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A Domain-Specific Language for Product-Process-Resource Modeling
Abstract
Cyber-Physical Production Systems (CPPSs) are envisioned as next-generation adaptive production systems combining modern production techniques with the latest information technology. In CPPS engineering, basic planners define the functional relations between Product-Process-Resource (PPR) views to specify valid production process and resource designs that fulfill the customer requirements. Using the Formalised Process Description standard (VDI 3682) allows to visually model thesePPR views but is hard to process by machines and insufficiently defined formally. In this paper, we present the design of a Domain Specific Language (DSL), the PPR DSL, to effectively and efficiently represent PPR aspects and evaluate constraints defined for these aspects. We illustrate the PPR DSL with the use case rocker switch, abstracted from an industrial use case. We identify requirements and iteratively design and evaluate the PPR DSL. We show that the PPR DSL can model (a) the functional view of CPPSs and (b) define and efficiently evaluate constraints of a CPPS using technologies well-established in industry. We argue that the PPR DSL provides a valuable contribution for the community and industry to describe PPR aspects and evaluate constraints on these aspects. This way, PPR model can be defined and evaluated more easily for researchers and/or practitioners.
... Figure 1 shows a section of a PPR model in VDI 3682 notation [13] with the products (represented as circles in a blue frame), e.g., the door, one process step (depicted as a rectangle in a red frame), i.e., the door screwing process, and a resource (shown as a rounded rectangle in a yellow frame), i.e., the screw-driving robot. A corresponding engineering artifact can be, e.g., the model in the Product-Process-Resource Domain-Specific Language (PPR-DSL) [22]. ...
... This reference model can specify common requirements but also technical solution elements for the PDAs. Furthermore, the engineers analyze existing artifacts, like PPR models in PPR-DSL [22], from previous projects to assess their reuse potential. The analysis aims to find and document artifacts that have been used in several projects and that engineers can adapt for more generic use. ...
... Similarly, the engineers model the resource functionality as capabilities and potentially implement them as skills. Modeling the C&Ss requires using appropriate models or languages, such as ontologies [5,17] or domain-specific languages [22]. For the skill implementations, engineers can utilize technologies, such as OPC UA [8,18] or PackML. ...
The flexibility of production systems is a key factor for Industry 4.0. Capabilities and skills (C&Ss) aim at improving engineering flexibility along the production system life-cycle by decoupling production processes and resources. However, traditional reuse approaches in production systems engineering, such as the VDI 3695, do not yet consider C&Ss. This paper proposes the Capability and Skill Reuse (CSR) framework to define how VDI 3695 activities require adaptation for C&S models. The paper analyzes how the framework can facilitate reuse along the production system life-cycle and identifies open issues for research.
... An integrated MDEG provides analysis capabilities, e.g., to investigate engineering data inconsistencies and logical constraints. For better illustration we present the Rocker Switch [4] use case elicited with our industry partner. The use case presents the assembly process of a rocker switch, its input & output products and related resources with sub-hierarchies visualised in a PPR network. ...
... Graph analysis can be conducted by the provided graph query language. Fig. 1 depicts an excerpt of an engineering graph based on the industrial use case Rocker Switch [4]. In addition to the PPR information of the use case analysis, aspects such as skills [3], requirements and assets are shown to motivate the potential of an MDEG. ...
... Fig. 1 is divided into four sections: (1) Product & Process (2) Skills (3) CPPS Resources and (4) Assets. The underlying PPR network is organised in the sections (1) and (3) and designed using a Domain-specific language (DSL), the PPR DSL [4]. The figure depicts products of the PPR network as a circle, processes as an rectangle and resources as a small rectangle with round corners. ...
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.
... The case studies are represented universally in the PPR DSL [16] as CPPS engineering artifact. The PPR DSL was created to represent the functional view on CPPSs including system variants. ...
... To plan a CPPS, engineers first design its functional model using Product-Process-Resource (PPR) concepts including different variants. Therefore, Meixner et al. [16] designed the PPR DSL building on extensions of the Formalised Process Description (FPD) [9]. Product design (with variants) is a crucial part of CPPS planning as the 2 https://github.com/tuw-qse/cpps-var-case-studies 1 Attribute "length": { type: "Number", unit: "mm" } variants and parameters determine the production processes and resources. ...
... If no variability meta-model is available (e.g., for industry representations), these transformation operations define a mapping between the industry engineering artifact and the well-known variability model. Transformation algorithms implement the transformation operations between two concrete variability model types (e.g., feature model to decision model) or the industry representation to a variability model (e.g., the PPR DSL [16] to a feature model) Based on learnings from earlier work [6], we map all product variability concepts of the PPR DSL to concepts of feature models. We accommodate for specific concepts of the PPR DSL, which a feature model cannot represent, e.g., custom attribute definitions or constraints based on these custom attributes, by storing them in feature properties. ...
... The VDI 3682 [8] provides a visual and formal representation xxxxx ©2023 IEEE of the PPR approach. The PPR-DSL [9] provides a domainspecific language that complements the notation. ...
... In PIA.3 the knowledge should be modeled as reusable artifacts. PPR modeling is a promising approach to achieve this, e.g., by using the PPR-DSL [9]. To conduct domain and system modeling and work out common concepts, various collaboration approaches seem promising. ...
In Cyber-Physical Production System (CPPS) engineering, multi-domain teams work concurrently and iteratively on a variety of assets to design and build (parts of) a CPPS. Previous work has shown that engineering assets can be organized in a Multi-Domain Engineering Graph (MDEG). However, the engineering assets for such system components must be continuously adapted, tested, and validated due to changing requirements and conditions. This paper investigates how a change impact analysis in multi-domain work environments can be organized to improve the change management process in the CPPS engineering lifecycle. We outline an agile framework in the context of the VDI 3695 activities for the adaptation and usage of change impact analysis techniques and tools for a multi-domain environment based on a common knowledge base, which is promising in terms of cost-savings and quality assurance. Additionally, we provide a research agenda that outlines research directions to implement such an approach for real-world usecases.
... The VDI 3682 [8] provides a visual and formal representation xxxxx ©2023 IEEE of the PPR approach. The PPR-DSL [9] provides a domainspecific language that complements the notation. ...
... In PIA.3 the knowledge should be modeled as reusable artifacts. PPR modeling is a promising approach to achieve this, e.g., by using the PPR-DSL [9]. To conduct domain and system modeling and work out common concepts, various collaboration approaches seem promising. ...
In Cyber-Physical Production System (CPPS) engineering, multi-domain teams work concurrently and iteratively on a variety of assets to design and build (parts of) a CPPS. Previous work has shown that engineering assets can be organized in a Multi-Domain Engineering Graph (MDEG). However, the engineering assets for such system components must be continuously adapted, tested, and validated due to changing requirements and conditions. This paper investigates how a change impact analysis in multi-domain work environments can be organized to improve the change management process in the CPPS engineering lifecycle. We outline an agile framework in the context of the VDI 3695 activities for the adaptation and usage of change impact analysis techniques and tools for a multi-domain environment based on a common knowledge base. Additionally, we provide a research agenda that outlines research directions to implement such an approach for real-world use cases.
... To program welding robots, information is required concerning the product design, the process and the resources needed to perform the weldments [9]. The systematic overview on product-process-resource information is also known as the "PPR perspective" and it is formalised in existing literature through PPR models [10][11][12]. PPR models include in their scope details about the resource capability, or skill required to conduct the manufacturing processes necessary to product an item. Brecher et al. and Ferrer et al. use PPR models to particularly formalize the process required and the skills needed to sustain assembly operations. ...
This paper describes a novel end-to-end approach for automatic welding-robot programming based on a product-process-resource (PPR) model, for one-of-a-kind manufacturing systems. For welding-robot programming to be possible, in a one-of-a-kind manufacturing system, a large range of information about the product is required e.g., customer requirements, product design features, manufacturing process parameters and resource capability. Traditionally, this information is processed and transferred along the manufacturing organisation’s value chain by using several stand-alone digital systems which require extensive human input and high skill to operate. A PPR model is proposed through this research as a platform for storing and processing the necessary information along the value chain seamlessly. This is achieved through the digital integration of CAD software tools compliant with the ISO 2553:2019 standard, and offline programming systems (OLP) for welding-robots. The PPR model enables the automatic programming of welding robots and drastically reduces human input. The applicability in manufacturing of the theoretical concept is demonstrated through technical implementations tested in laboratory and on the value chain of an engineering-to-order (ETO) industrial partner involved in the metal fabrication industry. The experiments were conducted by creating several products using the proposed artefact. Experiments show that automatic programming of welding robots can be achieved using PPR models, drastically reduce the human input necessary to obtain a welding-robot program, and drastically reduce the ETO product’s lead time.
... PPR modeling is based on the three main aspects of a production system: (1) products with their properties, (2) processes that produce products, and (3) resources that execute production processes. Meixner et al. [20] introduced the PPR-Domain Specific Language (PPR-DSL), a machine-readable and technologyagnostic language for PSE modeling. ...
In agile Cyber-physical Production System (CPPS) engineering, multi-disciplinary teams work concurrently and iteratively on various CPPS engineering artifacts, based on engineering models and Product-Process-Resource (PPR) knowledge, to design and build a production system. However, in such settings it is difficult to keep track of (i) the effects of changes across engineering disciplines, and (ii) their implications on risks to engineering quality, represented in Failure Mode and Effects Analysis (FMEA). To tackle these challenges and systematically co-evolve FMEA and PPR models, requires propagating and validating changes across engineering and FMEA artifacts. To this end, we design and evaluate a Multi-view FMEA+PPR (MvFMEA+PPR) meta-model to represent relationships between FMEA elements and CPPS engineering assets and trace their change states and dependencies in the design and validation lifecycle. We evaluate the MvFMEA+PPR meta-model in a feasibility study on the quality of a screwing process from automotive production. The study results indicate the MvFMEA+PPR meta-model to be more effective than alternative traditional approaches.
Purpose
Agile Production Systems Engineering (PSE) is characterised by parallel and iterative engineering of several disciplines. This multi-view engineering requires capabilities for tracing changes to support configuration management of PSE assets. Yet, traditional model transformation approaches in PSE do not preserve local views and hierarchies on concepts of PSE assets, such as plans and configurations. Thus, tracing multi-view changes to PSE assets is challenging.
Method
Following the Design Science approach, we (i) elicit requirements for tracing multi-view changes to PSE assets from a domain analysis in automotive manufacturing; (ii) introduce and evaluate the Traceable Multi-view Model Transformation (TMvMT) process; and (iii) propose the TMvMT pipeline architecture to provide traceable model integration capabilities for agile PSE.
Results
In a feasibility study on robot cell models, we evaluate the TMvMT process and architecture regarding the requirements for traceability compared to traditional approaches.
Conclusion
The proposed TMvMT approach provides traceability of changes in multi-view modelling as a basis through the separation of modelling transformation steps and provision of clear input and output artefacts to achieve traceable configuration management and validation of system designs for production system assets in agile PSE.
“Data is the new oil” is a frequently pronounced statement. It is expected that intelligent utilization of information will change economies. With respect to production systems this fact can become reality by utilizing the Industry 4.0 Asset Administration Shell. This paper describes ways to fill and exploit the data treasure with respect to production system engineering data, by highlighting the importance of multi-modelling of production systems.
In agile Production Systems Engineering (PSE), multi-disciplinary teams work concurrently on various PSE artifacts in an iterative process that can be supported by common concept and Product-Process-Resource (PPR) modeling. However, keeping track of the interactions and effects of changes across engineering disciplines and their implications for risk assessment is exceedingly difficult in such settings. To tackle this challenge and systematically co-evolve Failure Mode and Effects Analysis (FMEA) and PPR models during PSE, it is necessary to propagate and validate changes across engineering artifacts. To this end, we design and evaluate a FMEA-linked-to-PPR assets (FMEA+PPR) meta model to represent relationships between FMEA elements and PSE assets and trace their change states and dependencies in the design and validation lifecycle. Furthermore, we design and evaluate the FMEA+PPR method to efficiently re-validate FMEA models upon changes in multi-view PSE models. We evaluate the model and method in a feasibility study on the quality of a joining process automated by a robot cell in automotive PSE. The study results indicate that the FMEA+PPR method is feasible and addresses requirements for FMEA re-validation better than alternative traditional approaches. Thereby, the FMEA+PPR approach facilitates a paradigm shift from traditional, isolated PSE and FMEA activities towards an integrated agile PSE method.
Cyber-Physical Production Systems (CPPSs) are constantly evolving, highly configurable, complex software-intensive systems interacting with their environment. The variability of CPPSs must be well-documented to foster reuse, for which the Software Product Line (SPL) community proposed variability models. Unfortunately, industry is mostly unaware of existing variability modeling approaches and frequently develops custom artifacts to document variability, e.g., spreadsheets or Domain-Specific Languages (DSLs). In contrast to SPL variability models, the evolution of these custom artifacts is hardly researched and evolving them remains a tedious and error-prone manual task in practice. In this paper, using two CPPS case studies, we investigate the impact of system evolution on custom artifacts and feature models as a basis for further research. We discuss how feature models could benefit the evolution of DSL-based variability artifacts.
KeywordsVariability modelingVariability evolutionCustom variability artifactsFeature modelsCyber-physical production system
To engineer large, complex, and interdisciplinary systems, modeling is considered as the universal technique to understand and simplify reality through abstraction, and thus, models are in the center as the most important artifacts throughout interdisciplinary activities within model-driven engineering processes. Model-Driven Systems Engineering (MDSE) is a systems engineering paradigm that promotes the systematic adoption of models throughout the engineering process by identifying and integrating appropriate concepts, languages, techniques, and tools. This chapter discusses current advances as well as challenges towards the adoption of model-driven approaches in cyber-physical production systems (CPPS) engineering. In particular, we discuss how modeling standards, modeling languages, and model transformations are employed to support current systems engineering processes in the CPPS domain, and we show their integration and application based on a case study concerning a lab-sized production system. The major outcome of this case study is the realization of an automated engineering tool chain, including the languages SysML, AML, and PMIF, to perform early design and validation.
One of the most significant directions in the development of computer science and information and communication technologies is represented by Cyber-Physical Systems (CPSs) which are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the internet. Cyber-Physical Production Systems (CPPSs), relying on the newest and foreseeable further developments of computer science, information and communication technologies on the one hand, and of manufacturing science and technology, on the other, may lead to the 4th Industrial Revolution, frequently noted as Industry 4.0. The key-note will underline that there are significant roots generally – and particularly in the CIRP community – which point towards CPPSs. Expectations and the related new R&D challenges will be outlined.
Two paradigms characterize much of the research in the Information
Systems discipline: behavioral science and design science. The behavioral-science
paradigm seeks to develop and verify theories that explain or predict
human or organizational behavior. The design-science paradigm seeks
to extend the boundaries of human and organizational capabilities
by creating new and innovative artifacts. Both paradigms are foundational
to the IS discipline, positioned as it is at the confluence of people,
organizations, and technology. Our objective is to describe the performance
of design-science research in Information Systems via a concise conceptual
framework and clear guidelines for understanding, executing, and
evaluating the research. In the design-science paradigm, knowledge
and understanding of a problem domain and its solution are achieved
in the building and application of the designed artifact. Three recent
exemplars in the research literature are used to demonstrate the
application of these guidelines. We conclude with an analysis of
the challenges of performing high-quality design-science research
in the context of the broader IS community.
A domain-specific language (DSL) provides a notation tailored towards an application domain and is based on the relevant concepts and features of that domain. As such, a DSL is a means to describe and generate members of a family of programs in the domain. A prerequisite for the design of a DSL is a detailed analysis and structuring of the application domain. Graphical feature diagrams have been proposed to organize the dependencies between such features, and to indicate which ones are common to all family members and which ones vary. In this paper, we study feature diagrams in more details, as well as their relationship to domain-specific languages. We propose the Feature Description Language (FDL), a textual language to describe features. We explore automated manipulation of feature descriptions such as normalization, expansion to disjunctive normal form, variability computation and constraint satisfaction. Feature descriptions can be directly mapped to UML diagrams which in their turn can be used for Java code generation. The value of FDL is assessed via a case study in the use and expressiveness of feature descriptions for the area of documentation generators. 1998 ACM Computing Classification System: D.2.2, D.2.9, D.2.11, D.2.13. Keywords and Phrases: Domain engineering, tool support, software product lines, UML, constraints. Note: To appear in the Journal of Computing and Information Technology, 2001. Note: Work carried out under CWI project SEN 1.2, Domain-Specific Languages, sponsored by the Telematica Instituut. 1 1
Multi-disciplinary data exchange still poses many challenges: Heterogeneous data sources, diverging data views, and lack of communication lead to defects, late resolving of errors, and mismatches over the project lifecycle. Semantic approaches such as ontologies are a viable solution to derive common concepts between disciplines to limit negative effects in their collaboration. However, the application of these semantic approaches is still quite limited due to its inherent complexity. The purpose of this paper, is to discuss the concept of local glossaries as a step towards a Common Concept Glossary (CCG) method: A tool-supported method to enable and simplify the creation of common concepts derived from local glossaries that are built by discipline-specific workgroups. The local concepts can aid by making changes visible and enabling traceability and maintainability of common models between different disciplines.
Software and systems engineering combine artifacts from diverse domains and tools. This article explores how incremental consistency checking is able to automatically and continuously detect inconsistencies among these artifacts.
The Internet of Things and Services opens new perspectives for goods and value-added services in various industrial sectors. Engineering of industrial products and of industrial production systems is a multi-disciplinary, model- and data-driven engineering process, which involves engineers coming from several engineering disciplines. These engineering disciplines exploit a variety of engineering tools and information processing systems. This book discusses challenges and solutions for the required information processing and management capabilities within the context of multi-disciplinary engineering of production systems. The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) the product to be produced by (2) a production process executed on (3) a production system resource.
This chapter motivates the need for better approaches to multi-disciplinary engineering (MDE) for cyber-physical production systems (CPPS) and provides background information for non-experts to explain the interaction between production engineering, production systems engineering, and enabling contributions from informatics. Furthermore, the chapter introduces a set of research questions and provides an overview on the book structure, chapter contributions, and benefits to the target audiences.
The increasing challenge to manufacture individual products in short periods of time necessitates a huge amount of machine variants. Therefore, the efforts in engineering as well as in managing the variability increase. An adequate support in modelling such variant-rich systems enhances reuse of variable parts of the machine and, by that, promises an improvement of efficiency during development. To provide a first step into this direction, this paper analyses the applicability of an interdisciplinary product line approach as one means to improve the engineering in the machine manufacturing domain.
Objects to change within a manufacturing enterprise can be products, technological or logistical processes, parts of the manufacturing facilities or a company's organization. For this paper we assume, that IT systems are also objects to change – they have to be adapted to changes to products and facilities on the shop floor. Today the adaption of IT systems is managed and done manually – therefore the authors propose an automated way of changing the production's IT-systems. For this purpose two main ideas are described: reading and interpreting a self-description of production equipment and enrichment of these descriptions with data from the “digital factory” bridging the gap between planning and operating IT-systems and thus enabling higher adaptivity of manufacturing systems.
Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.
Praise for The Object Constraint Language, Second Edition“MDA promises a revolution in the way we develop software. This book is essential reading for anyone intending to adopt MDA technology.” ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ -Tony Clark, PhD ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ King's College, London“Through examples, Jos and Anneke demonstrate the power and intuitiveness of OCL, and the key role that this language plays in implementing and promoting MDA. The theme, structure, contents, and, not lastly, the clarity of explanations recommend this book as the best advocate for learning, using, and promoting OCL, UML, and MDA. I am sure that this work will contribute in a significant manner to the development and widespread use of new software technologies.” ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ -Dan Chiorean ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ Head of the Computer Science Research Laboratory ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ ï¾ Babes-Bolyai University, Cluj"In this thoroughly revised edition, Jos and Anneke offer a concise, pragmatic, and pedagogic explanation of the Object Constraint Language (OCL) and its different applications. Their discussion of OCL's potential role in Model Driven Architecture (MDA) is timely and offers great insight into the way that UML can be taken to the next level of automated software development practice. I highly recommend this book to anyone who is looking to get the most out of UML."-Shane Sendall, PhD, Senior Researcher, Swiss Federal Institute of Technology in LausanneThe release of Unified Modeling Language (UML) 2.0 places renewed emphasis on the Object Constraint Language (OCL). Within UML, OCL is the standard for specifying expressions that add vital information to object-oriented models and other object-modeling artifacts. Model Driven Architecture (MDA) relies on OCL to add the level of programming detail necessary to enable platform-specific models (PSM) to communicate with platform-independent models (PIM).This book is a practical, accessible guide to OCL for software architects, designers, and developers. Much care has been taken during the redesign of OCL to ensure that the syntax remains readable and writable by the average software modeler. The Object Constraint Language, Second Edition, utilizes a case study to show how to exercise these compact but powerful expressions for maximum effect.This newly updated edition Explains why OCL is critical to MDA--and why UML alone is not enough Introduces an SQL-like syntax to OCL Defines the new language constructs of OCL 2.0 Demonstrates how OCL can be incorporated into code Shares tips and tricks for applying OCL to real-world modeling challenges-showing which can be solved with UML and which require OCLUsing a combination of UML and OCL allows developers to realize the effective, consistent, and coherent models that are critical to working with MDA. The authors' pragmatic approach and illustrative use of examples will help application developers come quickly up to speed with this important object-modeling method-and will serve as a ready reference thereafter.
We describe our experiences with the process of designing a domain-specific language (DSL) and corresponding model transformations. The simultaneous development of the language and the transformations has lead to an iterative evolution of the DSL. We identified four main influences on the evolution of our DSL: the problem domain, the target platforms, model quality, and model transformation quality. Our DSL is aimed at modeling the structure and behavior of distributed communicating systems. Simultaneously with the development of our DSL, we implemented three model transformations to different formalisms: one for simulation, one for execution, and one for verification. Transformations to each of these formalisms were implemented one at the time, while preserving the validity of the existing ones. The DSL and the formalisms for simulation, execution, and verification have different semantic characteristics. We also implemented a number of model transformations that bridge the semantic gaps between our DSL and each of the three formalisms. In this paper, we describe our development process and how the aforementioned influences have caused our DSL to evolve.
A Domain-Specific Language for Connecting Product-Process-Resource Models with Dependencies
- J Decker
- H Marcher
J. Decker and H. Marcher, "A Domain-Specific Language for Connecting Product-Process-Resource Models with Dependencies," CDL-SQI, Institute for Information Systems Engineering, TU Wien, Technical
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- C J Date
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