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Maximum availability of drive systems in cement production

IoT Use Case - Innomotics + Rohrdorfer Zement
3 minutes Reading time
3 minutes Reading time

In the cement industry, maximum availability is crucial for continuous production. At Rohrdorfer Zement, there is an additional special feature: the cement works has a power plant that is operated with waste heat. It covers about 30 percent of the electricity needs. Sensors for the Industrial IoT ensure failure-free continuous operation.

The challenge: Availability of the highly loaded drive systems in cement production

Cement is an important building material in civil engineering For this purpose, rock is crushed, burned and grinded with a high energy input. The machines used in this industry are subject to high stress and wear. A failure leads to a production standstill and consequently to considerable costs. Therefore, it is the goal of many manufacturers such as Rohrdorfer Zement to make the drive systems of their machines available to the maximum extent.

This requires regular measurements of the plant parameters. A decisive part of the plant is the rotary kiln. In it, ground limestone and clay are slowly processed into clinker at temperatures of 1450°C. Keeping it running day in, day out is an important task in the company. It is the core of the production process and its waste heat covers around 30 percent of the plant’s electricity needs.

With manual monitoring, technical difficulties often only become apparent when the machine fails. With digital technologies for the Industrial IoT, measurements and fault alarms can be automated. To achieve such a solution, Rohrdorfer’s management contacted Innomotics the manufacturer of the heavy-duty drives used at the company.

The solution: Condition monitoring with sensors and a cloud platform

Drive systems (motors and converters) from the medium- and high-voltage segments are used in grinding mills, crushers, pumps, fans and compressors in industries such as oil, gas, mining, food and beverage, water and wastewater, metals, and cement. To avoid downtime, companies in these industries should maximize the availability of drive systems. A solution for the Industrial IoT that uses data analytics and machine learning to help prevent failures.

The basic principle is simple and suitable for all types of motors and converters: You need sensors for electrical power, temperature and vibration, for example, so that important status data is determined. Many drive systems are already equipped with sensors, but they can easily be retrofitted if necessary. The individual sensor data is transferred via an IoT gateway to the SIDRIVE IQ cloud platform from Siemens. It analyzes the data from the drive systems and uses it for condition monitoring or preventive maintenance. For example, if the sensors register unusual vibrations in a motor, an alarm is triggered and displayed in the cloud dashboard.

Innomotics uses algorithms developed in-house for condition monitoring of its own motors and converters. Schaeffler’s plain and rolling bearings are analyzed with algorithms that are retrieved directly from Schaeffler via the Internet using an API (application programming interface). This increases the flexibility of the solution for all industries that use large drives.

The result: Transparency results in rapid remedial action in the event of faults

The IIoT solution creates transparency to prevent failures. The added value is a kind of insurance benefit: If increased temperatures or increased vibrations occur, companies can react before a serious failure occurs. One of Innomotic’s customers experienced the benefits of IIoT monitoring for themselves some time after the solution was introduced.

The converter of an important machine suddenly showed unusual device parameters one weekend. An automatic alarm from SIDRIVE IQ on an employee’s smartphone quickly caught the malfunction. This allowed technicians to analyze the problem shortly after the alarm and begin repairs. Overall, the company needed less time than in comparable cases

In application

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