Dr.-Ing.

Kuhn, Thomas

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  • Publication
    A Quality 4.0 Model for architecting industry 4.0 systems
    ( 2022)
    Oliveira Antonino, Pablo
    ;
    Capilla, Rafael
    ;
    Pelliccione, Patrizio
    ;
    Schnicke, Frank
    ;
    Espen, Daniel
    ;
    Kuhn, Thomas
    ;
    Schmid, Klaus
    The increasing importance of automation and smart capabilities for factories and other industrial systems has led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical and horizontal integration of production through (i) comprehensive and intelligent automation of industrial processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be produced and the underlying production processes. While the first attempts to develop smart factories and enhance the digital transformation of companies are under way, we need adequate methods to support the identification and specification of quality attributes that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010 quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model based on an exhaustive analysis of similar proposals using the design science method as well as expertise from seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference architectures further clarifying its application.
  • Publication
    Continuous engineering for Industry 4.0 architectures and systems
    ( 2022)
    Oliveira Antonino, Pablo
    ;
    Capilla, Rafael
    ;
    Kazman, R.
    ;
    Kuhn, Thomas
    ;
    Schnicke, Frank
    ;
    Treichel, Tagline
    ;
    Bachorek, Adam
    ;
    Müller-Zhang, Zai
    ;
    Salamanca, V.
    Traditionally, the quality of a software or system architecture has been evaluated in the early stages of the development process using architecture quality evaluation methods. Emergent approaches like Industry 4.0 require continuous monitoring of both run-time and development-time quality properties, in contrast to traditional systems where quality is evaluated at specific milestones using techniques such as project reviews. Considering the dynamics and minimum down-time imposed by the industrial production domain, it must also be ensured that Industry 4.0 system evaluations are continuously performed with high confidence and with as much automation as possible, using simulations, for instance. In this regard, there is a need to develop new methods for continuously monitoring and evaluating the quality properties of software-based systems for Industry 4.0, which must be supported by automated quality evaluation techniques. In this research we analyze traditional architecture evaluation methods and Industry 4.0 scenarios, and propose an approach based on Digital Twins and simulations to continuously evaluate runtime quality aspects of the architecture and systems of industrial production plants. The evaluation is based on the instantiation of our approach for a concrete demand of an automation plant in the automotive domain.
  • Publication
    Industry 4.0 reference architectures: State of the art and future trends
    ( 2021)
    Nakagawa, Elisa Yumi
    ;
    Antonino, Pablo Oliveira
    ;
    Schnicke, Frank
    ;
    Capilla, Rafael
    ;
    Kuhn, Thomas
    ;
    Liggesmeyer, Peter
    Industry 4.0 has led to a dramatic shift in manufacturing processes, which must be accomplished by interacting end-to-end industrial systems. While Industry 4.0 is still a big challenge for many manufacturing companies, reference architectures have been increasingly adopted in different domains to guide engineers on how their systems should interoperate and be structured. Companies have made different experiences with reference architectures for Industry 4.0. However, depending on the use cases addressed, a reference architecture may be more or less suited to support the transformation of a particular company. Besides, a complete understanding of existing representative architectures does not exist. The main goal of this work is to review existing reference architectures for Industry 4.0 and analyze them concerning their suitability for supporting Industry 4.0 processes and solutions. For this, we systematically researched these architectures and thoroughly analyzed and characterized them. We also address their use and technologies/tools that could support their implementation. As a result, we found that existing architectures still have a long way to go; hence, we present the most urgent steps for the near future. We conclude that the Industry 4.0 community is right in investing in reference architectures considering the future of Industry 4.0.