Safety analysis is often performed independent of the system design life cycle, leading to inconsistency between the system design and the safety artifact. Additionally, the process of generating safety artifacts is manual, time-consuming, and error-prone. As a result, safety analysis often requires rework , is expensive, and increases system development time. Several model-based systems engineering (MBSE) approaches have been developed to automatically generate certain safety artifacts. However, these approaches only cover part of the system design and safety life cycle. To truly leverage the benefits of MBSE, system design must be undertaken together with safety analysis for the entire life cycle, and multiple safety artifacts must be generated from the same model. Moreover, MBSE approaches that require a model transformation between the system design and the safety model suffer from the inability to automatically reflect changes made to a safety artifact in the system and the safety model. This paper presents a framework to integrate the entire system design and safety life cycle using an MBSE approach. Both the system design and the safety data are captured in a single SysML model, from which safety artifacts such as failure modes and effects analysis (FMEA) tables and fault trees are automatically generated. This framework ensures consistency between the system design and the safety analysis by requiring no model transformation, thus reducing the resources required for safety analysis. The proposed Integrated System Design and Safety (ISDS) framework comprises three phases that together cover the entire system design and safety life cycle. In this paper, the application of Phase 1 of the framework to a real-world case study is demonstrated. INDEX TERMS Model-based systems engineering (MBSE), safety analysis, fault tree analysis (FTA), failure modes and effects analysis (FMEA), systems engineering, hazard analysis, SysML

Twenty-first century systems engineering is no longerdocument-centric; instead, it is model-centric. Model-centric systems engineering helps reduce ambiguity, increase clarity, and increase the analytics of the resulting complex systems. However, complex systems are governed by organizational policies that are still document-centric. Such policies are difficult to analyze, and gaps in policy can lead to major deficiencies in the resulting complex systems. This article introduces a framework for policy content modeling (PCM) and analysis. The framework represents the conceptual view and is supported by a step-by-step approach to achieve complete policy modeling and analysis. This approach was used with the intention of identifying and analyzing gaps in policy content and calculating policy toxicity, which negatively affects the resulting system. This framework and approach was also applied to Veterans Affairs (VA) and university policies. The VA PCM is conducted to discover toxicity in the policies and University policies modeling is done to graphically represent an undocumented policy and toxicity in the policy implementation. Index Terms-Complex systems policy, modeling, model-based systems engineering (MBSE), model centric systems engineering, policy, policy analysis. I. INTRODUCTION C OMPLEX engineered systems are manifestations of requirements derived from customer wants and needs. In addition to satisfying customer requirements, engineered systems must also adhere to policies, regulations, or standards established by the government, organization, technology, or interfaces [1], [2]. Public or corporate policies are typically documents that use natural-language, such as English to explain different organizational structures, definitions, rules, and regulations of conduct that dictate the resulting system [3]. Gaps in these policies can influence the outcome of the resulting system [4], [5]. Natural-language documents are not completely digital, and thus, they cannot be automatically analyzed or updated [3]. Another issue is that policies are not static entities; rather they are, dynamic, complex interdependent mazes of natural-language documents designed to accomplish a specific mission [6]. Most public, academic, and healthcare policies tend to be nonmachine-readable natural-language documents, which Manuscript

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The increased complexity of modern engineered systems has introduced novel challenges for assessing their safety early in the life cycle. For example, due to the iterative nature of the design and safety life cycle, there is constant data transformation and feedback of information between the system design models, safety analyses, and safety verification. Data transformation and feedback are often manually performed by engineers, which is time-consuming and error prone and can introduce inconsistencies in safety assessments. Although several model-based systems engineering approaches have been developed for safety analysis and safety verification, current approaches do not address the inconsistencies introduced in the safety assessment process. This study describes the Integrated System Design and Safety (ISDS) framework, which is a model-based safety assessment framework that aims to eliminate such inconsistencies. The framework combines a model-based safety analysis approach with a model-based safety verification. This paper extends previous work, which focused on the model-based safety analysis approach, to describe the model-based safety verification approach adopted in the ISDS framework. Safety verification is performed using a simulation-based fault injection approach and enabled by a fault injection engine, which injects failures into the system design and characterizes system behaviors to identify safety violations impacting the system. The results from the case study, in which the framework is used to assess the safety of a forward collision warning system, highlight that the algorithms and automated feedback loops of the framework can reduce inconsistencies in the safety assessment process while also identifying safety violations impacting the system.INDEX TERMS Model-based systems engineering (MBSE), safety analysis, failure modes and effects analysis (FMEA), systems engineering, SysML, simulation-based fault injection, safety verification.