Formal Requirements Engineering for Smart Industries: Toward a Model-Based Graphical Language

Borgne, Alexandre Le; Belloir, Nicolas; Bruel, Jean‐Michel; Nguyen, Thanh-Hung

doi:10.1109/uic-atc-scalcom-cbdcom-iop-smartworld.2016.0160

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…Specifically, a requirement is considered a combination of a condition (e.g., when flying), a carrier (e.g., the system), a property (e.g., power consumption), and a domain (e.g., less than 100 W) [29]. Similar patterns are found in the literature, such as check <condition> after <condition> within <time> [16]. While internally consistent, these definitions present two problems.…”

Section: Introductionmentioning

confidence: 94%

“…The majority of the literature in model-based requirements deals with aspects related to requirements management. Some examples include work on requirements traceability and allocation (e.g., [4,[15][16][17][18][19][20][21]) and modeling requirements engineering and management processes (e.g., [18,22]). However, as stated in the Introduction, such work does not address epistemological and structural aspects of model-based requirements.…”

Section: Introductionmentioning

confidence: 99%

“…Figure16. Requirements on the allocation of logical inputs and outputs to physical interfaces through which they must be conveyed.…”

mentioning

confidence: 99%

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Constructing True Model-Based Requirements in SysML

Salado

Wach

2019

Systems

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Some authors suggest that transitioning requirements engineering from the traditional statements in natural language with shall clauses to model-based requirements within a Model-Based Systems Engineering (MBSE) environment could improve communication, requirements traceability, and system decomposition, among others. Requirement elements in the Systems Modeling Language (SysML) fail to fulfill this objective, as they are really a textual requirement in natural language as a model element. Current efforts to directly leverage behavioral and structural models of the system lack an overarching theoretical framework with which to assess the adequacy of how those models are used to capture requirements. This paper presents an approach to construct true model-based requirements in SysML. The presented approach leverages some of SysML’s behavioral and structural models and diagrams, with specific construction rules derived from Wymore’s mathematical framework for MBSE and taxonomies of requirements and interfaces. The central proposition of the approach is that every requirement can be modeled as an input/output transformation. Examples are used to show how attributes traditionally thought of as non-functional requirements can be captured, with higher precision, as functional transformations.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

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Constructing True Model-Based Requirements in SysML

Salado

Wach

2019

Systems

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“…Most of the literature in model-based requirements deals with aspects related to requirements management (e.g., requirements traceability and allocation [21][22][23][24][25][26][27] or requirements engineering and management processes). 24,28,29 Modeling the actual requirements is generally accomplished with one of two approaches.…”

Section: Model-based Requirementsmentioning

confidence: 99%

A comparative experiment between textual requirements and model‐based requirements on proxies for contractual safety

Salado,

Shadab

2023

Systems Engineering

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Requirements form the backbone of contracting in acquisition programs. Requirements define the problem boundaries within which contractors try to find acceptable solutions (design systems). At the same time, requirements are the criteria by which a customer measures the extent that their contract has been fulfilled by the supplier. In this context, the quality of a requirement set is determined by the level of contractual safety that it yields. Unfortunately, textual requirements do not provide acceptable levels of contractual safety, as they remain a major source of problems in acquisition programs. Model‐based requirements have been proposed as an alternative to textual requirements, although this promise has not been demonstrated yet. This paper addresses the main question of whether using model‐based requirements improves the contractual safety of acquisition programs compared to using textual requirements. The level of adequate applicability, bounding, necessity, and completeness achieved by model‐based requirements are empirically measured using an experimental study with aerospace engineering and industrial and systems engineering students on a space system application. The results show that model‐based requirements outperform textual requirements in these four variables.

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“…Rezaei Aderiani et al [25] improved the genetic coding method of intelligent optimization algorithms for solving selective assembly problems and proved in three cases that the effect of intelligent algorithms was better than mixed integer linear programming and mixed integer nonlinear programming in selective assembly, and this method could effectively reduce the calculation time. A methodology has been proposed in [26,27], which defines system requirements formally and automatically verifies and evaluates the system through simulation. Based on Formal Requirements Modeling Language and the Modelica Language, it is verified in two practical engineering project cases.…”

Section: Introductionmentioning

confidence: 99%

Many-Objective Optimization and Decision-Making Method for Selective Assembly of Complex Mechanical Products Based on Improved NSGA-III and VIKOR

Pan

Zhao

2021

Processes

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In Industry 4.0, data are sensed and merged to drive intelligent systems. This research focuses on the optimization of selective assembly of complex mechanical products (CMPs) under intelligent system environment conditions. For the batch assembly of CMPs, it is difficult to obtain the best combinations of components from combinations for simultaneous optimization of success rate and multiple assembly quality. Hence, the Taguchi quality loss function was used to quantitatively evaluate each assembly quality and the assembly success rate is combined to establish a many-objective optimization model. The crossover and mutation operators were improved to enhance the ability of NSGA-III to obtain high-quality solution set and jump out of a local optimal solution, and the Pareto optimal solution set was obtained accordingly. Finally, considering the production mode of Human–Machine Intelligent System interaction, the optimal compromise solution is obtained by using fuzzy theory, entropy theory and the VIKOR method. The results show that this work has obvious advantages in improving the quality of batch selective assembly of CMPs and assembly success rate and gives a sorting selection strategy for non-dominated selective assembly schemes while taking into account the group benefit and individual regret.

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Formal Requirements Engineering for Smart Industries: Toward a Model-Based Graphical Language

Cited by 8 publications

References 4 publications

Constructing True Model-Based Requirements in SysML

Constructing True Model-Based Requirements in SysML

A comparative experiment between textual requirements and model‐based requirements on proxies for contractual safety

Many-Objective Optimization and Decision-Making Method for Selective Assembly of Complex Mechanical Products Based on Improved NSGA-III and VIKOR

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