Sharon A. Ferguson, Eric van Velzen, A. Olechowski
Remote work is becoming increasingly common, a trend accelerated by the global COVID‐19 pandemic. Existing remote work research fails to address the challenges and needs of engineers working remotely in Complex Aerospace System Development (CASD), the field responsible for creating and operating aerospace systems. This article presents an exploratory study to understand the challenges, benefits, and strategies when working remotely in CASD. We interviewed 12 CASD engineers working remotely at a major aerospace corporation. We ground our findings in six characteristics of CASD work (complex systems; design paths and feedback loops; relationships with suppliers, customers and regulators; distinct knowledge and skills; one‐off innovation; and high cost of experimentation) and discuss how each of these characteristics challenges remote work. The findings show that CASD requires many teams to work together, and this is encouraged through informal communication, which almost disappears in a remote setting. CASD requires frequent feedback, and we found that feedback was slow when working remotely. Participants found it challenging to demonstrate systems to customers and verify drawings with suppliers, and the interpersonal relationships, which help to bridge disciplinary divides, were harder to maintain remotely. The one‐off nature of the systems designed meant that conceptual work was important, but participants lacked the virtual tools to do this effectively. Lastly, testing hardware components required close virtual communication between technicians and engineers, which was tricky in a detail‐oriented context. This study motivates areas for future work to better understand and address the nuances of remote work by engineers in CASD.
{"title":"Team and communication impacts of remote work for complex aerospace system development","authors":"Sharon A. Ferguson, Eric van Velzen, A. Olechowski","doi":"10.1002/sys.21716","DOIUrl":"https://doi.org/10.1002/sys.21716","url":null,"abstract":"Remote work is becoming increasingly common, a trend accelerated by the global COVID‐19 pandemic. Existing remote work research fails to address the challenges and needs of engineers working remotely in Complex Aerospace System Development (CASD), the field responsible for creating and operating aerospace systems. This article presents an exploratory study to understand the challenges, benefits, and strategies when working remotely in CASD. We interviewed 12 CASD engineers working remotely at a major aerospace corporation. We ground our findings in six characteristics of CASD work (complex systems; design paths and feedback loops; relationships with suppliers, customers and regulators; distinct knowledge and skills; one‐off innovation; and high cost of experimentation) and discuss how each of these characteristics challenges remote work. The findings show that CASD requires many teams to work together, and this is encouraged through informal communication, which almost disappears in a remote setting. CASD requires frequent feedback, and we found that feedback was slow when working remotely. Participants found it challenging to demonstrate systems to customers and verify drawings with suppliers, and the interpersonal relationships, which help to bridge disciplinary divides, were harder to maintain remotely. The one‐off nature of the systems designed meant that conceptual work was important, but participants lacked the virtual tools to do this effectively. Lastly, testing hardware components required close virtual communication between technicians and engineers, which was tricky in a detail‐oriented context. This study motivates areas for future work to better understand and address the nuances of remote work by engineers in CASD.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44238788","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}
Lessons learned through MBSE adoption efforts is one of the key ways of communicating best practices and recommendations for MBSE. This study compiles lessons learned from published case studies and practitioner interviews. Lessons are summarized into categories such as adoption strategy, modeling practices, and communication. This paper provides a source for future adopters of MBSE to review best practices and recommendations from a multitude of different experiences. This should improve the adoption and implementation of MBSE.
{"title":"MBSE adoption experiences in organizations: Lessons learned","authors":"Kaitlin Henderson, Thomas A. McDermott, A. Salado","doi":"10.1002/sys.21717","DOIUrl":"https://doi.org/10.1002/sys.21717","url":null,"abstract":"Lessons learned through MBSE adoption efforts is one of the key ways of communicating best practices and recommendations for MBSE. This study compiles lessons learned from published case studies and practitioner interviews. Lessons are summarized into categories such as adoption strategy, modeling practices, and communication. This paper provides a source for future adopters of MBSE to review best practices and recommendations from a multitude of different experiences. This should improve the adoption and implementation of MBSE.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46574094","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}
Souvick Das, Novarun Deb, N. Chaki, Agostino Cortesi
Significant contributions in the existing literature highlight the potential of softgoal interdependency graphs towards analyzing conflicting non‐functional requirements (NFRs). However, such analysis is often at a very abstract level and does not quite consider the run‐time performance statistics of NFR operationalizations. On the contrary, some initial empirical evaluations demonstrate the importance of the run‐time statistics. In this paper, a framework is proposed that uses these statistics and combines the same with NFR priorities for computing the impact of NFR conflicts. The proposed framework is capable of identifying the best possible set of NFR operationalizations that minimizes the impact of conflicting NFRs. A detailed space analysis of the solution framework helps proving the efficiency of the proposed pruning mechanism in terms of better space management. Furthermore, a Dynamic Bayesian Network (DBN) ‐ based system behavioral model that works on top of the proposed framework, is defined and analyzed. An appropriate tool prototype for the framework is implemented as part of this research.
{"title":"Minimising conflicts among run‐time non‐functional requirements within DevOps","authors":"Souvick Das, Novarun Deb, N. Chaki, Agostino Cortesi","doi":"10.1002/sys.21715","DOIUrl":"https://doi.org/10.1002/sys.21715","url":null,"abstract":"Significant contributions in the existing literature highlight the potential of softgoal interdependency graphs towards analyzing conflicting non‐functional requirements (NFRs). However, such analysis is often at a very abstract level and does not quite consider the run‐time performance statistics of NFR operationalizations. On the contrary, some initial empirical evaluations demonstrate the importance of the run‐time statistics. In this paper, a framework is proposed that uses these statistics and combines the same with NFR priorities for computing the impact of NFR conflicts. The proposed framework is capable of identifying the best possible set of NFR operationalizations that minimizes the impact of conflicting NFRs. A detailed space analysis of the solution framework helps proving the efficiency of the proposed pruning mechanism in terms of better space management. Furthermore, a Dynamic Bayesian Network (DBN) ‐ based system behavioral model that works on top of the proposed framework, is defined and analyzed. An appropriate tool prototype for the framework is implemented as part of this research.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49375624","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}
Leila Saari, M. Räikkönen, E. Hytönen, Katri Valkokari
The complexity of industrial challenges is emerging together with the exponentially developing information and communication technologies (ICT) that provide several implementation approaches for systems engineering. It is difficult for a single company to follow technological development and remain a pioneer in every topic. Still, the industrial challenges require experts in each technology. Therefore, collaboration among technology providers is an opportunity to gather all resources and competences needed for full delivery. A joint offering (JO) is a solution, that is, co‐created in collaboration between two or more actors that usually have complementary technological skills or value‐creation logics. A JO has several doubts relating to the use case (UC) in hand, the feasibility of the joint solution to be co‐created, the resources and skills needed to deliver the joint solution, the partners, the business value creation, the elements of the contract and the ownership of the outcome, just to mention a few. The Joint Offering Evaluation Framework (JOEF) uncovers these issues and supports decision‐making before the development of a JO starts. The JOEF comprises the Joint Offering Playbook and the Business Value Toolset (BVT). The Playbook offers seven viewpoints with checklists and tools for IT solution providers considering collaboration and co‐creation for a solution that they cannot deliver or sell alone. The BVT evaluates and illustrates the business value of a JO from the viewpoints of both creation and delivery, together with value capture and assessment. The JOEF was piloted with a digital twin (DT) UC from the pulp and paper industry.
{"title":"Joint Offering Evaluation Framework for Assessing the Feasibility and Business Value of a Digital Twin Use Case","authors":"Leila Saari, M. Räikkönen, E. Hytönen, Katri Valkokari","doi":"10.1002/sys.21713","DOIUrl":"https://doi.org/10.1002/sys.21713","url":null,"abstract":"The complexity of industrial challenges is emerging together with the exponentially developing information and communication technologies (ICT) that provide several implementation approaches for systems engineering. It is difficult for a single company to follow technological development and remain a pioneer in every topic. Still, the industrial challenges require experts in each technology. Therefore, collaboration among technology providers is an opportunity to gather all resources and competences needed for full delivery. A joint offering (JO) is a solution, that is, co‐created in collaboration between two or more actors that usually have complementary technological skills or value‐creation logics. A JO has several doubts relating to the use case (UC) in hand, the feasibility of the joint solution to be co‐created, the resources and skills needed to deliver the joint solution, the partners, the business value creation, the elements of the contract and the ownership of the outcome, just to mention a few. The Joint Offering Evaluation Framework (JOEF) uncovers these issues and supports decision‐making before the development of a JO starts. The JOEF comprises the Joint Offering Playbook and the Business Value Toolset (BVT). The Playbook offers seven viewpoints with checklists and tools for IT solution providers considering collaboration and co‐creation for a solution that they cannot deliver or sell alone. The BVT evaluates and illustrates the business value of a JO from the viewpoints of both creation and delivery, together with value capture and assessment. The JOEF was piloted with a digital twin (DT) UC from the pulp and paper industry.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47271299","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 study uses the Design Science Research Methodology (DSRM) approach in creating an artifact on the perspective of the Information System. Design Science as a valuable tool for creating a new artifact or developing an existing artifact through research. The DSRM Framework described in this study discusses the implementation of each stage, namely, Explicated Problem, Define Requirement, Design and Development, Demonstration, and Evaluation and is complemented by the implementation of case studies of artifact creation in DSRM stages. The Digital Maturity Measurement in question is a service to measure digital maturity in various dimensions. Each DSRM stage is mapped to a case study of that service.Canvas visualization is presented to describe a complete picture of how the artifacts of Digital maturity services are built with the DSRM approach. This research also provides guidance on the principles, procedures, and characteristics needed to build effective research.
{"title":"Measuring the digital transformation maturity level independently with the design science research methodology","authors":"T. Haryanti, Nur Aini Rakhmawati, A. P. Subriadi","doi":"10.1002/sys.21714","DOIUrl":"https://doi.org/10.1002/sys.21714","url":null,"abstract":"This study uses the Design Science Research Methodology (DSRM) approach in creating an artifact on the perspective of the Information System. Design Science as a valuable tool for creating a new artifact or developing an existing artifact through research. The DSRM Framework described in this study discusses the implementation of each stage, namely, Explicated Problem, Define Requirement, Design and Development, Demonstration, and Evaluation and is complemented by the implementation of case studies of artifact creation in DSRM stages. The Digital Maturity Measurement in question is a service to measure digital maturity in various dimensions. Each DSRM stage is mapped to a case study of that service.Canvas visualization is presented to describe a complete picture of how the artifacts of Digital maturity services are built with the DSRM approach. This research also provides guidance on the principles, procedures, and characteristics needed to build effective research.","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49115302","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}
Scott D. Lucero, A. Pyster, Kristen J. Baldwin, D. DeLaurentis, J. Wade, T. McDermott, D. Verma
{"title":"Lessons learned from establishing the Systems Engineering Research Center, a networked University Affiliated Research Center","authors":"Scott D. Lucero, A. Pyster, Kristen J. Baldwin, D. DeLaurentis, J. Wade, T. McDermott, D. Verma","doi":"10.1002/sys.21712","DOIUrl":"https://doi.org/10.1002/sys.21712","url":null,"abstract":"","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45747800","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}
C. Robert Kenley, Shrividya Subramanian, Katherine M. Adams
{"title":"Statistical modeling to relate technology readiness to schedule","authors":"C. Robert Kenley, Shrividya Subramanian, Katherine M. Adams","doi":"10.1002/sys.21711","DOIUrl":"https://doi.org/10.1002/sys.21711","url":null,"abstract":"","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44206755","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}
{"title":"Cyber oriented digital engineering","authors":"J. Mitola, Mark Prys","doi":"10.1002/sys.21710","DOIUrl":"https://doi.org/10.1002/sys.21710","url":null,"abstract":"","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41578565","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}
Aditya U. Kulkarni, Ashley Girod, Peng Xu, A. Salado
{"title":"Optimal verification strategy for general development plans using a belief‐based approach","authors":"Aditya U. Kulkarni, Ashley Girod, Peng Xu, A. Salado","doi":"10.1002/sys.21708","DOIUrl":"https://doi.org/10.1002/sys.21708","url":null,"abstract":"","PeriodicalId":54439,"journal":{"name":"Systems Engineering","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44188897","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：