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Complex robot systems and intelligent automation concepts play a key role in manufacturing companies. Due to the required high level of expertise in such systems, many robot automation solutions do not achieve a good economical cost-benefit ratio. In order to meet these challenges, intuitive engineering platforms are urgently needed. In this paper,...
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... is used successfully in software engineering. In the context of architecture development, the onion-view model shows the cyclical course of the aggregation of knowledge as well as the learning effect over time on different views (Fig. 1). For the development of the software architecture, we have divided the onion-view model into three layers. Fig. 2 depicts the three layers, from the physical layer in the outer shell, the digital layer, to the meta-layer in the inner ...
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... In a similar study, Shafiee et al. (2020) examined the application of two approaches, including RUP and Scrum, to addressing documentation challenges in product configuration system development, and highlighted the advantages offered by Scrum. Based on the onion-view model for software engineering described in (Alexander and Robertson, 2004), Schäffer et al. (2018) proposed to manage configuration information and knowledge at three layers, including a physical layer, a digital layer, and a meta layer, in developing configurators. To ensure the continuous maintenance and updates of configuration knowledge in the future, Shafiee et al. (2018) proposed a four-stepped framework to manage configuration knowledge in developing configurators. ...
Configurators have the potential to revolutionize the business processes of Engineering-to-order (ETO) companies. Despite their positive impacts on ETO companies' operations and strategies, there is a paucity of empirical investigations examining the development processes and practices of configurators, in particular integrated configurators. We, thus, carry out a longitudinal case study in a large ETO company to study and compare the characteristics and dynamics of the development process of an integrated sales and technical (ST) configurator with these of a sales configurator and a technical configurator. First, the findings uncover the nature of the integrated ST configurator development process in terms of development team formation, development planning activities, processes and activities that went wrong, and unplanned events and their handling. Second, performance evaluation with respect to several criteria contributes to a holistic picture of the development process of the integrated ST configurators. Based on the findings, we further shed light on managerial implications including the business processes changes associated with the application of the integrated ST configurator and the need of having a clear, comprehensive project plan before development. To conclude, our study is expected to broaden ETO companies’ understanding of the development processes of integrated configurators and to guide them to make wise decisions in developing configurators.
... An outline for a user friendly platform for configuring robotic solutions is proposed in Schäffer et. al. [4]. They describe that creating configurators for robot systems is complicated due to a number of issues related to lack of standardisation and insufficient documentation. ...
The amount of robots in industry is increasing, pushing the need for easier configuration and integration of robots. The cost of robot integration is often larger than the cost of the robots themselves. With the increasing complexity of robotic systems and the tasks they perform, the future of reducing the expenses of robot system integration is significant. In this position paper, we report on some of the main challenges in robot system configuration, and give an overview of the current state-of-the-art of robot system configuration. We briefly look into the configuration of personal computers (PCs) and study how the robot system configuration can be improved inspired by the standards used in the PC area. We conclude with concrete proposals as to what can be done in the future, to make the process of robot system configuration and integration easier and cheaper.
... There are two steps build the plant model. The first step is a product configurator, which is a similar process as presented in [18]. The result is the digital product twin that, however, in the configured extend is an information model that contains, amongst others, CAD data, connector types of the components, the wiring, or the dimensions and positions of the products. ...
Nowadays, companies produce electrolyzers with a high manual effort. Main reasons for this manual production are a low demand as well as a high variance in the size and design of the electrolyzers. The sizes, for instance, can range from 19-inch racks up to 40-feet containers. Nevertheless, we can observe a trend towards the use of hydrogen. Of course, the increased use of hydrogen will raise the demand for electrolyzers, which in turn will cause a need for automated production. Although we can design an efficient production plant for a single type of electrolyzer, we need a solution for a large variety of electrolyzers. Starting with a specification of an arbitrary electrolyzer, the research project FertiRob aims to develop a generic method to derive an automated production plant. The method will work on a digital twin level. The input is a template of the electrolyzer while the output is a digital twin of the corresponding production plant. The latter twin will provide a sophisticated simulation that is used for succeeding methods, e.g., to validate the twin by means of a virtual commissioning or to optimize the production plant in terms of cycle time or required space. As it turns out, a main prerequisite for the method is a certain level of abstraction of the electrolyzer specification as well as of the production means. This paper will present the current approach for a possible abstraction. Thereby, we transfer the design pattern paradigm to the described problem of deriving a digital twin of a production plant. Design patterns are widely used in the domain of software development, and they provide a sufficient level of abstraction for both the electrolyzers and the production means.
... For this reason, expert knowledge and Best Practice (BP) examples, regarding reasonable realizable physical functions and interaction with the product as well as first basic path planning for position and range evaluation of RAS, are necessary. Thereby, BP [14,21] are modularized and digitalized, successfully implemented RAS. ...
... ROBOTOP is based on the scalable and flexible idea of a microservice architecture, firstly introduced in 2006 through amazon [29]. In doing so, the ROBOTOP functions are divided into several independent microservices (MS), such as BP selection, configuration, simulation, AML-data-exchange [1,14] and spec-sheet generator [21]. The MS can communicate via standardized interfaces. ...
Automation solutions in production represent a sensible and long-term cost-effective alternative to manual work, especially for physically strenuous or dangerous activities. However, especially for small companies, automation solutions are associated with a considerable initial complexity and a high effort in planning and implementation. The ROBOTOP project, a consortium of industrial companies and research institutes has therefore developed a flexible web platform for the simplified, modular planning and configuration of robot-based automation solutions for frequent tasks. In this paper, an overview of the project’s scientific findings and the resulting platform is given. Therefore, challenges due to the scope of knowledge-based engineering configurators like the acquisition of necessary data, its description, and the graphical representation are outlined. Insights are given into the platform’s functions and its technical separation into different Microservices such as Best Practice selection, configuration, simulation, AML-data-exchange and spec-sheet generator with the focus on the configuration. Finally, the user experience and potentials are highlighted.
... Other approaches also rely on the simulation of manufacturing resources through a platform to quickly find suitable configurations for personalized production orders (Graupner et al., 2002;Schäffer et al., 2018). ...
The paradigm shift from mass production to on-demand, personalized,
customer-driven, and knowledge-based production reshapes manufacturing.
Smart manufacturing leads to an automated world that relies
more on information and communication technologies (ICTs) and sophisticated
information-technology-intensive processes, enhancing flexibility.
Furthermore, as automation and digital supply chain management
become the norm across enterprise systems, advanced manufacturing
becomes increasingly linked at a global level. Manufacturing companies
are under pressure to achieve the goals of high competitiveness and
profitability in a globalized and volatile environment. To address these
challenges, engineers have to develop and implement new design and operation
methodologies for production networks taking also into account
mass personalization and market uncertainty. In the era of digitalization,
the integration of cloud-based approaches can elevate enterprise performance.
Therefore, to meet these challenges, new technologies such as
cyber-
physical systems (CPS), artificial intelligence (AI), augmented reality
(AR), big data analytics, the Internet of things (IoT), and the industrial
Internet of things (IIoT) must be integrated.
The book consists of 12 chapters, written by leading researchers in the
field of manufacturing. Chapter 1 presents the peculiarities of the integration
of key Industry 4.0 technologies toward the design, planning, and operation
of global production networks and the integration of the customer
to the design phase of the products, services, and systems. In Chapter 2
recent and future trends of how emerging technologies support the transformations
in reconfigurable supply chains and production systems are
presented. Chapter 3 is devoted to present the implications for the design
and management of global production networks (GPNs) induced by the
mass production paradigm (MPP). Chapter 4 aims to identify and highlight
the implications in the design and planning of manufacturing networks
in the mass personalization environment and Chapter 5 presents
the state of the art on adaptive scheduling and developments in smart
scheduling within Industry 4.0 paradigm. Chapter 6 presents how modern
digital manufacturing technologies may be utilized for reducing and
eventually taming the complexity in production systems and networks.
Chapter 7 provides an overview of innovative smart scheduling and predictive
maintenance (PdM) techniques under smart manufacturing production
environments. Chapter 8 reviews the landscape of the industrial Internet of things (IIoT). Chapter 9 presents a generic framework for
industrial big data utilization in industrial environments and big data
application areas and Chapter 10 aims to map major architectures and applications
of digital twins for Industry 4.0. Chapter 11 reviews and presents
machine learning (ML) technologies and artificial intelligence (AI) in
manufacturing systems. Finally, Chapter 12 demonstrates the real-world
applicability of blockchain potential using industrial case studies.
... Other approaches also rely on the simulation of manufacturing resources through a platform to quickly find suitable configurations for personalized production orders (Graupner et al., 2002;Schäffer et al., 2018). ...
The industrial Internet of things (IIoT) key technologies advance flexibility, personalization, and cost savings in industrial processes. Smart manufacturing and Industry 4.0 integrate the physical and decision-making aspects of manufacturing processes into autonomous and decentralized systems. Cloud manufacturing is emerging with scheduling issues between process design dynamics, and machine setup. Furthermore, as information and communication technologies (ICTs) have integrated into the cyber-physical systems (CPSs), adaptive scheduling and rescheduling have turned into the cornerstones of smart manufacturing. The cyber-physical production systems (CPPs) link the information technology (IT) systems to establish communication networks. This chapter addresses the state of the art of the ICTs that are the drivers of data-driven innovations and presents the industrial applications that bridge the gap among the industry and academia creating a bifold knowledge and experience network. Finally, the shift toward digitalization intensifies the need for digital skills. Lastly, the problems and future research directions toward the new generation of the production staff are discussed.
... From the necessity of consistent data exchange between IT solutions for RAS planning (e.g. [38]), KD4 deals with the development of semantically consistent data models ensuring interoperability. In general, the path towards continuous, consistent modelling can be divided into three stages, representing the historical development of technology enablers in an abstracted way (Fig. 10). ...
Robot-centric automation solutions (RAS) promise greater efficiency and consistent quality in production, relieving workers of physically demanding and dangerous tasks, especially in the times of COVID-19. Nevertheless, due to their relatively high complexity and implementation costs, RAS are only used to a limited extent by small and medium-sized manufacturing companies. As a rule, the high costs of RAS arise from custom engineering efforts, which take up to 70 percent of the acquisition costs. For this reason, it is necessary to optimise the engineering of RAS. However, software tools such as configurators have been used primarily for the individualisation of products, such as automobiles or clothing, based on variants predefined by the manufacturer, and less for the engineering of automation solutions. The development of knowledge-based systems, in particular knowledge-based engineering configurators (EC), is usually performed by few proficient experts with high development effort. One of the primary challenges in the knowledge acquisition is that several experts possess partial aspects of knowledge in an inhomogeneous, implicit form. Furthermore, there is a lack of efficient development methods for EC. By reusing knowledge elements from previous development projects, a sustainable increase in efficiency is possible. In order to enable an efficient development process of EC, we introduce a structuring model consisting of four knowledge domains (KD): knowledge about specific business cases (KD1), Best Practices as case-specific solution knowledge (KD2), logical expert knowledge (KD3) as well as semantically consistent data models for interoperability of different IT systems (KD4). As the four KD are independent, their development can be agilely divided among several teams or companies. Finally, the agile development approach is validated individually for each KD as well as comprehensively within the scope of the ROBOTOP platform for planning RAS.
... For this reason, it is necessary to optimize the engineering and development tools of RAS. Configurators are a possible tool to automate knowledge-based processes [4][5][6], which also includes engineering. Also, configurators provide the opportunity of condensing the knowledge of different employees of engineering. ...
Robot-centric automation solutions (RAS) promise more efficiency and quality in production as well as more economic stability and security through local production, especially in the times of COVID-19. Nevertheless, due to their high complexity and costs, RAS are only used to a limited extent by small and medium-sized manufacturing companies. As a rule, the high costs of RAS arise from individual engineering, which takes up to 70 percent of the acquisition costs. For this reason, it is necessary to optimise the engineering of RAS. Among other things, better software and less costly top-down engineering methods are needed for this kind of enhancement. Pure optimisation via more advanced simulation tools is not sufficient. Configurators in particular offer the possibility of automatically arranging individual solutions from existing experience. Up to now, however, configurators have been used primarily for the individualisation of products, such as automobiles or clothing, on the basis of the variants predefined by the manufacturer, and less for the engineering of automation solutions. To make top-down configuration and simulation functions easily available to small medium enterprises, a web platform is a convenient solution. Due to the high complexity within the engineering domain, it is reasonable to build this kind of web platform with different services from specialised companies, e.g. by using microservices (MS). Conceivable roles could be as following. The web platform operator (WPO) offers an industry-specific, turnkey complete web platform. The WPO combines, integrates and orchestrates various modules and MS like configuration, simulation, data exchange and other. The MS can be provided by MS providers. In particular, since data interoperability and exchange are very important for engineering, an AutomationML (AML) MS is used to implement both. AML particularly supports the generic exchange of data based on industrial standards. To provide a general solution, a MS and AML-based web platform reference architecture was developed. These concepts and MS architecture are validated via a prototypical implementation and utilisation of the web platform within the scope of the ROBOTOP research project. Thus, the potential for increasing efficiency in engineering for RAS could be demonstrated using this top-down approach.
... Our vision, and that of our industrial partners, is that robot configuration tasks should be as easy as their PC configuration counterparts. Recent developments [11,12,14] attempt to simplify robot integration by modelling skills for automation of robots and end effectors. While this is an important milestone, the state of the art assumes the information regarding these skills is available. ...
Determining which components are required for a system configuration, and whether they are compatible, can be a difficult task, especially in an industry with significant amounts of information that resides within a group of experts. In this paper we illustrate some of the main challenges we and our industrial partner (Technicon) face when configuring a robot system (typically consisting of a robotic arm, end effector, coupling device, and a base) and present our domain model, Robot System Configurator Information Model (RoboCIM). We formalise the model within a defeasible reasoning framework, in order to explicitly capture cases where information is missing or is obtained from the system integrators’ experience. We provide a prototype implementation of the framework in ASP and evaluate it on a subset of components from Technicon’s component catalogue, illustrating the feasibility of the configurator.
... Therefore, the classical planning process for RAS is analysed and divided into subsequent stations. Furthermore, we identify potentials of streamlining the planning process through the use of KC, resulting in a second proposed process, the Best Practice based planning, developed within the research project ROBOTOP [2,3,[26][27][28][29]. To allow for an intuitive side-byside comparison, the individual scenes from both planning approaches up to the virtual robot teach-in are combined and implemented in order of execution in a virtual tour. ...
The term Virtual Reality (VR), is very well known in the consumer goods and entertainment sector. The visual presentation of the VR environment is typically achieved via stereoscopic head-mounted displays (HMD), and the interaction via a 3D position detection of HMD and additional input devices such as controllers for active user input. While the variety of applications in the entertainment industry is constantly growing and the technological possibilities become more extensive, this trend has marginally established itself in the industry. Even though powerful and affordable VR hardware is available, VR applications are often associated more with gaming than professional industrial applications. In addition, only few interaction mechanisms such as 3D viewing, moving, teleporting and rarely direct interaction capabilities are used in the most industrial VR solutions. The reason for this is often a lack of understanding and structure of use cases and the added value that VR applications and interactions create for companies and their customers. This unnecessarily limits the applicability of new VR applications for the industry. For a better structuring of VR use cases and required 3D objects for targeted user interaction, we introduce seven Levels of Detail. Along these, one VR use case setup is created, to provide examples for classical concept planning and a new knowledge-based process based on engineering Best Practices. For each, we derive adequate prototypical implemented demonstrator stations and necessary interaction mechanisms for VR development. To highlight further VR possibilities, we extend the examples by adding a second use case setup for VR planning and virtual commissioning of industrial human-robot collaboration solutions based on body and hand tracking. Hence, the contribution provides a structured compilation of potential and useful industrial VR planning use case setups and for these relevant interaction mechanisms in combination with concretely implemented examples.