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Machinery Intelligence

Machinery Intelligence – the better AI

    The sheer unlimited computing power available from the cloud, increasingly networked Industry 4.0, and an exponentially growing set of valuable data from the operation of machines and systems: Today, digitalization is providing companies with never-before-seen efficiency and is bringing them up to speed for innovative future projects. As a digital partner to its customers, Voith plays an integral role in the design of Machinery Intelligence – with domain knowledge extending back 150 years combined with advanced tools and methods.

    Artificial Intelligence, digitalization, digital opportunities, digital expertise, digital readiness, digital transformation, digitalization is opening up new horizons, industry 4.0, Machinery Intelligence the better AI. Artificial Intelligence is to equip machines with capabilities allowing them to process and analyze large amounts of data. Machinery Intelligence is therefore clearly the more suitable designation.

    Artificial intelligence (AI) is all the rage although the term really misses the heart of the matter: AI is not intended to imitate human thought and intuitive action using machines. Rather, it is to equip machines with capabilities allowing them to process and analyze large amounts of data. Machinery Intelligence is therefore clearly the more suitable designation.

    No other concept in modern IT is associated with so many expectations and promises as AI. AI is soon to solve the great problems of humanity, shape our environment in a sustainable manner, and even help conquer diseases to make all our lives better and more pleasant.

    Want to learn how you can increase your company’s Machinery Intelligence?

    Leave your information below – our experts are happy to help.

    Maximum industrial efficiency thanks to Machinery Intelligence

      Cloud computing reinvigorates AI

      Artificial intelligence has been around for more than 60 years. Its algorithm-based theory has been known for a long time and has not changed substantially. However, there have been dramatic enhancements in the technical potential of applying AI. Cloud computing, the universal availability of tremendous computing performance with a fail-safe operation exceeding 99.99 percent and IT security that far exceeds normal company computer centers: This all makes the intelligent, exhaustive evaluation of data possible for the very first time. This technical enhancement in computing has just helped AI to an upsurge if not a breakthrough.

      Did you know…?

      • The amount of data that we create today is one main reason for the spread of AI.
      • Market researchers from IDC estimate that the amount of data globally of about 33 zettabytes (ZB) in 2018 will increase to 175 ZB by 2025. One zettabyte corresponds to 1 billion terabytes or 1 billion commercially available hard disks.
      • In 1999, the total amount of data available worldwide was just 12 exabytes – more information than humanity had produced in total over the previous 300,000 years, according to a study by the Berkeley University of California.

      Machinery Intelligence: When robots manipulate the physical world

      The manufacturing industry had the greatest share of the global volume of data in 2018, at about 3.6 ZB. That is one more reason why we will say goodbye here to the concept of artificial intelligence and start using Machinery Intelligence (MI) instead. Machinery Intelligence describes the capability of machines to collect and analyze, that is, to process, data. Many experts and scientists see MI as something “that can manipulate the physical world, consequently something built into a robot that makes it autonomous so that the robot can interact with its environment, manipulate it and think about it to draw the correct conclusion,” as defined by an employee at the Chair for Robotics and System Intelligence of the Technical University of Munich (TU München). With this definition, he also emphasized “that the intelligence is associated with the physical machine. AI exists as a concept and may be anything imaginable. Machinery Intelligence focuses instead on the physical presence of the intelligent machinery.”

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      Machine-to-machine communication with connected hardware

      Within the scope of machinery intelligence Networked production is generating a growing quantity of valuable data in the communication from machine to machine. Machines and systems or, in more general terms, assets, are ever increasingly being linked to one another and to centralized computer centers. These are often, but not always, in the cloud. In addition, such assets are increasingly equipped with sensor equipment that, at first, perceives what machines and systems do in a completely value-neutral manner. This equipment could be temperature sensors, cameras or even, for example, microphones like Voith uses in hydro power plants. In the Budarhals hydro power plant in Iceland, for example, Voith installed the OnCare.Acoustic monitoring system. It recognizes noises that deviate from normal. In this way, Voith reduces the probability that the power plant machinery will experience unplanned downtimes and this increases system efficiency.

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      OnCumulus: The platform for modern-day data processing

      Behind the sensors in systems and machinery, there are platforms capable of collecting, consolidating, and processing data. Increasingly, the cloud forms the basis for these technologies, even at Voith. With OnCumulus, we have created a platform for the networked Industry 4.0, the Industrial Internet of Things (IIoT), that you can use to extract added value from your own data. This platform does not include only advanced network, cloud and data technologies. It stores all the expertise and experience of Voith from more than 150 years of its industrial history – including the experience in design, operation, and maintenance of systems. Based on this, you can optimize your processes and resources and achieve more flexibility, data protection, and safety.

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      The intelligent OnCumulus IIoT platform from Voith:

      Platforms such as OnCumulus have the benefit of offering companies of any size direct access to applications that they may scale up to any degree and that are always the latest version. As a result, the users of such platforms do not need, to a large extent, to draw from their own expertise, experience, and their own developments. Instead, thanks to OnCumulus, they can concentrate fully on the (further) development of their core business and data-driven business models.

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      Data quality and data maturity: Smart or Right Data instead of Big Data

      Data from networked production can provide companies with valuable knowledge – about the status of machinery and systems, about business transactions, about market developments. This is because they can support companies in enhancing their business models and inventing new earnings models However, for them to do this, companies must prepare the data. This is an initial and, from this point on, continuing process.

      As a first step, the master data and metadata for their own products and services must be properly organized. The data must be consolidated so that they are consistent and compatible with other systems. Often, individual data domains are located in separate data collections (“silos”) and cannot just be linked to one another.

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      Then, the most important transaction data from the individual company processes and the data from machine-to-machine communication must be continuously collected, processed and stored so that algorithms for intelligent analysis can access the data. In this step, it is not necessary to always store and provide all the data. The buzzword Big Data, popular for a long time, has, in the meantime, become somewhat passé and rightly so. It is being replaced with new data thriftiness and by terms such as “Smart Data” or “Right Data.” All this enables companies to track, collect, and process only that data from the growing data volume that lead to new insights. For a hydro power plant, for example, it is no longer necessary to store all acoustical events recorded by the OnCare.Acoustic. Instead it is better to store only data in need of more precise analysis. The domain knowledge of a manufacturer like Voith and the knowledge based on the data have been part of the algorithms for a long time. And they only need to become active if there is a significant deviation from normal.

      Take a look at OnCare.Acoustic in use:

      Data quality and data transparency are two indispensable strategic conditions for using Machinery Intelligence. Companies can only profit from the growing amount of data if they are capable, both technically and operationally, to condition, link, and process these data. They also need support and experience in this. Voith can provide you with both.

      Industrial automation solutions, proactive monitoring and asset management

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        Automatic data processing by Machinery Intelligence

        One of the salient capabilities of Machinery Intelligence is processing data automatically. In view of the amount of data available, there really is no other feasible option. The manual analysis of such large amounts of data usually exceeds the skills and the time budget of employees many times over.
         
        Machinery and algorithms do not need breaks and do not get tired, even when working on monotonous, repetitive tasks. Consequently, they lend themselves to the automatic processing of large amounts of data. They also have the outstanding ability to detect significant patterns in tremendous amounts of data and can even register the smallest anomalies. For example, they are able to raise the alarm if there are such deviations that might lead to malfunctions in machinery operation. In a company, the specialized discipline of Business Process Automation (BPA) deals with the strategic requirements placed on the automation of business processes.

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        Smart process automation using digitalization

        If machinery intelligence also gets involved, we are more likely to talk about Smart Process Automation and this is one of the most important tasks when companies digitize. One of the essential conditions for this to happen is the continuous digitization of the company processes that produce data. This basically applies to almost all processes because, in modern companies, data are created along the entire process chain – and these data are also needed for valid analyses. And these become virtually impossible if even one link is missing due to the use of analog processes and data not being available digitally.

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        Computer-aided maintenance management systems in networked industry

        One of the most important goals in digitizing parts of a company or entire organizations is the increase in operational efficiency aimed at saving money. Unforeseen machine stoppages and high costs for maintenance and repairs, to the contrary, strain the result. Predictive Maintenance and Intelligent Asset Management are among the most important actions for achieving this goal. Machinery Intelligence has proven a crucial tool in this process.

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        Intelligent Industrial Asset Management in the form of a Computerized Maintenance Management System (CMMS) is important for achieving high system availability. A CMMS can help to reliably identify the key parameters of a networked production environment. Based on this, timely actions can be initiated to maintain this system – with transparent costs. In the sense of a productive Machinery Intelligence, however, many of these systems run into problems when not all the data needed on maintenance are available to them. This can make efficient preventive maintenance more difficult if not impossible.

        With OnCare.Asset, Voith offers, for example, a solution for asset performance management to maintain the customer’s paper machinery or hydro power plants. From planning and documentation, to cost control and spare-parts management, it covers the entire maintenance process in networked production. The system already has all the important data from operation and system preventive maintenance because Voith has also integrated its domain expertise directly in its solutions here.

        IoT health monitoring system: Act before the walls start to shake

        Proactive maintenance is not used just for single machines or systems but also for large complex structures such as buildings or entire factories. They are also subjected to constant loads that, over the long run, may impair their task or function.

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        The physical properties of these structures may be changed or weakened by normal environmental effects and also by extreme weather phenomena such as storms or floods. With its great experience in commissioning, operating and maintaining large hydro power plants, Voith also has knowledge in this domain to prevent the collapse of assemblies. For Structural Health Monitoring (SHM), we also offer maintenance solutions that are specialized in the monitoring of stationary systems in our OnCare product family. These solutions break with the customary forms of maintenance because they detect incipient weaknesses in a structure and can initiate actions for its protection long before functionality is jeopardized.

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        Want to learn how you can increase your company’s Machinery Intelligence?

        Leave your information below – our experts are happy to help.

        Voith – Your contact for intelligent B2B solutions

        Platforms, infrastructures, services: Based on its experience of more than 150 years of industrial history, Voith has developed a digital range of products for its customers. These products are designed to support our customers in using data intelligently. We make use of the best tools in the B2B market for automating services and data analyses. This is how we see digitalization in the manufacturing industry. Consult with us about your requirements and plans.

        Do you want to utilize the potential of Machinery Intelligence?

          Our experts would be glad to help you. Contact us!

          Voith GmbH & Co. KGaA

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