Concurrent Design of Embedded Control Software

Embedded software design for mechatronic systems is becoming an increasingly time-consuming and error-prone task. In order to cope with the heterogeneity and complexity, a systematic model-driven design approach is needed, where several parts of the system can be designed concurrently. There is however a trade-off between concurrency efficiency and integration efficiency. In this paper, we present a case study on the development of the embedded control software for a real-world mechatronic system in order to evaluate how we can integrate concurrent and largely independent designed embedded system software parts in an efficient way. The case study was executed using our embedded control system design methodology which employs a concurrent systematic model-based design approach that ensures a concurrent design process, while it still allows a fast integration phase by using automatic code synthesis. The result was a predictable concurrently designed embedded software realization with a short integration time

Factory modelling: data guidance for analysing production, utility and building architecture systems

Work on energy and resource reduction in factories is dependent on the availability of data. Typically, available sources are incomplete or inappropriate for direct use and manipulation is required. Identifying new improvement opportunities through simulation across factory production, utility and building architecture domains requires analysis of model feasibility, particularly in terms of system data composition, input resolution and simulation result fidelity. This paper reviews literature on developing appropriate model data for assessing energy and material flows at factory level. Gaps are found in guidance for analysis and integration of resource-flows across system boundaries. The process for how data was prepared, input and iteratively developed alongside conceptual and simulation models is described. The case of a large-scale UK manufacturer is presented alongside discussions on challenges associated with factory level modelling, and the insights gained from understanding the effect of data clarity on system performance

A derivative-free approach for a simulation-based optimization problem in healthcare

Hospitals have been challenged in recent years to deliver high quality care with limited resources. Given the pressure to contain costs,developing procedures for optimal resource allocation becomes more and more critical in this context. Indeed, under/overutilization of emergency room and ward resources can either compromise a hospital's ability to provide the best possible care, or result in precious funding going toward underutilized resources. Simulation--based optimization tools then help facilitating the planning and management of hospital services, by maximizing/minimizing some specific indices (e.g. net profit) subject to given clinical and economical constraints. In this work, we develop a simulation--based optimization approach for the resource planning of a specific hospital ward. At each step, we first consider a suitably chosen resource setting and evaluate both efficiency and satisfaction of the restrictions by means of a discrete--event simulation model. Then, taking into account the information obtained by the simulation process, we use a derivative--free optimization algorithm to modify the given setting. We report results for a real--world problem coming from the obstetrics ward of an Italian hospital showing both the effectiveness and the efficiency of the proposed approach

A Framework for Executable Systems Modeling

Systems Modeling Language (SysML), like its parent language, the Unified Modeling Language (UML), consists of a number of independently derived model languages (i.e. state charts, activity models etc.) which have been co-opted into a single modeling framework. This, together with the lack of an overarching meta-model that supports uniform semantics across the various diagram types, has resulted in a large unwieldy and informal language schema. Additionally, SysML does not offer a built in framework for managing time and the scheduling of time based events in a simulation. In response to these challenges, a number of auxiliary standards have been offered by the Object Management Group (OMG); most pertinent here are the foundational UML subset (fUML), Action language for fUML (Alf), and the UML profile for Modeling and Analysis of Real Time and Embedded Systems (MARTE). However, there remains a lack of a similar treatment of SysML tailored towards precise and formal modeling in the systems engineering domain. This work addresses this gap by offering refined semantics for SysML akin to fUML and MARTE standards, aimed at primarily supporting the development of time based simulation models typically applied for model verification and validation in systems engineering. The result of this work offers an Executable Systems Modeling Language (ESysML) and a prototype modeling tool that serves as an implementation test bed for the ESysML language. Additionally a model development process is offered to guide user appropriation of the provided framework for model building

Model Continuity in Discrete Event Simulation: A Framework for Model-Driven Development of Simulation Models.

Most of the well known modeling and simulation methodologies state the importance of conceptual modeling in simulation studies and they suggest the use of conceptual models during the simulation model development process. However, only a limited number of methodologies refers to howto move from a conceptual model to an executable simulation model. Besides, existing modeling and simulation methodologies do not typically provide a formal method for model transformations between the models in different stages of the development process. Hence, in the current M&S practice, model continuity is usually not fulfilled. In this article, a model driven development framework for modeling and simulation is in order to bridge the gap between different stages of a simulation study and to obtain model continuity. The applicability of the framework is illustrated with a prototype modeling environment and a case study in the discrete event simulation domain

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify and analyse a prominent example of adaptive system: robot swarms equipped with obstacle-avoidance self-assembly strategies. The analysis exploits the statistical model checker PVesta

Conceptual modelling: framework, principles, and future research

The conceptual modelling task in a simulation project is very important and yet is still generally regarded as more of an art than a science. The meaning and nature of conceptual modelling are discussed and a framework set out. The overall aim should be to choose the best model for the project and conceptual modelling can be viewed as a difficult optimisation problem that can be tackled effectively using a creative search process that develops alternative models and predicts their performance throughout the project. An experiment relating model characteristics to some aspects of performance is described and this type of experiment may inform the process of predicting model performance. Based on advice from the literature and my own previous work on conceptual modelling 17 principles of conceptual modelling are suggested. Conceptual modelling research is still at an early stage and ideas for future research are proposed