In this paper, a novel chatbot for risk reduction as an aid during machinery design is presented. The general workflow of the chatbot involves the identification of the hazard described by the user using a neural network model followed by an interactive dialog based conversation, in which the risk reduction measures are outlined. A prototype implementation of the chatbot presents the steps to generate and pre-process the training data for Artificial Intelligence (AI) based models. Different neural network models are trained and evaluated for the proposed risk reduction chatbot. A comparative study is presented by employing an in-depth qualitative and quantitative evaluation. The work presented in this paper shows significant promise in ensuring safety awareness, thereby aiding in implementing functional safety in the early stages of machinery design and development.

The use of Artificial Intelligence (AI) in machinery functional safety can enhance efficiency and accuracy by automating tasks previously carried out by humans. This paper presents an experimental evaluation of Neural Network (NN) models for hazard identification in machinery functional safety. The systematic study includes own implementations of NN models using open source building blocks and the use of an open source conversational AI framework with various pipeline configurations. The paper provides a comparative analysis of the qualitative and quantitative parameters for the models and configurations.

Standards such as ISO 13849 and ISO 12100 enable users to model safety related control elements with safety functions, according to a specified architecture and required performance level. In this direction, a novel Artificial Intelligence (AI)-based assistant is introduced in this paper to aid in determining the required performance level parameter by indulging the user in a dialog-based conversation regarding hazard scenarios. This will help inexperienced machinery safety personnel (e.g. mechanical engineer) to get an overview of the safety engineering aspects, before consulting with safety experts for risk assessment.

In the domain of embedded systems, the complexities involved in embedded software development are being successfully addressed by the emerging field of model-based software development and testing. However, in embedded systems, the underlying embedded software is often expected to collaborate with various hardware, mechanical, electrical modules/technologies. To address this aspect of heterogeneity in embedded systems, practitioners of model-based embedded software engineering are required to use more than one modeling language. This is essential to address the multi-faceted design aspects/requirements of an embedded system. This paper elaborates on the existing data interchange and coupling mechanisms between embedded software sub-systems modeled using UML and Matlab/Simulink. While there are some existing coupling mechanisms for data exchange among heterogenous modeling domains, they are all not applicable to all real-time operating systems and/or limited to a few simulation studies. This paper addresses the aforementioned gaps and proposes a simple, generic methodology for data exchange between events (in UML domain) and signals (in Matlab/Simulink domain). The proposed approach is elaborated using a seesaw (real-word) embedded software system application scenario example. Initial prototype implementation of the proposed approach, experimental results and some future directions are outlined.

The existing model-based tools employ runtime monitoring methodologies for debugging and testing of embedded systems. In these tools, the additional instrumentation for incorporating and executing the test code varies based on the application. Such techniques could also introduce significant, non-deterministic overhead in the embedded system. This is a hurdle in applying Model-Based Testing (MBT) for resource constrained embedded systems and industrially relevant examples. To address this gap, this paper elaborates on the monitoring methodology used in a test framework for executing the model-based test cases in the embedded system. Two variants of the proposed monitoring methodology, (a) software and (b) on-chip monitoring are discussed. An empirical evaluation based on a prototype implementation of the proposed runtime monitoring mechanisms is discussed.

The growing variety and complexity of embedded software development necessitates the usage of structured embedded software engineering and automation approaches such as the model-driven methodology. Whereas there are several modeling domains and tools to support embedded software development, coupling of embedded software subsystems developed using heterogeneous modeling domains is still an emerging field. This paper outlines a novel approach towards the development of a generic middleware aimed at automated source codelevel coupling of embedded software-subsystems developed using heterogeneous modeling domains (e.g. UML, Matlab/Simulink). The proposed approach, initial results and future directions are outlined.

Model-based approaches to develop software for embedded systems are becoming increasingly important in the last ten years. In this context, it is desirable to carry out debugging at the model level in conjunction with the model-based development of embedded software. This paper presents such a model-based debugging approach which can be used to visualize the behaviour of embedded software on a host PC. The various constraints in embedded software development and execution pose a big challenge to monitor the embedded system without affecting its runtime behaviour. The focus of this work is to describe the underlying monitoring mechanism and the methodology to visualize the embedded system behaviour in real time. This includes different approaches to get the trace data from the target without or with minimal influence on the runtime behaviour of the monitored embedded system.

Model driven design and development of real-time embedded systems has been gaining a lot of attention in the recent past. It is imperative for a hard real-time embedded system to execute and respond to sequenced exchanges of messages under critical temporal constraints. The UML provides artifacts such as communication diagrams, sequence diagrams and timing diagrams to aid software engineers to model and precisely document such a schedule of interactions or state changes at the design level. While modeling at the design level is interesting on one hand, it is also significant to understand the run time behavior of the embedded software. A step forward in this direction is to provide a real-time representation of the target system behavior on the host side. We propose an approach to realize a target debugger on the host side with a monitor solution in the target side. With the back annotated information from the target, a visual representation of the system behavior in real-time is now available at the design level. This way, a debugging solution in real-time is provided, thus taking a step forward towards understanding the behavior of the embedded software at hand. We illustrate our proposed approach with a prototype and examples.

The LK3S approach uses FIPA compliant agent technology to realize a flexible and easy to configure decisionmaking on embedded devices. The agents are developed by using the LK3S configuration application generating an agent description out of UML diagrams. To enable agents on embedded systems with limited resources an LK3S embedded agent framework (LEAF) is created, which uses the agent management system and domain facilitator of the hosting agent system in LK3S (JADE).