7,706 research outputs found

    Special Session on Industry 4.0

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    Light at the end of the tunnel:Synthesis-based engineering for road tunnels

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    An Ontological Approach to Representing the Product Life Cycle

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    The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end of life. We call this suite the Product Life Cycle (PLC) Ontologies. The suite extends proximately from The Common Core Ontologies (CCO) used widely in defense and intelligence circles, and ultimately from the Basic Formal Ontology (BFO), which serves as top level ontology for the CCO and for some 300 further ontologies. The PLC Ontologies were developed together, but they have been factored to cover particular domains such as design, manufacturing processes, and tools. We argue that these ontologies, when used together with standard public domain alignment and browsing tools created within the context of the Semantic Web, may offer a low-cost approach to solving increasingly costly problems of data management in the manufacturing industry

    Structural Synthesis for GXW Specifications

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    We define the GXW fragment of linear temporal logic (LTL) as the basis for synthesizing embedded control software for safety-critical applications. Since GXW includes the use of a weak-until operator we are able to specify a number of diverse programmable logic control (PLC) problems, which we have compiled from industrial training sets. For GXW controller specifications, we develop a novel approach for synthesizing a set of synchronously communicating actor-based controllers. This synthesis algorithm proceeds by means of recursing over the structure of GXW specifications, and generates a set of dedicated and synchronously communicating sub-controllers according to the formula structure. In a subsequent step, 2QBF constraint solving identifies and tries to resolve potential conflicts between individual GXW specifications. This structural approach to GXW synthesis supports traceability between requirements and the generated control code as mandated by certification regimes for safety-critical software. Synthesis for GXW specifications is in PSPACE compared to 2EXPTIME-completeness of full-fledged LTL synthesis. Indeed our experimental results suggest that GXW synthesis scales well to industrial-sized control synthesis problems with 20 input and output ports and beyond.Comment: The long (including appendix) version being reviewed by CAV'16 program committee. Compared to the submitted version, one author (out of her wish) is moved to the Acknowledgement. (v2) Corrected typos. (v3) Add an additional remark over environment assumption and easy corner case

    Lessons learned in the application of formal methods to the design of a storm surge barrier control system

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    The Maeslantkering is a key flood defense infrastructural system in the Netherlands. This movable barrier protects the city and harbor of Rotterdam, without impacting ship traffic under normal circumstances. Its control system, which operates completely autonomously, must be guaranteed to work correctly even under extreme weather conditions, although it closes only sporadically. During its development in the 1990's, the formal methods Z and Spin were used to increase reliability. As the availability of industrial expert knowledge on these formal methods declines, maintaining the specifications defined back then has become cumbersome. In the quest for an alternative mathematically rigorous approach, this paper reports on an experience in applying supervisory control synthesis. This formal method was recently applied successfully to other types of infrastructural systems like waterway locks, bridges, and tunnels, with the purpose to ensure safe behavior by coordinating hardware components. Here, we show that it can also be used to coordinate several (controller) software systems. Additionally, we compare the lessons learned from the originally used formal methods and link Z to supervisory control synthesis

    Automated Verification and Generation of Flexible Automation Control

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    Consumer product life-cycles are constantly shortening; the automotive industry is an illustrative example. As a consequence, the introduction of new products into the manufacturing system necessarily becomes more frequent. Inherently, this brings a performance reduction for the manufacturing system. The reduced performance is caused by a down-time and a ramp-up-time. During the down-time the mechanical equipment is rebuilt and the new control programs are debugged. During ramp-up there are a large number of errors mainly caused by mechanical devices not being properly adjusted, bugs in the control programs and operators not used to new procedures. Thus, in order to maintain the productivity level and to achieve full cost-efficiency both the down-time and the ramp-up time must be reduced. One way to reduce these lead times is to verify the control programs in offline mode. However, efficient and reliable offline verification requires some major improvements of the current development process of manufacturing systems. Information handling and development of control programs based on information reuse are the two most important improvement areas.The work presented here addresses four industrial problems related to this, lack of tools for offline verification of control programs, lack of information reuse in the development process of a manufacturing system, lack of operator support in error situations, and lack of tools for analyzing the control of complex manufacturing cells.We propose a development method where information from different tools in the development process of a manufacturing system is reused and processed by tools for verification and optimization. Then the control programs are generated by combining the processed information with a library of standardized software components. The proposed method solves the above-mentioned industrial problems without adding work to the development process. On the contrary, the amount of work will be reduced since the control program development will be automated and the time for debugging the control programs on the shop floor will be drastically reduced, due to the new mathematically based verification process
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