Conference Paper

Continuous Integration in Multi-view Modeling: A Model Transformation Pipeline Architecture for Production Systems Engineering

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

Background. Systems modeling in Production Systems Engineering (PSE) is complex: Multiple views from different disciplines have to be integrated, while semantic differences stemming from various descriptions must be bridged. Aim. This paper proposes the Multi-view Modeling Framework (MvMF) approach and architecture of a model transformation pipeline. The approach aims to ease setup and shorten configuration effort of multi-view modeling operations and support the reusability of modeling environments, like additional view integration. Method. We combine multi-view modeling with principles from distributed, agile workflows, i.e., Git and Continuous Integration. Results. The MvMF provides a lightweight modeling operation environment for AutomationML (AML) models. We show MvMF capabilities and demonstrate the feasibility of MvMF with a demonstrating use case including fundamental model operation features, such as compare and merge. Conclusion. Increasing requirements on the traceability of changes and validation of system designs require improved and extended model transformations and integration mechanisms. The proposed architecture and prototype design represents a first step towards an agile PSE modeling workflow.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... We will build on recent research of the Christian Doppler Laboratory on Security and Quality Improvement in the Production System Lifecycle [3,4,15,18,19,28], resulting from a technical debt analysis [28], which highlighted the gaps between established practices and state of the art. ...
... We designed and prototypically evaluated an initial approach of a multi-view model transformation pipeline using a common underlying model and automated by a Continuous Integration (CI) server [19]. ...
Conference Paper
Full-text available
Background. Consistent cross-disciplinary engineering data models have become increasingly important for engineers and project managers to validate system designs or implement new features in existing systems. However, discipline-specific designs (mechanical, electrical, automation engineering etc.) in isolated data models and proprietary software tools often create information silos. Similar to information systems, the challenges in Cyber-Physical Production System (CPPS) are a high amount of heterogeneous data that needs to be analysed and accessible for stakeholders and systems. Aim. The goal of the Flexible Multi-aspect Model Integration project is to support the integration of local engineering views and artefacts using the definition of common concepts across different disciplines. Therefore, the thesis project will provide capabilities to integrate and validate multi-aspect models more efficiently to increase the data quality. Method. The project will follow Design Science methodology to design and evaluate i) a method for collecting and defining common concepts across engineering disciplines, ii) a modularised software system design that enables flexible model integration processes in a CPPS context, and iii) an exemplary model integration process that supports data integration needs in the planning, operation, and analytics phase. The model integration processes are evaluated with real-world uses cases from industry. Conclusion. The information systems community will gain insight into the requirements in engineering and a method for agreeing on an inter-disciplinary common understanding from this research.
... As integrated model description language, AML is proposed by several framework architectures [17], [18]. Implementations like the Multi-view Modeling Framework (MvMF) use AML to enable and automate an multi-disciplinary and view-specific data integration process defined by a flexible pipeline architecture [19]. ...
... However, while we designed the first instance model manually we needed additional tool support to automate the process. Based on the designed common concept definition method and the multidomain engineering model formalization method and their prototype implementations we will use the MvMF [19] to specify and implement a flexible integration pipeline. ...
Conference Paper
Industry 4.0 envisions adaptive production systems,i.e.,Cyber-Physical Production Systems (CPPSs), to manufacture products from a product line. Product-Process-Resource modeling represents the essential aspects of a CPPS. However,due to discipline-specific models, e.g., mechanical, electrical, and automation models, it is often unclear how to integrate the proprietary data into an integrated model due to missing common understanding. This paper investigates (i) how to integrate local engineering views with Common Concepts (CCs) and using them as a defined taxonomy for modeling a network of engineering concepts; (ii) how to build an engineering network graph for visualisation and analysis considering discipline-specific needs. We motivate a method to support CPPS engineering organisations to integrate their heterogeneous data using CCs. This builds the basis for defining multi-domain engineering graphs for visualisation and analysis aspects. In this paper, we present a research agenda discussing open issues and expected results.
... MvCM System Design, based on MvMF(Rinker et al., 2021b). ...
Conference Paper
Agile Production Systems Engineering (PSE) is a complex, collaborative, and knowledge-intensive process. PSE requires expert knowledge from various disciplines and the integration of discipline-specific perspectives and workflows. This integration is a major challenge due to fragmented views on the production system with a difficult a priori coordination of changes. Hence, proper tracking and management of changes to heterogeneous engineering artifacts across disciplines is key for successful collaboration in such environments. This paper explores effective and efficient multi-view change management for PSE. Therefore, we elicit requirements for multi-view change management. We design the agile Multi-view Change Management (MvCM) workflow by adapting the well-established Git Workflow with pull requests with a multi-view coordination artifact to improve over traditional document-based change management in PSE. We design an information system architecture to automate MvCM workflow steps. We evaluate the MvCM workflow in the context of a welding robot work cell for car parts, using a typical set of changes. The findings indicate that the MvCM workflow is feasible, effective, and efficient for changes of production asset properties in agile PSE.
Article
Full-text available
Currently, enterprises have to make quick and resilient responses to changing market requirements. In light of this, low-code development platforms provide the technology mechanisms to facilitate and automate the development of software applications to support current enterprise needs and promote digital transformation. Based on a theory-building research methodology through the literature and other information sources review, the main contribution of this paper is the current characterisation of the emerging low-code domain following the foundations of the computer-aided software engineering field. A context analysis, focused on the current status of research related to the low-code development platforms, is performed. Moreover, benchmarking among the existing low-code development platforms addressed to manufacturing industry is analysed to identify the current lacking features. As an illustrative example of the emerging low-code paradigm and respond to the identified uncovered features, the virtual factory open operating system (vf-OS) platform is described as an open multi-sided low-code framework able to manage the overall network of a collaborative manufacturing and logistics environment that enables humans, applications, and Internet of Things (IoT) devices to seamlessly communicate and interoperate in the interconnected environment, promoting resilient digital transformation.
Article
Full-text available
Industry 4.0 integrates cyber-physical systems with the Internet of Things to optimize the complete value-added chain. Successfully applying Industry 4.0 requires the cooperation of various stakeholders from different domains. Domain-specific modeling languages promise to facilitate their involvement through leveraging (domain-specific) models to primary development artifacts. We aim to assess the use of modeling in Industry 4.0 through the lens of modeling languages in a broad sense. Based on an extensive literature review, we updated our systematic mapping study on modeling languages and modeling techniques used in Industry 4.0 (Wortmann et al., Conference on model-driven engineering languages and systems (MODELS’17), IEEE, pp 281–291, 2017) to include publications until February 2018. Overall, the updated study considers 3344 candidate publications that were systematically investigated until 408 relevant publications were identified. Based on these, we developed an updated map of the research landscape on modeling languages and techniques for Industry 4.0. Research on modeling languages in Industry 4.0 focuses on contributing methods to solve the challenges of digital representation and integration. To this end, languages from systems engineering and knowledge representation are applied most often but rarely combined. There also is a gap between the communities researching and applying modeling languages for Industry 4.0 that originates from different perspectives on modeling and related standards. From the vantage point of modeling, Industry 4.0 is the combination of systems engineering, with cyber-physical systems, and knowledge engineering. Research currently is splintered along topics and communities and accelerating progress demands for multi-disciplinary, integrated research efforts.
Article
Full-text available
In this paper we provide an overview of recent theoretical approaches and technologies that respond to the fundamental challenges of modern factory automation. We classify these major methods and technologies into several groups and, for seven of them - namely: vertical integration of factory automation systems; distributed and decentralised control, smart sensors and actuators in factories; networked control systems and wireless sensors and actuators; autonomy and self-organisation of factories; advanced sensing for factory automation; semantic models of factories; engineering methods of factory automation systems - we report recent research contributions and formulate open technical problems in the domain of modern factory automation.
Conference Paper
Full-text available
Industry 4.0 initiatives have fostered the definition of different standards, e.g., AutomationML or OPC UA, allowing for the specification of industrial objects and for machine-to-machine communication in Smart Factories. Albeit facilitating interoperability at different steps of the production life-cycle, the information models generated from these standards are not semantically defined, making the semantic data integration a challenging problem. We tackle the problems of integrating data from documents specified either using the same or different Industry 4.0 standards, and propose a rule-based framework that combines deductive databases and Semantic Web technologies to effectively solve these problems. As a proof-of-concept, we have developed a Datalog-based representation for AutomationML documents, and a set of rules for identifying semantic heterogeneity problems among these documents. We have empirically evaluated our proposed framework against several benchmarks and the initial results suggest that exploiting deductive and Semantic Web techniques allows for increasing scalability, efficiency, and coherence of models for Industry 4.0 manufacturing environments.
Conference Paper
Full-text available
Modeling complex systems involves dealing with several heterogeneous and interrelated models defined using a variety of languages (UML, ER, BPMN, DSLs, etc.). These models must be frequently combined in different cross-domain perspectives to provide stakeholders the view of the system they need to best perform their tasks. Several model composition approaches have already been proposed addressing this problem. Nevertheless, they present some important limitations concerning efficiency, interoperability and synchronization between the base models and the composed ones. As an alternative we introduce EMF Views, an approach coming with a dedicated language and tooling for defining views on potentially heterogeneous models. Similarly to views in databases, model views are not materialized but instead redirect all model access and manipulation requests to the base models from which they are obtained. This is realized in a transparent way for both the modeler and the other modeling tools using the concerned (meta)models.
Conference Paper
Full-text available
As the range of modelling approaches that claim to be "multi-level" diversifies, there is growing debate in the literature about what multi-level modelling actually is and what form supporting languages and infrastructures should take. However, there is no consensus yet on how this debate should be framed and what objective criteria should be used to evaluate different approaches. It is clear from the literature that proponents of different approaches base their arguments on fundamentally different assumptions about what multi-level modelling is and what benefits it should aim to provide. In this position paper we identify some of the core issues that currently hinder progress towards the required consensus and identify some of the terminological differences that have amplified confusion. Referencing various work that represents diverging viewpoints, our goal is to initiate a meta-discussion on what the open questions in multi-level modelling are, how respective proposals to answer them could be evaluated, and which kinds of discussions are expedient in this context.
Article
To cope with the challenge of managing the complexity of automated production systems, model-based approaches are applied increasingly. However, due to the multitude of different disciplines involved in automated production systems engineering, e.g., mechanical, electrical, and software engineering, several modeling languages are used within a project to describe the system from different perspectives. To ensure that the resulting system models are not contradictory, the necessity to continuously diagnose and handle inconsistencies within and in between models arises. This article proposes a comprehensive approach that allows stakeholders to specify, diagnose, and handle inconsistencies in model-based systems engineering. In particular, to explicitly capture the dependencies and consistency rules that must hold between the disparate engineering models, a dedicated graphical modeling language is proposed. By means of this language, stakeholders can specify, diagnose, and handle inconsistencies in the accompanying inconsistency management framework. The approach is implemented based on the Eclipse Modeling Framework (EMF) and evaluated based on a demonstrator project as well as a small user experiment. First findings indicate that the approach is expressive enough to capture typical dependencies and consistency rules in the automated production system domain and that it requires less effort compared to manually developing inter-model inconsistency management solutions.
Conference Paper
Technical Debt (TD) has proven to be a suitable communication concept for software-intensive contexts to raise awareness regarding longterm negative effects of deviations from standards and guidelines. TD has also been introduced to systems engineering domain, to communicate design shortcomings in long-running, software-assisted systems. We analysed potential TD in the engineering data exchange for production system engineering. Similar to requirements engineering in software-intensive systems, data exchange in the design phase plays an integral part in Software Engineering (SE) for Production Systems Engineering: Specifications, and physical logic have to be derived from heterogeneous plant models or parameter tables designed by different stakeholders. However, traditional procedures and inadequate tool support lead to inefficient data extraction and integration. We identified debt arising from knowledge representation, data model and the exchange process. The refinement validation of identified TD was achieved through semi-structured interviews with representatives in two analysed companies. In an online survey with ten participants from an industrial consortium we evaluated whether the identified TD concepts also applied to other companies, which is true for the majority of TD. Furthermore, we discuss promising TD management strategies to repay and manage negative effects and the accumulation of additional debt, such as improved communication, test-driven model engineering and visualisation of engineering models.
Conference Paper
Model-Based System Engineering is increasingly adopted. However it is centred on the notion of model while the industry is still strongly document-based. In order to enable a smooth evolution between those paradigms, the interplay between documents and models need to be managed, especially models can be used to efficiently derive up-to-date documents matching standard templates from initial requirements to final certification. The purpose of this paper is to review and to assess current strategies to manage model for document generators in order to meet industrial requirements like document complexity, document/model scalability, quick generation time, maintainability and evolvability of document templates. After exploring different generation strategies, our work focuses on toolchains based on the Eclipse Modelling Framework and compares a few shortlisted libraries in the light of our requirements and using document derived from industry cases.
Chapter
A key requirement in supporting the work of engineers involved in the design of Cyber-Physical Production Systems (CPPS) is offering tools that can deal with engineering data produced across the various involved engineering disciplines. Such data is created by different discipline-specific tools and is represented in tool-specific data models. Therefore, due to this data heterogeneity, it is challenging to coordinate activities that require project-level data access. Semantic Web technologies (SWTs) provide solutions for integrating and making sense of heterogeneous data sets and as such are a good solution candidate for solving data integration challenges in multi-disciplinary engineering (MDE) processes specific for the engineering of cyber-physical as well as traditional production systems. In this chapter, we investigate how SWTs can support multi-disciplinary engineering processes in CPPS. Based on CPPS engineering use cases, we discuss typical needs for intelligent data integration and access, and show how these needs can be addressed by SWTs and tools. For this, we draw on our own experiences in building Semantic Web solutions in engineering environments.
Chapter
Application fields of automated production systems are varied, e.g. automotive, aerospace and food industry, just to name a few. The complexity of such production systems has significantly been increased in the last years, (Koren et al., CIRP Ann Manuf Technol 48(2):527–540, 1999). This increase was a result of the increased complexity and variance of products. As a result of this, the engineering workflow of automated production system has continuously been adapted to new requirements. In this regards, this chapter shows and describes the current engineering workflow of automated production systems based on experience in the field of production system for the automotive industry. The main focus of this description is set on the established tool-chains and used tools to create engineering information as well as data formats to save and exchange information between tools and involved personnel. In the introduction of this chapter, differences between an automated production system and a cyber-physical system are given. Current production systems could be named CPPS but this term is not popular in the field of production system builder as well as production owners. But in spite of that the end of this chapter gives an outlook of the future of automated production systems in direction of CPPS.
Conference Paper
View-based modeling approaches based on the notion of a Single Underlying Model (SUM) revolve around the use of projective views to manipulate the SUM. Defining view types is a challenging task since it includes the definition of view element types and the definition of transformations to extract data from the SUM to populate the view. The latter can be supported by an automatic transformation mechanism that easies the definition and maintenance of transformations. Such an approach leads to simple and fast definition of views and easies the work of the methodologist in defining relations between the elements in the SUM and the elements in the views.
Article
In the context of Model Driven Engineering, models are the main development artifacts and model transformations are among the most important operations applied to models. A number of specialized languages have been proposed, aimed at specifying model transformations. Apart from the software engineering properties of transformation languages, the availability of high quality tool support is also of key importance for the industrial adoption and ultimate success of MDE. In this paper we present ATL: a model transformation language and its execution environment based on the Eclipse framework. ATL tools provide support for the major tasks involved in using a language: editing, compiling, executing, and debugging.
Efficient engineering data exchange in multidisciplinary systems engineering
  • S Biffl
  • A Lüder
  • F Rinker
  • L Waltersdorfer
Biffl, S., Lüder, A., Rinker, F., and Waltersdorfer, L. (2019). Efficient engineering data exchange in multidisciplinary systems engineering. In International Conference on Advanced Information Systems Engineering, pages 17-31. Springer.
  • C Ebert
  • G Gallardo
  • J Hernantes
  • N Serrano
Ebert, C., Gallardo, G., Hernantes, J., and Serrano, N. (2016). Devops. Ieee Software, 33(3):94-100.
Stepwise adoption of continuous delivery in model-driven engineering
  • J Garcia
  • J Cabot
Garcia, J. and Cabot, J. (2018). Stepwise adoption of continuous delivery in model-driven engineering. In International Workshop on Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, pages 19-32. Springer.
Towards support of global views on common concepts employing local views
  • F Rinker
  • L Waltersdorfer
  • K Meixner
  • S Biffl
Rinker, F., Waltersdorfer, L., Meixner, K., and Biffl, S. (2019). Towards support of global views on common concepts employing local views. In 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019, Zaragoza, Spain, September 10-13, 2019, pages 1686-1689. IEEE.
Lowcomote: Training the next generation of experts in scalable low-code engineering platforms
  • M Tisi
  • J Mottu
  • D S Kolovos
  • J De Lara
  • E Guerra
  • D D Ruscio
  • A Pierantonio
  • M Wimmer
Tisi, M., Mottu, J., Kolovos, D. S., de Lara, J., Guerra, E., Ruscio, D. D., Pierantonio, A., and Wimmer, M. (2019). Lowcomote: Training the next generation of experts in scalable low-code engineering platforms. volume 2405 of CEUR Workshop Proceedings, pages 73-78. CEUR-WS.org.
Presentation of EMF Compare Utility
  • A Toulmé
Toulmé, A. (2006). Presentation of EMF Compare Utility. In Eclipse Modeling Symposium, pages 1-8.