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COVER STORY:FOREWORD

Value Chain Innovation

Smart Manufacturing

    Thomas Bauernhansl
    Director of the Fraunhofer Institute for Manufacturing Engineering and Automation IPA
    Director of the Institute of Industrial Manufacturing and Management IFF at the University of Stuttgart
    Prof. Dr.-Ing. Thomas Bauernhansl has been Director of the Fraunhofer Institute for Manufacturing Engineering and Automation IPA and the Institute of Industrial Manufacturing and Management IFF at the University of Stuttgart since 2011. He is an expert in personalized production, Industrie 4.0, sustainable production, quality and advanced complexity management and production optimization. He is a member of the Strategy Committee for Platform Industrie 4.0 organized by the German government and Vice-Chairman of the Steering Committee Alliance Industrie 4.0 BW. Professor Bauernhansl is the author and publisher of numerous books. His most recent work is the second edition of “Industrie 4.0 in Produktion, Automatisierung und Logistik” published by Springer Verlag.

    Digitization including the shift to mass personalization leads to significant changes in manufacturing, especially to making it smart. Cloud-based-platforms for instance offer applications that run in the cloud, or use services provided from the cloud, or both. Some of the prevailing service shop apps could be used also in manufacturing and some platforms are available as private clouds already. Industry-oriented platforms, however, are very young in development.

    Step-by-step, digital transformation is breaking down the Taylorist principle of separating labor and knowledge. In the future, knowledge will be transferred directly to the production line. Employees will once again become competent to make decisions in every area – using assistance systems where necessary – and concentrate on high-value tasks such as decision making and design. Seen from this perspective, Smart Manufacturing will bring back the expertise of the engineers directly into the value creation process and improve the status of production workplaces. In conclusion, the digitization of value creation will be a long and unique journey for every company and involve many phases. Step-by-step they will have to integrate new technologies and structures and redefine established relationships between manufacturers, suppliers and customers.

    Artificial Intelligence (AI) and Machine Learning are obviously core elements of Smart Manufacturing which have to be further developed and have potential to revolutionize manufacturing. Today, companies often have large amounts of data, but they do not derive knowledge from it. Machine learning will help to change that. With the help of AI, which can use structured and unstructured data, conclusions can be drawn from unclear data sets. Those analyses often show completely new contexts that can be used to come to superior decisions and automatically generated services. Without Machine Learning, competitiveness on the market will be lost quickly, because the digital transformation focuses on the efficient and increasingly automated use of large amounts of data gained and processed through the Internet of Things and Services.

    Fraunhofer IPA made many examples of how machine learning can enhance machine functionalities. The robot system “dual arm bin-picking” for instance enabled a robot to grasp exactly the right piece out of unsorted parts in a bin. The robot optimizes its accuracy autonomously. The more often the robot grasps, the better it performs. In our project “smart system analysis” it was possible to raise the total efficiency of automated manufacturing lines by AI-algorithms more than ten percent in a few days.

    The Industrial Internet including the Internet of Things offers versatile, highly flexible systems which make it possible to transfer value creation to the location where it can best take place. This reduces complexity and transaction costs and generates new potential for improving efficiency. The overall system of objectives for value creation – in terms of time, costs, quality, flexibility and sustainability – remains unchanged, but the requirements rise in each individual area. Smart Manufacturing on manufacturing platforms in the framework of Industrie 4.0 extends the scope of solutions for the economic and sustainability aspects of value creation systems to and between every level – from the process to the business ecosystem. All the value creation partners and the end customers will be integrated. This capability is new. Networking based on platforms which permit both horizontal and vertical integration can, therefore, be used to generate and distribute specific tasks or even machine functionalities within this digitized ecosystem.

    Due to the above mentioned increased complexity, technological, social, economic and environmental challenges can no longer be addressed by one company or organization alone. Dynamic, task-specific and temporary alliances are created, based on required competencies and capacities. To enable such collaborations, physical tangible objects will have to merge with the intangible virtual world. Numerous devices communicate with cloud-based software services. For manufacturing, this implies a full view of the complete value chain in order to produce more rapidly, more efficiently and with greater output using fewer resources. This will lead to a reduced time to market and addresses the increasing demand for customized and even personalized products.

    Nowadays, hardware for computation and cloud computing enables the processing of low-level high-frequency data. Big data analytics have become technically feasible and support production visualization and Key Performance Indicators in order to manage and continuously improve manufacturing and logistics.

    The use of big data, Smart Manufacturing and the digitization of value creation within platform-based ecosystems brings a change of perspective. When we are dealing with complex contexts the world is different from the (former) complicated world. We focus on finding correlations to optimize manufacturing instead of searching causalities. We ask “what do we have to do to be successful” instead of “why are we successful”. Cyber-physical systems connect the Internet of Things with people (customers) and new tools, resources and services in production systems – in real time. This lies at the heart of Smart Manufacturing driving the Fourth Industrial Revolution, in which’s context value creation is platform-based and integrated in business ecosystems. Today, the market is ready, the technology is there and companies are on their way to revolutionize business.

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