Continuous monitoring of the condition of machines can make operating processes safer and more efficient. Especially for critical components, condition-based or even predictive maintenance is the favoured method nowadays: modern intelligent system components transmit relevant condition parameters to higher-level maintenance management systems. But what about older components that do not have the appropriate diagnostic capabilities? This is where a sophisticated combination of IIoT sensors, gateway units and cloud services offers an ideal solution for retrofitting. In a manufacturing centre for process instrumentation and analytics, this package has proven to be extremely cost-effective and versatile.
In production and process plants, maintenance teams have been striving to increase overall productivity for decades. A key element of this endeavour is the development and implementation of effective maintenance strategies. The traditional approach of running machines and equipment until they fail (known as "run to failure") has proven to be inefficient and costly. A key step in the development of more effective maintenance strategies has been the introduction of Preventive Maintenance (PM). This involves routine maintenance and inspections carried out according to set schedules. Although PM helps to avoid unexpected breakdowns, it sometimes leads to unnecessary maintenance work when the equipment is actually still in good condition.
The next step in the development of efficient maintenance strategies is predictive maintenance (PdM). This involves collecting and analysing data on the condition of the equipment in order to predict when maintenance might be required. The aim of this method is to carry out maintenance when it is actually necessary, based on the current condition of the equipment and not according to a predefined schedule. An important aspect of PdM is Condition-Based Monitoring (CBM), which involves continuously monitoring and analysing the condition of equipment during normal operation. The successful implementation of this condition-based maintenance requires various technologies and resources such as suitable sensors, data transmission and processing systems and specialised analysis software. Without these resources, it is impossible to perform maintenance based on current machine conditions. Retrofitting such technologies is now possible at low cost, especially for rotating or vibrating system components, as the following example illustrates.
Expertise in the production of flowmeters
The Siemens plant in Haguenau, France, which celebrated its 50th anniversary in 2020, employs over 800 people. It specialises in the manufacture of pressure gauges, flowmeters and gas analysers and has been recognised for its innovative approach to digital transformation: Since 2015, the plant has continuously optimised its production through automation, robotics and digitalisation. Production processes can now be simulated in real time and designed more efficiently.
Robert Gerber coordinates maintenance here, while his colleague David Uhrig works as a maintenance planner. "We have made enormous progress in terms of maintenance in recent years," explains Uhrig, who has worked at the Haguenau plant since 1995 as a maintenance technician and then as a maintenance planner. "Our maintenance teams help to improve the efficiency of the plants year on year. We monitor the production systems around the clock and now benefit from diagnostic options that were not available a few years ago." The maintenance strategies vary from plant component to plant component, as Gerber reports: "Every day, we move between the challenges of wanting to and being able to: through criticality analyses, we naturally know what effects the failure of certain plant components can have on operating performance and what we need to pay particular attention to accordingly. Nevertheless, we cannot develop predictive maintenance strategies for all systems because we don't have the condition data."
Appropriate spare parts are available for most critical system parts, but this alone does not protect against system downtime: "Let's take our autoclave as an example," explains Gerber: "All flow meters have a special internal coating that is vulcanised in the autoclave. If it fails, production comes to a standstill. The motor for the blower is particularly critical here, and we have such a motor in stock. However, the problem with a sudden failure is that the fan wheel is attached to the motor axle without a coupling. Despite the spare part, this means two days of downtime and the deployment of specialists."
Condition-based monitoring as a retrofit solution
The two maintenance specialists wanted a condition-based monitoring option for this engine and found what they were looking for in-house: Their employer offers an intelligent system for the continuous monitoring and maintenance of rotating or vibrating machine components. It uses a combination of IIoT sensors and artificial intelligence to continuously record and analyse vibration and temperature data.
The Sitrans MS200 multi-sensors are mounted directly on the relevant system components. They are characterised by their robustness and IP 69-protected housing, which ensures safe operation under industrial conditions. The battery-operated sensors do not need to be wired, as data is transmitted to the Sitrans CC220 gateways via Bluetooth Low Energy (BLE). These gateways collect the data from the multi-sensors and forward it to the cloud application. They are part of a comprehensive internal security system that includes end-to-end encryption from the sensor level to the application level.
