Systems Engineering: Making People Talk!

Haskins, Cecilia; Ruud, Kristin S.

doi:10.1007/978-3-319-62217-0_75

Cited by 4 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• There is an absence of a widely accepted and consistent terminology for fundamental SE concepts, which results in miscommunication, misunderstanding, and misinterpretation among SE stakeholders (Dori and Sillitto, 2017;Ernadote, 2015;Haskins and Ruud, 2018;Lin and Harding, 2007;Rousseau et al, 2016;.…”

Section: Review Of the Research Questionsmentioning

confidence: 99%

“…Large socio-technical systems are often characterized by a high degree of complexity, a strong interaction with their environment, and an integration between human, cyber, and physical components. Systems engineering (SE) is an interdisciplinary and scientific approach that leverages systems thinking, system life cycle models and system life cycle processes to enable the successful realization of complex systems, often characterized with large scale, high intricacy and significant heterogeneity (Buede and Miller, 2016;Haskins and Ruud, 2018;Kossiakoff et al, 2011;Wasson, 2015). It is responsible for delivering complex projects to meet the needs of the stakeholders in the system life cycle.…”

Section: Introductionmentioning

confidence: 99%

“…Third, SE is multidisciplinary. It is commonly seen that SE projects often involve many stakeholders who are equipped with a variety of competencies and skills (Haskins and Ruud, 2018;. When considering the multitude of stakeholders involved in the entire system life cycle processes, it is hard to maintain a unique vocabulary due to the diverse set of terminologies used across the project team (Rousseau et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ontology Learning for Systems Engineering Body of Knowledge

Yang

Cormican

2021

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

Section: Review Of the Research Questionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ontology Learning for Systems Engineering Body of Knowledge

Yang

Cormican

2021

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

“…By applying MOSAIC to an inter-organizational project concerning the implementation of a train-towing vehicle and evaluating it together with involved project members, this chapter demonstrated that the designed MOSAIC analysis contributes to reaching the goals of the project by: (1) focusing on a clear objective and including relevant actors; (2) providing a structured process and analysis for determining the SOI; (3) synchronizing the perspectives of inter-organizational and multidisciplinary experts through an integral expert session; ( 4) enabling an open, yet focused discussion, supported by guiding questions and visual aids; (5) identifying diverse impacts of the change across sociotechnical domains, and tasks required to be carried out by diverse stakeholders to achieve the determined objective; (6) highlighting ownership and responsibilities; and (7) identifying interdependencies across which collaboration is essential. Here, continuous evaluations can facilitate introduction of new experts and their late-arriving viewpoints to influence the scope, this was also highlighted previously by C. Haskins & Ruud (2017).…”

Section: Design and Development: Applying Systems Thinking To Facilit...mentioning

confidence: 60%

“…Moreover, systems thinking as a practice is the ability to think abstractly in order to: (1) aid in creating an overarching perspective, (2) understand how independent elements come together into a unified overview, (3) incorporate multiple perspectives, (4) work within a space where the boundaries, scope of change, or system may be 'fuzzy', (5) understand the diverse operational contexts of the change, (6) identify inter-and intra-organizational relationships and dependencies, and (7), most importantly, predict the impact of changes to the system (Boardman & Sauser, 2008;C. Haskins & Ruud, 2017;Potts et al, 2022;Sauser & Boardman, 2015;Squires et al, 2011).…”

Section: Systems Thinkingmentioning

confidence: 99%

Enabling inter-organizational change integration in sociotechnical systems : Systems thinking applied in the Dutch railway system

Ramtahalsing

View full text Add to dashboard Cite

the author. Alle rechten voorbehouden. Niets uit deze uitgave mag worden vermenigvuldigd, in enige vorm of op enige wijze, zonder voorafgaande schriftelijke toestemming van de auteur.Chapter 1 While this minimizes the cost of the error, a time-consuming process of redesigning will need to be undertaken, delaying the trains' production process and subsequent delivery by several years (Euronews, 2023; Railway supply, 2023).Another example occurred in 2014, when French train operator SNCF ordered 2000 regional trains at a cost of €15 billion and discovered that they were too wide for the network's platforms. The error was caused by data from the infrastructure manager which did not account for older structures. In this case, the trains had already been manufactured and the platforms had to be rebuilt at great cost. As a consequence, the SNCF was forced to modify more than a thousand stations, after it was revealed that the 1860 newly commissioned trains were too wide for many of the country's platforms. This mistake cost SNCF Réseau over €50 million, as the operator started 'shaving' the edges of affected platforms (BBC News, 2014; The Verge, 2014). Both examples show that such errors can cause significant delays and can be very costly.One reason such errors occur is related to the kinds of systems in which such changes are to be integrated. Railway systems are complex, sociotechnical, and inter-organizational (Bugalia et al., 2021;Milch & Laumann, 2016), which means that they are characterized by multiple domains, such as processes, personnel, technical systems, rules and regulations, and the interactions between these (Bartolomei et al., 2012). Within these systems, multiple interacting parties, complex social structures, and numerous companies and work processes are involved, requiring the collaboration of employees from different organizations (Milch & Laumann, 2016). As such, while a change itself may initially appear simple, it can turn out to be more complex when attention is paid to the context into which it must be integrated, due to the systemic impacts of such changes.The impacts not only affect existing technologies, but also people (with varying attitudes, backgrounds, and skills) who use a range of technologies and tools, work within a physical infrastructure, operate with a specific set of cultural assumptions, and use varying sets of processes, working practices, and regulations (Davis et al., 2014). As such, practitioners may have limited access to data and information about the railway system, which can make it difficult to understand the system itself, but also to identify how changes impact it.Additionally, technological advancements spawn system after system, each increasingly interdependent with other, preceding systems (Arnold & Wade, 2015). As such, the predicted technological changes and the projects that strive to realize these, are increasing in scope, and therefore in degree of systemic impact. All of these potential impacts need to be considered and accounted for in parallel with the ch...

show abstract

Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

2023

View full text Add to dashboard Cite

Complexity is often regarded as a “problem” to solve. Instead of attempting to solve complexity, we follow systems engineering practices and switch back to the problem domain, where a major obstacle is the impossibility to universally define complexity. As a workaround, we explored complexity characterization and its existing shortcomings, including: lack of standardization, inconsistent semantics, system-centricity, insufficiently transparent reasoning, and lack of validation. To address these shortcomings, we proposed a compilatory framework to characterize complexity using the Five Ws information-gathering method. The answer to the WHO question proposed four complexity viewpoints; the answer to the WHY question proposed a two-dimensional structure for complexity drivers; and the answer to the WHAT question derived generalized complexity challenges. As a preliminary step to show the potential of the framework to characterize complexity, we used and validated it as a tool to structure general literature related to complexity. In general, our findings suggest that papers with complexity solutions do not frame their research within the complexity problem domain, hindering the contribution evaluation. Through the viewpoints, we identified general research gaps of six solution directions. From the drivers, we noted three observations in the discourse of complexity origins: (1) a system-driven tendency, (2) a preference for concreteness vs. abstraction, and (3) an unclear distinction between origins and effects. Through the challenges’ findings we explored two hypotheses: (1) a system-centric preference; and (2) a solution-oriented vision, both of which were supported by the results (most challenges relate to the system viewpoint and challenges are defined based on solution directions).

show abstract

Systems Engineering: Making People Talk!

Cited by 4 publications

References 14 publications

Ontology Learning for Systems Engineering Body of Knowledge

Ontology Learning for Systems Engineering Body of Knowledge

Enabling inter-organizational change integration in sociotechnical systems : Systems thinking applied in the Dutch railway system

Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

Contact Info

Product

Resources

About