Compositional specification of functionality and timing of manufacturing systems

In this paper, a formal modeling approach is introduced for compositional specification of both functionality and timing of manufacturing systems. Functionality aspects can be considered orthogonally to the timing. The functional aspects are specified using two abstraction levels; high-level activities and lower level actions. Design of a functionally correct controller is possible by looking only at the activity level, abstracting from the different execution orders of actions. Furthermore, the specific timing of actions is not needed. As a result, controller designcan be performed on a much smaller state space compared to an explicit model where timing and actions are present. The performance of the controller can be analyzed and optimizedby taking into account the timing characteristics. Since formal semantics are given in terms of a (max, +) state space, various existing performance analysis techniques can be used. Weillustrate the approach, including performance analysis, on an example manufacturing system

Primary central nervous system lymphomas: incidence and survival in the Southern and Eastern Netherlands.

Item does not contain fulltextBACKGROUND: An excessive increase in the incidence of primary central nervous system lymphoma (PCNSL) has been reported since the mid-1980s in the U.S. and U.K. Clinical studies have shown that radiotherapy and chemotherapy may prolong survival. In the current study, the authors describe the incidence, treatment, and survival of an unselected group of patients with PCNSL in the southern and eastern Netherlands. METHODS: Data regarding patients diagnosed between 1989-1994 were obtained from 4 population-based regional cancer registries in the southern and eastern Netherlands (n = 86) and the Eindhoven Cancer Registry for 1980-1988 (n = 6). Lymphomas were registered as PCNSL when a tissue diagnosis of CNS lymphoma was established for a patient with neurologic symptoms (i.e., lymphomas were not necessarily restricted to the CNS at the time of diagnosis). Only patients diagnosed during their lifetime with Stage I disease, Stage "IV" disease (i.e., diffuse CNS lymphoma), or disease of unknown stage were included (63 patients, 8 patients, and 15 patients, respectively, between 1989-1994). For 80 patients (93%) follow-up was complete until January 1, 1997. RESULTS: Between 1989-1994, an average World Standardized Rate of 2.3 cases and 1.7 cases per 1 million person-years, respectively, was reported for males and females. The median age of the patients at the time of diagnosis was 62 years, and was 66 years for patients with an unknown disease stage. In the area of the Eindhoven Cancer Registry the occurrence of PCNSL more than doubled from or = 60 years. CONCLUSIONS: The increase in the incidence of PCNSL in the 1980s may be explained in large part by changes in diagnostics and registration. The relatively high incidence and low survival rate of PCNSL in the southern and eastern Netherlands reported in the 1990s may be due in part to the inclusion of patients with systemic lymphoma and immunodeficiency disorders. However, a significant improvement in the prognosis of patients with PCNSL in the southern and eastern Netherlands diagnosed in the 1990s is unlikely

Partial-Order Reduction for Supervisory Controller Synthesis

A key challenge in the synthesis and subsequent analysis of supervisory controllers is the impact of state-space explosion caused by concurrency. The main bottleneck is often the memory needed to store the composition of plant and requirement automata and the resulting supervisor. Partial-order reduction (POR) is a well-established technique that alleviates this issue in the field of model checking. It does so by exploiting redundancy in the model with respect to the properties of interest. For controller synthesis, the functional properties of interest are nonblockingness, controllability, and least-restrictiveness, but also performance properties, such as throughput and latency are of interest. We propose an on-the-fly POR on the input model that preserves both functional and performance properties in the synthesized supervisory controller. This improves the scalability of the synthesis (and any subsequent performance analysis). Synthesis experiments show the effectiveness of the POR on a set of realistic manufacturing system models

Modular model-based supervisory controller design for wafer logistics in lithography machines

Development of high-level supervisory controllers is an important challenge in the design of high-tech systems. It has become a significant issue due to increased complexity, combined with demands for verified quality, time to market, ease of development, and integration of new functionality. To deal with these challenges, model-based engineering approaches are suggested as a cost-effective way to support easy adaptation, validation, synthesis, and verification of controllers. This paper presents an industrial case study on modular design of a supervisory controller for wafer logistics in lithography machines. The uncontrolled system and control requirements are modeled independently in a modular way, using small, loosely coupled and minimally restrictive extended finite automata. The multiparty synchronization mechanism that is part of the specification formalism provides clear advantages in terms of modularity, traceability, and adaptability of the model. We show that being able to refer to variables and states of automata in guard expressions and state-based requirements, enabled by the use of extended finite automata, provides concise models. Additionally, we show how modular synthesis allows construction of local supervisors that ensure safety of parts of the system, since monolithic synthesis is not feasible for our industrial case

Identifying bottlenecks in manufacturing systems using stochastic criticality analysis

System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system

Eclipse ESCET™: The Eclipse Supervisory Control Engineering Toolkit

The Eclipse Supervisory Control Engineering Toolkit (ESCET™) is an open-source project to provide a model-based approach and toolkit for developing supervisory controllers, targeting their entire engineering process. It supports synthesis-based engineering of supervisory controllers for discrete-event systems, combining model-based engineering with computer-aided design to automatically generate correct-by-construction controllers. At its heart is supervisory controller synthesis, a formal technique for the automatic derivation of supervisory controllers from the unrestricted system behavior and system requirements. Vital for the future development of these techniques and tools is the ESCET project’s open environment, allowing industry and academia to collaborate on creating an industrial-strength toolkit. We report on some crucial developments of the toolkit in the context of research projects with Rijkswaterstaat and ASML that have considerably improved its capability to deal with the complexity of real-life systems as well as its usability