Malak Saidi, Anis Tissaoui, D. Benslimane, S. Faiz
Today, the economic crisis is putting enormous pressure on most organizations. It evolves in a crucial competitive environment with a multiplication of production cycles and implementation on the market. Due to this dynamism, organizations must be scalable and agile by adopting an approach that aims to make the process model of a given organization reusable. Indeed, according to the new paradigm which is called “Design by reuse” the models of configurable processes, gain recently in importance since these models have the capacity to represent explicitly the common parts and variables of identical processes in a customizable model. These configurable process which group several execution choices through a variation point called configurable connector will present an uncertainty related to the execution (or not) of the conditional tasks in a process model. In this paper, we propose a measure based on Shannon's entropy in order to model the uncertainty of the process at design time to guide configurable business process designers and analysts in developing and improving processes to be more predictable, less complex, and more understandable.
{"title":"Uncertainty measurement of a configurable business process","authors":"Malak Saidi, Anis Tissaoui, D. Benslimane, S. Faiz","doi":"10.1002/sys.21650","DOIUrl":"https://doi.org/10.1002/sys.21650","url":null,"abstract":"Today, the economic crisis is putting enormous pressure on most organizations. It evolves in a crucial competitive environment with a multiplication of production cycles and implementation on the market. Due to this dynamism, organizations must be scalable and agile by adopting an approach that aims to make the process model of a given organization reusable. Indeed, according to the new paradigm which is called “Design by reuse” the models of configurable processes, gain recently in importance since these models have the capacity to represent explicitly the common parts and variables of identical processes in a customizable model. These configurable process which group several execution choices through a variation point called configurable connector will present an uncertainty related to the execution (or not) of the conditional tasks in a process model. In this paper, we propose a measure based on Shannon's entropy in order to model the uncertainty of the process at design time to guide configurable business process designers and analysts in developing and improving processes to be more predictable, less complex, and more understandable.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41820805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article explores conceptual modeling to support system‐level decision‐making during concept evaluation. The system‐level decisions made in the concept phases decide most of the systems' value and cost. The context for our research is the Norwegian energy domain. Through an industrial case study in a global subsea system supplier company, we have explored conceptual modeling to support system‐level decision‐making in the conceptual phase. From the insights and learnings gained in the industry case, the article proposes an approach for using conceptual modeling to support System‐Level Decision‐Making. Further, the article presents three examples of applications to demonstrate the use of the approach. To evaluate the approach's usefulness in the industrial setting, we conducted a survey of 37 engineers in the company of research. The engineers perceive that using the approach would improve awareness of the system context and support a holistic mindset. Furthermore, the engineers perceive the conceptual models as efficient for knowledge sharing and communication, especially in meetings between technical and non‐technical personnel. The engineers identify simplicity as a top benefit of the approach but also as a concern. Balancing the need for abstracting with the need for being specific is a crucial challenge in modeling. The survey also shows concerns about the implementation of the approach and the effort required to use the approach in daily work. The primary outcome of the research is insights into how conceptual modeling can support system‐level decision‐making in the industrial context.
{"title":"Conceptual modeling to support system‐level decision‐making: An industrial case study from the Norwegian energy domain","authors":"Siv Engen, G. Muller, K. Falk","doi":"10.1002/sys.21649","DOIUrl":"https://doi.org/10.1002/sys.21649","url":null,"abstract":"This article explores conceptual modeling to support system‐level decision‐making during concept evaluation. The system‐level decisions made in the concept phases decide most of the systems' value and cost. The context for our research is the Norwegian energy domain. Through an industrial case study in a global subsea system supplier company, we have explored conceptual modeling to support system‐level decision‐making in the conceptual phase. From the insights and learnings gained in the industry case, the article proposes an approach for using conceptual modeling to support System‐Level Decision‐Making. Further, the article presents three examples of applications to demonstrate the use of the approach. To evaluate the approach's usefulness in the industrial setting, we conducted a survey of 37 engineers in the company of research. The engineers perceive that using the approach would improve awareness of the system context and support a holistic mindset. Furthermore, the engineers perceive the conceptual models as efficient for knowledge sharing and communication, especially in meetings between technical and non‐technical personnel. The engineers identify simplicity as a top benefit of the approach but also as a concern. Balancing the need for abstracting with the need for being specific is a crucial challenge in modeling. The survey also shows concerns about the implementation of the approach and the effort required to use the approach in daily work. The primary outcome of the research is insights into how conceptual modeling can support system‐level decision‐making in the industrial context.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44530102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Sajid, A. Wasim, S. Hussain, M. Raza, M. Jahanzaib
In recent years, the reliable, accurate, and timely estimate of product cost at the conceptual design stage can enhance the competitiveness of a casting part. Set‐based concurrent engineering has emerged as an efficient solution to overcome this limitation as it provides simultaneous design procedures to positively assist the designer in achieving the required customer values in a short time and low cost. Therefore, this study attempts to integrate the set‐based concurrent engineering methodology into the development of a cost modeling system for the metal casting process. The system architecture is comprised of a user interface, knowledge database, and CAD modeling system. A detailed working flow process of the developed cost modeling system has been proposed under the guidelines of set‐based concurrent engineering. Further, the proposed methodology is demonstrated and validated by employing a real‐time casting part that was manufactured using the sand casting process. The implementation of the system provided many tangible benefits to the collaborative company including a decrease in cost estimation time (∼50%) and part rejection rate (∼32.3%). Further, the developed cost modeling approach provided a cost estimate near the actual cost of the product (∼4% deviation). It truly proves the significance of the developed system for the practitioners who believe that accurate and timely estimates of product manufacturing cost at the design stage can enhance the competitiveness of a product.
{"title":"Application of set‐based concurrent engineering methodology to the development of cost modeling system for metal casting process","authors":"Muhammad Sajid, A. Wasim, S. Hussain, M. Raza, M. Jahanzaib","doi":"10.1002/sys.21648","DOIUrl":"https://doi.org/10.1002/sys.21648","url":null,"abstract":"In recent years, the reliable, accurate, and timely estimate of product cost at the conceptual design stage can enhance the competitiveness of a casting part. Set‐based concurrent engineering has emerged as an efficient solution to overcome this limitation as it provides simultaneous design procedures to positively assist the designer in achieving the required customer values in a short time and low cost. Therefore, this study attempts to integrate the set‐based concurrent engineering methodology into the development of a cost modeling system for the metal casting process. The system architecture is comprised of a user interface, knowledge database, and CAD modeling system. A detailed working flow process of the developed cost modeling system has been proposed under the guidelines of set‐based concurrent engineering. Further, the proposed methodology is demonstrated and validated by employing a real‐time casting part that was manufactured using the sand casting process. The implementation of the system provided many tangible benefits to the collaborative company including a decrease in cost estimation time (∼50%) and part rejection rate (∼32.3%). Further, the developed cost modeling approach provided a cost estimate near the actual cost of the product (∼4% deviation). It truly proves the significance of the developed system for the practitioners who believe that accurate and timely estimates of product manufacturing cost at the design stage can enhance the competitiveness of a product.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44025468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Obsolescence is an important consideration in the management and engineering of heavy industrial facilities. Examples of these could include refineries, chemical plants, and other large‐scale materials processing facilities. These facilities have lifetimes of many decades but operate on software, automation hardware, and other electrical equipment that reaches obsolescence much sooner than the rotating equipment, unit operations, and other major systems of the facility. This work proposes a method to manage obsolescence of automation and electrical systems at industrial sites. This risk management method was developed by first analyzing a database of upgrade projects at several industrial sites and identifying parts that had been replaced due to obsolescence. The analysis was used to prioritize replacement of obsolescent parts based on the average operational lifespans, their criticality in operations, their manufacturer's continued production state, and other factors. Based on those results, a taxonomy of obsolescence risk, and a risk assessment plan were developed to manage the replacement of parts. The value of this proposed management strategy was validated through its application to 13 heavy industrial facilities. The results indicate a reduction of roughly 70% in reactive replacements due to obsolescence after the major upgrade and a 24% reduction in unplanned downtime due to part failure during normal operations. While this study is focused on heavy industries, the proposed method for identifying and managing component obsolescence can be applied to other industries and systems.
{"title":"Risk‐based approach for managing obsolescence for automation systems in heavy industries","authors":"T. Ault, Thomas H. Bradley","doi":"10.1002/sys.21635","DOIUrl":"https://doi.org/10.1002/sys.21635","url":null,"abstract":"Obsolescence is an important consideration in the management and engineering of heavy industrial facilities. Examples of these could include refineries, chemical plants, and other large‐scale materials processing facilities. These facilities have lifetimes of many decades but operate on software, automation hardware, and other electrical equipment that reaches obsolescence much sooner than the rotating equipment, unit operations, and other major systems of the facility. This work proposes a method to manage obsolescence of automation and electrical systems at industrial sites. This risk management method was developed by first analyzing a database of upgrade projects at several industrial sites and identifying parts that had been replaced due to obsolescence. The analysis was used to prioritize replacement of obsolescent parts based on the average operational lifespans, their criticality in operations, their manufacturer's continued production state, and other factors. Based on those results, a taxonomy of obsolescence risk, and a risk assessment plan were developed to manage the replacement of parts. The value of this proposed management strategy was validated through its application to 13 heavy industrial facilities. The results indicate a reduction of roughly 70% in reactive replacements due to obsolescence after the major upgrade and a 24% reduction in unplanned downtime due to part failure during normal operations. While this study is focused on heavy industries, the proposed method for identifying and managing component obsolescence can be applied to other industries and systems.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44961758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Organizations use command and control (C2) systems to collect, organize, and disseminate information in order to make decisions, impart instructions, and manage resources to accomplish a mission. C2 agility and robustness are critical to ensure that a C2 system can perform well in a variety of environments. One system design principle, decentralization, has been closely linked to desirable system characteristics such as agility and adaptability, but its relationship to system performance robustness is not well‐established. In this study, we explore C2 system architectures—ranging from fully centralized to fully decentralized archetypes—to assess their performance and robustness characteristics across a spectrum of operating environments. While the centralized archetype achieves high performance in favorable environmental conditions, its performance quickly degrades when conditions worsen, hindering its overall robustness. Conversely, the decentralized archetype achieves a lower but more stable performance profile resulting in more robustness when performance requirements are lower. Finally, we explore alternative, hybrid architectures with varying degrees of centralized and decentralized decision‐making. We find that by centralizing only certain system‐consequential functions such as resource allocation, and decentralizing more focused decision functions which can be performed suitably with only local information and resources, system performance and robustness are improved beyond that of the simple archetypes.
{"title":"Robustness of decentralized decision‐making architectures in command and control systems","authors":"Lewis N. Boss, E. Gralla","doi":"10.1002/sys.21647","DOIUrl":"https://doi.org/10.1002/sys.21647","url":null,"abstract":"Organizations use command and control (C2) systems to collect, organize, and disseminate information in order to make decisions, impart instructions, and manage resources to accomplish a mission. C2 agility and robustness are critical to ensure that a C2 system can perform well in a variety of environments. One system design principle, decentralization, has been closely linked to desirable system characteristics such as agility and adaptability, but its relationship to system performance robustness is not well‐established. In this study, we explore C2 system architectures—ranging from fully centralized to fully decentralized archetypes—to assess their performance and robustness characteristics across a spectrum of operating environments. While the centralized archetype achieves high performance in favorable environmental conditions, its performance quickly degrades when conditions worsen, hindering its overall robustness. Conversely, the decentralized archetype achieves a lower but more stable performance profile resulting in more robustness when performance requirements are lower. Finally, we explore alternative, hybrid architectures with varying degrees of centralized and decentralized decision‐making. We find that by centralizing only certain system‐consequential functions such as resource allocation, and decentralizing more focused decision functions which can be performed suitably with only local information and resources, system performance and robustness are improved beyond that of the simple archetypes.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44928418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anil Kumar Dsouza, Ananthapadmanabha Thammaiah, L. M. Venkatesh
This article proposes a hybrid approach for power flow management and power quality (PQ) improvement in smart grid (SG) system. The proposed methodology is designed into two phases, power flow management is the first stage and power quality improvement is the second stage of the system. The key purpose of the proposed method is “to regulate that power flow depends on variation of source and load side parameters deliver the highest PQ.” The initial phase of power flow management is executed by using Improved Binary Sailfish Optimizer (IBSFO) approach. The control signal is recognized by the IBSFO approach against active and reactive power variation. The second phase of power quality enhancement is implemented by K2ORBFNN, which is the combination of Kho‐Kho optimization (KKO) and Radial Basis Function Neural Network (RBFNN). The gain parameter of the proportional integral (PI) controller is tuned based on load current, DC link, and voltage sources using K2ORBFNN approach. The prediction of optimal control signal minimizes the error which is obtained by RBFNN approach. The proposed method is utilized to attain compensating non‐linear load current harmonics, compensating reactive load power requirement, compensating unbalanced load current with neutral current. Finally, the performance of proposed system is executed in the MATLAB platform and performance is compared with existing techniques. The efficiency under the trails of 100, 200, 500, and 1000 attains 99.1673%, 99.4567%, 99.8402%, and 99.9879%.
{"title":"A hybrid approach for enhancing and optimizing the power quality and power flow in Smart Grid Connected System","authors":"Anil Kumar Dsouza, Ananthapadmanabha Thammaiah, L. M. Venkatesh","doi":"10.1002/sys.21645","DOIUrl":"https://doi.org/10.1002/sys.21645","url":null,"abstract":"This article proposes a hybrid approach for power flow management and power quality (PQ) improvement in smart grid (SG) system. The proposed methodology is designed into two phases, power flow management is the first stage and power quality improvement is the second stage of the system. The key purpose of the proposed method is “to regulate that power flow depends on variation of source and load side parameters deliver the highest PQ.” The initial phase of power flow management is executed by using Improved Binary Sailfish Optimizer (IBSFO) approach. The control signal is recognized by the IBSFO approach against active and reactive power variation. The second phase of power quality enhancement is implemented by K2ORBFNN, which is the combination of Kho‐Kho optimization (KKO) and Radial Basis Function Neural Network (RBFNN). The gain parameter of the proportional integral (PI) controller is tuned based on load current, DC link, and voltage sources using K2ORBFNN approach. The prediction of optimal control signal minimizes the error which is obtained by RBFNN approach. The proposed method is utilized to attain compensating non‐linear load current harmonics, compensating reactive load power requirement, compensating unbalanced load current with neutral current. Finally, the performance of proposed system is executed in the MATLAB platform and performance is compared with existing techniques. The efficiency under the trails of 100, 200, 500, and 1000 attains 99.1673%, 99.4567%, 99.8402%, and 99.9879%.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42844275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan Antonio Martínez Rojas, José L. Fernández-Sánchez
The model based systems engineering (MBSE) approach describes a system using consistent views to provide a holistic model as complete as possible. MBSE methodologies end with the physical architecture of the system, but a physical model is clearly incomplete without the study of its associated physical laws and phenomena related to the whole system or its parts. However, the computational demands could be excessive even for modest projects. Dimensional analysis (DA) is common in fluid dynamics and chemical engineering, but its application to systems engineering is still limited. We describe an engineering methodological process, which incorporates DA as a powerful tool to understand the physical constraints of the system without the burden of complex analytical or numerical calculations. A detailed example describing a microantenna is presented showing the benefits of this approach. The selected example describes a problem rarely covered in modern expositions of DA in order to show the wide benefit of these techniques. The information provided by this analysis is very useful to select the best physically realizable architectures, testing design, and conduct trade‐off studies. The complexity of modern systems and systems of systems demands new testing procedures in order to comply with increasingly demanding requirements and regulations. This can be accomplished through research in new DA methods. Finally, this article serves as a fairly comprehensive guide to the use of DA in the context of MBSE, detailing its strengths, limitations, and controversial issues.
{"title":"Combining dimensional analysis with model based systems engineering","authors":"Juan Antonio Martínez Rojas, José L. Fernández-Sánchez","doi":"10.1002/sys.21646","DOIUrl":"https://doi.org/10.1002/sys.21646","url":null,"abstract":"The model based systems engineering (MBSE) approach describes a system using consistent views to provide a holistic model as complete as possible. MBSE methodologies end with the physical architecture of the system, but a physical model is clearly incomplete without the study of its associated physical laws and phenomena related to the whole system or its parts. However, the computational demands could be excessive even for modest projects. Dimensional analysis (DA) is common in fluid dynamics and chemical engineering, but its application to systems engineering is still limited. We describe an engineering methodological process, which incorporates DA as a powerful tool to understand the physical constraints of the system without the burden of complex analytical or numerical calculations. A detailed example describing a microantenna is presented showing the benefits of this approach. The selected example describes a problem rarely covered in modern expositions of DA in order to show the wide benefit of these techniques. The information provided by this analysis is very useful to select the best physically realizable architectures, testing design, and conduct trade‐off studies. The complexity of modern systems and systems of systems demands new testing procedures in order to comply with increasingly demanding requirements and regulations. This can be accomplished through research in new DA methods. Finally, this article serves as a fairly comprehensive guide to the use of DA in the context of MBSE, detailing its strengths, limitations, and controversial issues.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49558082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kelly X. Campo, T. Teper, Casey E. Eaton, Anna M. Shipman, Garima Bhatia, Bryan L. Mesmer
Although Model‐Based Systems Engineering (MBSE) is quickly becoming adopted in Systems Engineering (SE), there have not been many studies evaluating literature to determine the perceived value of implementing MBSE. This research first identifies and discusses previous studies on the justification or rejection of MBSE. This study investigates how the SE community perceives the value of MBSE by coding and analyzing positive and negative descriptions of MBSE; perceived benefits and drawbacks of implementing MBSE; and the evidence and metrics used to substantiate and measure each claim about MBSE. From 60 academic sources, this study collected and coded over 2900 claims on MBSE. Our findings determine the most positive attributes of MBSE to be Verification & Validation Capability, Consistency, Reasoning, and Risk & Error Manageability, while the most negative attributes were Approach Understandability, Acceptability, Familiarity, and Approach Complexity. The most‐stated benefits were Reduced Time, Better Communication/Information Sharing, Reduced Costs, and Better Analysis Capability. The most claimed drawbacks were Increased Costs, Increased Time, Increased Effort, and Worsened Capability. A large share of claims (47%) about MBSE was based on author opinions. Most claims (86%) were not substantiated by a metric.
{"title":"Model‐based systems engineering: Evaluating perceived value, metrics, and evidence through literature","authors":"Kelly X. Campo, T. Teper, Casey E. Eaton, Anna M. Shipman, Garima Bhatia, Bryan L. Mesmer","doi":"10.1002/sys.21644","DOIUrl":"https://doi.org/10.1002/sys.21644","url":null,"abstract":"Although Model‐Based Systems Engineering (MBSE) is quickly becoming adopted in Systems Engineering (SE), there have not been many studies evaluating literature to determine the perceived value of implementing MBSE. This research first identifies and discusses previous studies on the justification or rejection of MBSE. This study investigates how the SE community perceives the value of MBSE by coding and analyzing positive and negative descriptions of MBSE; perceived benefits and drawbacks of implementing MBSE; and the evidence and metrics used to substantiate and measure each claim about MBSE. From 60 academic sources, this study collected and coded over 2900 claims on MBSE. Our findings determine the most positive attributes of MBSE to be Verification & Validation Capability, Consistency, Reasoning, and Risk & Error Manageability, while the most negative attributes were Approach Understandability, Acceptability, Familiarity, and Approach Complexity. The most‐stated benefits were Reduced Time, Better Communication/Information Sharing, Reduced Costs, and Better Analysis Capability. The most claimed drawbacks were Increased Costs, Increased Time, Increased Effort, and Worsened Capability. A large share of claims (47%) about MBSE was based on author opinions. Most claims (86%) were not substantiated by a metric.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48639835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model‐based systems engineering is a powerful methodology to develop safety‐critical systems. The use of the system model as a single source of truth for risk and dependability analysis results in a consistent and complete assessment. Besides, representation and logging of the assessment within the model result in a complete and up‐to‐date single source of information that can be used during the device certification as well. This paper aims to provide a comprehensive risk management SysML profile that includes interconnected safety analysis [functional hazard assessment (FHA), fault tree, and failure mode and effect analysis (FTA, FMEA)], control measure, and evaluation model elements in compliance with the medical standards. Model‐based risk assessment of a point‐of‐care diagnostic device for sepsis has been shown as a case study to show the implementation of the profile. This device is a standalone unit and the test results obtained directly affect the patient. Therefore, both the top‐down (FHA and FTA) and bottom‐up (FMEA) safety assessment methods have been used. Another objective of the study is to define a systematic and holistic method to perform fault tree analysis, not only from the system architecture models but also from the functional, activity, and sequence diagrams of the system model.
{"title":"Integration of systems design and risk management through model‐based systems development","authors":"Y. Uludağ, Ersin Evin, Nazan Gözay Gürbüz","doi":"10.1002/sys.21643","DOIUrl":"https://doi.org/10.1002/sys.21643","url":null,"abstract":"Model‐based systems engineering is a powerful methodology to develop safety‐critical systems. The use of the system model as a single source of truth for risk and dependability analysis results in a consistent and complete assessment. Besides, representation and logging of the assessment within the model result in a complete and up‐to‐date single source of information that can be used during the device certification as well. This paper aims to provide a comprehensive risk management SysML profile that includes interconnected safety analysis [functional hazard assessment (FHA), fault tree, and failure mode and effect analysis (FTA, FMEA)], control measure, and evaluation model elements in compliance with the medical standards. Model‐based risk assessment of a point‐of‐care diagnostic device for sepsis has been shown as a case study to show the implementation of the profile. This device is a standalone unit and the test results obtained directly affect the patient. Therefore, both the top‐down (FHA and FTA) and bottom‐up (FMEA) safety assessment methods have been used. Another objective of the study is to define a systematic and holistic method to perform fault tree analysis, not only from the system architecture models but also from the functional, activity, and sequence diagrams of the system model.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48907043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Systems engineering tools and methodologies are increasingly being used in urban planning and sustainable development applications. Such tools were previously extensively used for urban planning during the 1960s and 1970s in the United States, only to result in high profile failures and pushback from urban planners, politicians, and the public. In order to better understand why this occurred, what has changed, and how we can avoid such failures moving forward, this study conducts a systematic review and an integrative review of the systems engineering and critical literature. These reviews are used to identify eight common pitfalls and organize them into key themes. Technological and methodological developments that may address each of these pitfalls are considered and recommendations are made for future applications of systems engineering to planning contexts. Finally, examples are provided of systems engineering being used productively in a way consistent with these recommendations for sustainable development applications.
{"title":"Systems engineering applied to urban planning and development: A review and research agenda","authors":"Jack Reid, D. Wood","doi":"10.1002/sys.21642","DOIUrl":"https://doi.org/10.1002/sys.21642","url":null,"abstract":"Systems engineering tools and methodologies are increasingly being used in urban planning and sustainable development applications. Such tools were previously extensively used for urban planning during the 1960s and 1970s in the United States, only to result in high profile failures and pushback from urban planners, politicians, and the public. In order to better understand why this occurred, what has changed, and how we can avoid such failures moving forward, this study conducts a systematic review and an integrative review of the systems engineering and critical literature. These reviews are used to identify eight common pitfalls and organize them into key themes. Technological and methodological developments that may address each of these pitfalls are considered and recommendations are made for future applications of systems engineering to planning contexts. Finally, examples are provided of systems engineering being used productively in a way consistent with these recommendations for sustainable development applications.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45347960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：