime, delaying a potential $10K per hour of production value process. Thus, defective products cause financial and damage company's reputation. Improving quality and reducing defect rates can generate millions of dollars of revenue per year for your company.

Objectives • Create an innovative IT environment that supports the move toward a solution-provider business model • Enhance existing business processes and leverage the power of Big Data and predictive maintenance to become more proactive, customer oriented, and competitive • Leverage the SAP HANA® platform to transform and simplify the entire SAP® solution landscape

In order to scale up operations, loT Systems’ client needed a system to monitor vacuum pumps and provide managers with actionable data at near real-time speeds from anywhere, at any time, and on any device. The vacuum pumps are part of vertical furnaces that prepare semiconductor wafers at precise temperatures and pressures according to their clients’ exact specifications. If a pump was about to fail and a manager did not see the alarm, it could lead to a scrap event, costing the client revenue, delaying production with unplanned downtime, and increasing overall manufacturing costs. Managers could not see alarms in real time unless they physically walked around the floor, making predictive maintenance and preventing scrap events harder as the client scaled upwards.

ArcelorMittal’s rotating assets often operate in harsh environments. A conveyor at the company’s hot strip mill in Ghent, Belgium moves plates of sizzling hot steel along the production process. In conditions like these, traditional proximity-based technologies like vibration and acoustic analysis fail: the sensors can’t handle the high temperatures.“In the steel industry, assets frequently operate in conditions that are not hospitable to sensitive sensor technologies,” says Andy Roegis, ArcelorMittal’s industrial digitalization manager for northern Europe. “The conveyor on our hot strip mill is a critical part of the production process, but it’s virtually impossible to use manual or vibration-based techniques to assess its condition.”

Leica Microsystems attributes its success to providing innovative products and superior customer service. To extend its leadership position, the company began exploring a more proactive service approach for its line of confocal microscopes and tissue processors. The Leica Microsystems project team began searching for a global software that would allow for the shift from a reactive to proactive service company. Their initiative focused on downtime avoidance and the prediction of potential problems across the globe, targeting issue prevention. As a result, customers would not only benefit from minimal product downtime, but from faster service and increased productivity. To obtain approval and funding for the initiative, the team would need to prove to management that this service strategy shift would result in optimized instrument uptime and reduced costs of service.

WIN-911’s partner product ALERT is a key element in the Supervisory Control and Data Acquisition (SCADA) system “FabView” from Air Liquide. Air Liquide is the second largest supplier of industrial gasses in the world. This SCADA alarm notification system is specifically designed to monitor, among other things, the distribution of gas in a semiconductor manufacturing plant located in Dresden Germany. Like most operations of its type, this facility can’t afford much downtime in its distribution facility. If ALERT detects a leak in a pipeline, the system evaluates how severe the leak is and transfers the data back to the central site or home office. Once the information is back in the main office, the SCADA alert system then transcribes the data into understandable messages to which employees can respond appropriately.

Data management system versiondog, an indispensable instrument in operations engineering at Warsteiner. Preventive maintenance has long been the norm at the Warsteiner Brewery. And yet, unplanned maintenance activity can still occur. It is therefore of great importance that the latest update version for each and every PLC be stored centrally. In this industry, there is no time to waste trying to conduct a search.

During critical junction time, multiple decision must be made without hesitation and fear. Companies are required to make quick repairs to pieces of gear. Solution is needed to complete challenges during those times.

Companies are facing greater challenges than ever before when it comes to making sure their cooling equipment operates at maximum efficiency. One of the challenges is the need to understand how equipment is performing to optimize their use, their health and to anticipate issues and failures. Having an HVAC service engineer who continuously monitors the chiller is unrealistic.

The client is looking to generate higher value from the elevator data that is collected. Sensors and data include:Laser - position of the elevator carLuminosity - Level of light within the carUltrasound - Open shaft doorVibration - Acceleration of the car; vibration of the carMicrophones - abnormal sounds of the carAtmospheric Pressure - Air pressureHumidity - Shaft humidityTemperature - Shaft temperature 

A stripper well or marginal well is an oil or gas well that is nearing the end of its economically useful life. In the U.S., oil wells are generally classified as stripper wells when they produce 10 to 15 barrels per day or less for any 12-month period. These wells account for approximately 18% of the U.S. production. The key ask was to design a solution that would connect these wells often located in remote locations and collect information about their performance and operating conditions. 

Machine uptime is one of the most vital performance factors for electric rotating machinery. In times when an hour of downtime can equate to thousands of dollars in losses, securing predictability turns into a high priority for all industrial businesses. Manufacturers operate in an extremely volatile environment, thus avoiding unplanned downtime becomes critical for achieving desired business outcomes. Predictive maintenance is no longer a nice-to-have but a necessity to survive and thrive in unfavourable conditions. Start from the basics. Making machines perform better means, first and foremost, understanding how the machine works, extracting relevant data, and gaining meaningful insights into ongoing processes. The power of the machine lies in utilizing its full potential.

KONE already provided traditional maintenance services for its more than 400,000 building owner and facilities management customers, but it sought cloud-based analytics technology to capture and use the vast amount of data generated by its elevator and escalator equipment worldwide to transform its service offerings. “We knew that digitalization was changing the industry, and we wanted to become a forerunner, not a follower in this development,” says Markus Huuskonen, the Director of Maintenance Processes and Connected Services at KONE.

A major European aircraft component supplier encountered this challenge first-hand. A mission-critical, programmable milling machine failed, halting the organization’s production process. Despite the customer team’s expertise, the problem proved challenging to diagnose. At first, it appeared the downtime resulted from a damaged spindle, the most complicated part of the milling machine. However, a costly and time-consuming spindle replacement did not correct the situation. The team was forced to perform an extensive system evaluation to identify the culprit.

The client wanted to reduce downtime and production losses by effectively prioritizing maintenance activities and proactively replacing components before failure.

Like many organizations, Anaren had a homegrown work order application that had basic asset management functionality. “It was menu driven, so quite cumbersome,” explained Bill, “reporting was limited and it still relied heavily on paper transactions and records. We looked at our business needs going forward and decided this was one area that could be modernized.” On launching the Manufacturing CMMS project, Bill, the business analyst of the company identified three major areas for improvement:1. Improve efficiency by eliminating paper.2. Improve the control of preventive maintenance. 3. Improve inventory management.