This paper is the second part of a four-part series concerning the development and deployment of Systems Engineering. In this paper we tackle the technical processes and the requirements from three key and recognized systems engineering documents respectively, ISO/IEC/IEEE 15288, ISO/IEC/IEEE 29148 and the INCOSE Systems Engineering Handbook. The authors explain, adapt and then exploit a suite of tools and methods including IPOs (Inputs-Processes-Outputs), ConOps, Requirements specification documents, to develop an approach that concludes with a ‘Technical Processes Matrix’ and tailoring framework. This suite is exercised within the context of product development processes (PDP) of complex systems. The paper concludes with several key findings to explain the challenges faced by organizations when developing and deploying SE with special emphasis on process assessment and SE relevant process tailoring.
High-energy physic experiments are complex systems. The particle detectors, the electronics for data selection and acquisition, the services, and the mechanical support structures are all integrated in a highly crowded and optimized space. The size and sophistication of these systems have been constantly growing during the last decades. This note summarizes some basic common characteristics of these apparatuses and describes how these concepts are implemented in several experiments under design or construction to study the behaviour of neutrinos. Neutrinos are intriguing particles: they have no electrical charge, much smaller mass than the other particles and weakly interact with matter. The Standard Model of particle physics as it is today cannot explain some of their measured properties. Therefore, the neutrino studies are gaining importance in the field of high-energy physic. One hundred and seventy-five research institutes all over the world have established a common important programme of experiments. It foresees the construction of a series of detectors from small prototypes to large elements operating in liquid argon cryogenic environment. The first prototypes have a size of a few cubic meters while the ultimate detector will be in four elements 22.4 m x 14 m x 45.6 m each. One of these elements will contain about 17’000 tonnes of liquid argon. They will be located in an old mine in South Dakota. The cavern is 1500 m below the ground level, a challenge for the transport and assembly of all the components. As final example, I describe the design and construction of the ICARUS experiment aluminium cryostats. This experiment is one of the milestones of the neutrino programme and it makes use of the largest liquid argon Time Projector Chamber built and operated so far with a bath of approximately 760
Large industrial information systems are composed of dozens of inter-operating software applications. Each of them implements a relatively independent set of functions but also participates to business processes involving more applications. Applications may be COTS acquired from different vendors or custom-developed. The network of them evolves and grows in time. Many development groups/vendors manage the network. All these characteristics support the idea that large information systems may be interpreted as Systems of Systems (SoS) and that this view may provide value to IT managers. In the paper, we present an experience report of SoS concepts application to the information system of a large retail company. In this System of Systems, a critical problem is the absence of documents providing SoS views of the whole information system: the set of applications, their relationships and the impact of business processes on the network of applications. To mitigate the problem, we developed a set of models using the minimalist approach (the selection of the minimal set of documents based on a cost/benefit analysis) and the ArchiMate modeling standard and tools. A static view (software applications and relations) and dynamic views (business processes and their interaction with software applications) model each business area. We discuss the current use and benefits of the models and the forecast improvements.
In modern Software Engineering, Continuous Delivery (CD) is a development approach in which a software is iteratively developed in short cycles ensuring, for each cycle, that the new features are available to end users as soon as they are implemented and tested. CD aims at defining, building and releasing software with greater speed and frequency through the deployment pipeline resulting in three major benefits, visibility, feedback and continuous deployment respectively, enabling the software functional items to efficiently flow from development to production. In this domain, the need for evaluating the performance of the deployment pipeline emerges, since the conventional metrics available in the software engineering discipline are not suited to handle all the involved aspects. In this paper, the metrics suited for supporting CD are introduced and an integration with Modeling and Simulation (M&S) techniques is discussed, based on the Business Process Model and Notation (BPMN) standard, which could represent a valid support offering a graphical notation to easily specify the deployment pipeline steps as a standard and repeatable process. The main objective is to identify feasible perspectives in which simulation methods and principles can be exploited, thus evaluating the effectiveness of M&S to support performance analysis of a deployment pipeline, seen as a predictable process. Specifically, M&S can be seen as an enabling tool for the evaluation and comparison of different CD choices against requirements through an effective implementation of simulation techniques and virtual testing.
The Systems Engineering approach and practices have been key success factors for developing Telematic Hub for Insurance Industry as a real solution for production helping to meet customer specific requirements since the first provided input. Telematic Hub aims to leverage data coming from possible existing motor solutions and to extend/expand telematic capabilities in order to easily respond and adapt to insurance industry business model changes. This innovative solution offers full support for three logical layers: Connected Devices, IoT Analytics and Big Data. Systems Engineering adopted practices will be discussed for developing the Telematic Hub solution going from concept to production and operation.
The human unreliability is the main cause of industrial accidents. In the petrochemical field, about 90% of accidents are due to human errors. Over the years, several models of Human Reliability Analysis have been developed. The major limitation of these models is due to their static nature. Thus, the present research aims to propose a new innovative approach to evaluate the variability of the human error probability between related activities in complex systems using a resilience engineering approach.. Research integrates an HRA evaluation model with a resilience engineering model called Functional Resonance Analysis Model to assess the human error variability. The methodology is applied in a real case study for the emergency management in a petrochemical company.
