Suppliers Germany AUVESY-MDT
SUPPLIER MANAGED
AUVESY-MDT Logo

AUVESY-MDT

We secure the world's automation
Germany
Landau in der Pfalz
2007
Private
$10-100m
51 - 200
Open website

AUVESY-MDT is a solid medium-sized enterprise based in Rhineland-Palatinate, Germany. The software octoplant offers worldwide a secure solution for version control and data management in industrial automation. This leading version control software is the basis to heighten production efficiency by reducing errors and downtime; and monitor and control automation projects.

傲晖数据软件(南京)有限公司是AUVESY-MDT在中国的全资子公司,与西门子、施耐德、三菱、微软等合作伙伴携手已为全球50多个国家安装3200多套软件。AUVESY-MDT研发的versiondog/octoplant用来统一管理各种自动化设备(如:PLC/机器人/HMI/CNC/相机/压机/拧紧机/工控机/马达驱动等),且不受制造商的限制,实现灾难恢复以提高运营效率,并减轻网络安全攻击,保持生产连续不间断。集团总部位于德国兰道。

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When AUVESY-MDT talks about the Internet of Things (IoT), they are not just talking about smart factories, but also smart products. The combination of the two means that the production of small batches and one-off products becomes practical even in highly automated facilities. versiondog is the certified enterprise solution for software and data management in the automated production. With versiondog, customers can make automated backups of their data and at the same time have a powerful versioning system for project data and documentation, including integrated lifecycle management. versiondog interprets data and programs of the different automated components and automates the administration of the flood of data and versions, which accrues in every production. versiondog does not only administrate all this project data but controls, analyses and monitors all changes in the devices and that automatically. The current producing program, the used parameters and set points as well as the clear version allocation are available at any time.

octoplant是AUVESY-MDT研发的一款用于自动化生产中程序备份和版本管理的企业级解决方案,统一管理各种自动化设备(如:PLC、DCS、SCADA、机器人、HMI、CNC、相机、压机、拧紧枪、工控机、交换机、路由器、防护墙、马达驱动等),通过对设备控制系统程序、参数进行自动备份、版本管理和软件状态记录、BI展示分析,确保制造过程的可视化、完全可追溯性且不受原制造商的限制,实现快速灾难恢复以提高运营效率,并减轻网络安全攻击,保持生产连续不间断。

Octoplant创新性地为工厂层的生产设施设备提供了一个中央数据管理系统,只需点击一个按钮,即可保护您的数据、质量证明、项目文档和变更管理。

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Tesla, Space-X, CERN, Daimler, GM, Ford, BMW, Audi, Volkswagen, Volvo, Porsche, Bosch, Continental, Mann & Hummel, ZF, Brose, Nestle, Coca Cola, Kraftfood, Mars, Airbus, Benteler, Eisenmann, Dürr, Roche, Boehringer Ingelheim, Fresenius, Sun Chemical, RWE, Vattenfall

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AUVESY-MDT is a provider of Industrial IoT infrastructure as a service (iaas), platform as a service (paas), application infrastructure and middleware, functional applications, and sensors technologies, and also active in the automotive, equipment and machinery, food and beverage, metals, pharmaceuticals, and utilities industries.
Technologies
Application Infrastructure & Middleware
Data Visualization
Database Management & Storage
Sensors
Level Sensors
Pressure Sensors
Platform as a Service (PaaS)
Data Management Platforms
Infrastructure as a Service (IaaS)
Backup & Recovery
Functional Applications
Remote Monitoring & Control Systems
Use Cases
Machine Condition Monitoring
Remote Control
Water Utility Management
Functions
Business Operation
Logistics & Transportation
Maintenance
Process Manufacturing
Industries
Automotive
Equipment & Machinery
Food & Beverage
Metals
Pharmaceuticals
Utilities
Services
Training
AUVESY-MDT’s Technology Stack maps AUVESY-MDT’s participation in the infrastructure as a service (iaas), platform as a service (paas), application infrastructure and middleware, functional applications, and sensors IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies13
New Business Models in Maintenance
New Business Models in Maintenance
Everything that can be automated will be automated, and it is up to us, as people, to learn how to adjust to this development With the advent of the networking of processes and the Industrial Internet of Things, IT has further cemented its place in the production facilities of modern enterprises and is now set to revolutionise the way in which maintenance is approached. The Chamber of Industry and Commerce has its hands full when it comes to making sure that vocational and training concepts both accompany and keep up with these developments. Many employees are anxious, believing that the ongoing digitalisation of the world of work will result in greater job insecurity; a general misconception which regrettably continues to abound. The fact that digitalisation is set to provide both new opportunities and challenges, and that not every workplace is in danger, is often conveniently overlooked in the surrounding hype. It’s as if history is due to repeat itself every time any major industrial revolution occurs. Production workers begin to fear for their jobs and fear of change in the workplace remains high. Nevertheless, production is subject to constant change and we must all learn to adapt. Today, it is IT, in the wake of the IIoT, which stands to replace traditional rosters and blackboards. What’s more, the advent of employees directly communicating with machines via speech in order to reset them is also fast approaching. Voice-control has already gained general acceptance, but an even greater degree of trust in technology is required. If no changes are made to the way you work, the sudden advent of digitalisation may make it appear as though things are out of place or even missing. That isn’t to suggest that there was a time in which IT didn’t exist in the realm of production; such a statement wouldn’t be true, as evidenced by the fact that, in times past, maintenance staff spent an inordinate amount of time making their rounds accompanied by a programmer’s notebook, which had different editors to program components and helped to facilitate communication between human and machine. Nevertheless, the fact remains that the networking of processes continues to generate considerable uncertainty. Customised production The introduction of online marketing has resulted in a large percentage of industrial production being tailored to fit the customer. Affiliate marketing allows you to find out much more about your customers, their behaviour as consumers, and the underlying motives that drive their decision making. Thus, in certain sectors, it no longer makes sense to produce products, place them in storage units, and then wait until they are sold off. Instead, it is becoming the norm to make predictions according to customer decisions or trends. By using information gathered from CRM systems, customer feedback and digital sales statistics, it is possible to determine the colours, form, and features that a customer would desire a future product to have. It is also possible to produce products in such a way that the targeted customer immediately purchases them, thus resolving the need to store the products away until such a time as they are sold. Customised production places high demands on maintenance. Common topics that are frequently brought up in addition to classical and continual improvement processes include: - Preventive Maintenance - Corrective Maintenance - Condition-related maintenance The umbrella term ‘predictive maintenance’ is often used to encompass the topics listed above. Predictive maintenance is a strategy that is based on real-time data taken from production. It permits you to quickly recognise and respond to problems or results which were not visible in the past, but which are now, thanks to new advances in technology (e.g. condition monitoring), immediately detectable. What does the process of networking involve? When surveying a newly digitalised production hall for the first time, the first difference that one notices is that a specific IP address has been assigned to all automated devices connected to the network, which allows for data to be received and sent. These automated devices can be completely different from each other. It does not matter. What does matter (where plant or machine controllers are involved) is the PLC (programmable logic controller). A digital network topology looks as such: sensors, drives, and actuators move things around; robots weld, solder, press and pack; and HMI/SCADA systems supervise the processes. Then there are presses, drills, machine tools, milling processes, and much more. Generally, there is a different editor used to program each type of automated device type. There are very few uniform standards when it comes to software editors and thus automation engineers cannot use the same software to program a wide range of devices. Visual programming languages in DIN EN 61131-3 are regulated, however, each editor has its own special features and they are seldom compatible. Editors continue to be further developed if only for the purpose of continuously updating them to support current operating systems. Software developers are eager to offer their customers ongoing updates, the reason for which lies in the fact that customers do not have any reason to pay for software editors that have reached the end of their development. They will only pay for new developments. For maintenance staff, this trend necessitates them to undergo constant further training in order to understand and implement the latest functions and features brought out by the software developer. In that regard, it is interesting to note that, even as the number of people present in the production hall continues to decline, the number of maintenance staff continues to grow. This stands in stark contrast to the hype about the human factor becoming an obsolete element when it comes to production; on the contrary, the human factor will continue to grow in importance, especially when it comes to fixing unplanned malfunctions and errors that may occur to the complex machines and systems during production. All visions involving the future state of digital production thus have one thing in common and that is the fact that people will continue to play a vital role: the ability to understand the complex connections between numerous machines, controllers and programs, will continue to be a sure-fire guarantee of success.
Process Control System Support
Process Control System Support
In many automated production facilities, changes are made to SIMATIC PCS 7 projects on a daily basis, with individual processes often optimised by multiple workers due to shift changes. Documentation is key here, as this keeps workers informed about why a change was made. Furthermore, SIMATIC PCS 7 installations are generally used in locations where documentation is required for audits and certification. The ability to track changes between two software projects is not only an invaluable aid during shift changes, but also when searching for errors or optimising a PCS 7 installation. Every change made to the system is labour-intensive and time-consuming. Moreover, there is also the risk that errors may occur. If a change is saved in the project, then the old version is lost unless a backup copy was created in advance. If no backup was created, it will no longer be possible to return to the previous state if and when programming errors occur. Each backup denotes a version used by the SIMATIC PCS 7 system to operate an installation. To correctly interpret a version, information is required on WHO changed WHAT, WHERE, WHEN and WHY: - Who created the version/who is responsible for the version? - Who released the version? - What was changed in the version i.e. in which block or module of the SIMATIC PCS 7 installation were the changes made? - When was the version created? Is this the latest version or is there a more recent version? - Why were the changes made to the version? If they are part of a regular maintenance cycle, then is the aim to fix an error or to improve production processes? - Is this particular version also the version currently being used in production? The fact that SIMATIC PCS 7 projects use extremely large quantities of data complicates the situation even further, and it can take a long time to load and save information as a result. Without a sustainable strategy for operating a SIMATIC PCS 7 installation, searching for the right software version can become extremely time-consuming and the installation may run inefficiently as a result.
Versiondog Comes for Coffee
Versiondog Comes for Coffee
“Well before it went live, we had worked out a clear plan for exactly how we were going to use the new versiondog versioning and data management software from AUVESY,” says Michael Mrugalla, who works in process automation at the Mainz plant. “We also had to think about what backups really meant for us. With all our field devices, control programs, drive systems, programming languages, file formats and software applications, we needed to know precisely what we have to back up in case a breakdown (e.g. a power outage) stops production. Because the whole point of making a backup is to be able to recover data quickly and easily when something goes wrong and continue working as if nothing had happened. But that means more than simply restarting production, it also means we need to be able to pick up where we left off with our ongoing process maintenance and optimisation.” It was particularly important to Nestlé that their backup strategy be built around a sin-gle continually active and universally appli-cable solution. And they wanted it to maintain a centralised backup of all the data necessary for both recovery and further development for all devices and all related projects (i.e. every piece of hardware and software). And the programs actually running on controllers need to correspond precisely with the data on the server. If not, the reason must be easily identifiable and the valid version always available to be reloaded onto the device.
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MachineMetrics
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Artesis A.S.
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Tridium (Honeywell)
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Number of Partners11
ABB
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Siemens
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General Electric
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