Coordination of distributed design work is an important activity in large-scale and complex engineered systems (LSCES) design projects. Coordination strategies have been studied formally in system design optimization and organizational science. This article reports on a study to identify what strategies are used in coordination practice. While the literature primarily offers prescriptive coordination strategies, this study focussed on the contribution of individuals’ behaviours to system-level coordination. Thus, a coordination strategy is seen as a particular set of individual actions and behaviours. We interviewed professionals with expertise in systems engineering, project management and technical leadership at two large aerospace design organizations. Through qualitative thematic analysis, we identified two strategies used to facilitate coordination. The first we call authority-based and is enabled by technical know-how and the use of organizational authority; the second we call empathetic leadership and includes interpersonal skills, leadership traits and empathy. These strategies emerged as complementary and, together, enabled individuals to coordinate complex design tasks. We found that skills identified in competency models enable these coordination strategies, which in turn support management of interdependent work in the organization. Studying the role of individuals contributes an expanded view on how coordination facilitates LSCES design practice.

Machine learning has shown its potential to support the knowledge extraction within the development processes and particularly in the early phases where critical decisions have to be made. However, the current state of the research in the applications of the machine learning in the product development are fragmented. A holistic overall view provides the opportunity to analyze the current state of research and is the basis for the strategic planning of future research and the actions needed. Hence, implementing the systematic literature survey techniques, the state of the applications of machine learning in the early phases of the product development process namely the Requirements, functional modelling and principal concept design is reviewed and discussed.

Travelers interact with a large number and variety of products and services during their journeys. The quality of a travel experience depends on a whole urban mobility system considered in space and time. This paper outlines the relevant concepts to be considered in designing urban mobility. The goal is to provide a language and insights for the early stages of a design process. A literature review sheds light on the complexity of urban mobility from technical, sociotechnical, and user experience perspectives. Observations of experiences in urban areas provide data for describing and understanding travel experience patterns and issues. The paper proposes a conceptual model to describe and analyze different facets of traveler experience and categorizes problems that travelers face when they interact with an urban mobility system. A case study is reported illustrating the use of the conceptual model in identifying travel problems for a demand-responsive transport service.

Introduction: The “chain of survival” is a 5-link theoretical construct that has been central to cardiac arrest resuscitation for over 40 years. Although the role of each link has been extensively studied, little is known about the impact of performing the chain of survival in sequence. The purpose of this study was to estimate the proportion of out-of-hospital cardiac arrest (OHCA) responses by Emergency Medical Services (EMS) that had an intact chain of survival sequence response, and the effect of this on survival to hospital discharge. Methods: We conducted a prospective cohort study of adult (>age 20 years) OHCA patients using data collected between 2005-2007 by the Resuscitation Outcomes Consortium (ROC). ROC is a research network involving 10 research sites and 264 EMS agencies across North America. Using routinely collected data, we coded cases as receiving an intact or non-intact chain of survival sequence based on EMS cardio pulmonary resuscitation (CPR), rhythm analysis or defibrillation, epinephrine administration or endotracheal intubation, and transport to a hospital with an electrophysiology lab or percutaneous coronary intervention capability, contingent on the patient’s condition when EMS arrived. Multiple variable logistic regression was performed, adjusting for known (Utstein) survival predictors, to estimate the independent effect of intact chain of survival sequence on survival to hospital discharge. REB approval was obtained. Results: We enrolled12,821 OHCA cases, of which, 29.4% (n=3,773) had an intact chain of survival and 7.6% (n=972) survived to hospital discharge. Cases with an intact chain of survival were younger, and more likely to arrest in public, receive bystander CPR, occur in the USA and specific ROC sites, and had faster EMS response times. The adjusted odds ratio of survival to hospital discharge with an intact chain of survival sequence was 2.4 (95% CI: 2.1-2.8). A sensitivity analysis of 4,056 cases with known timing of endotracheal intubation found a similar adjusted odds ratio of 2.1 (95% CI: 1.6-2.8). Conclusion: Our results indicate that OCHA resuscitation with an intact chain of survival occurs in approximately 1/3 of cases, and results in over a two-fold increase in the odds of surviving to hospital discharge. Initiatives to improve EMS teamwork and increase the proportion of OHCA resuscitation with an intact chain of survival appear to be warranted.

Introduction: Paramedics are sometimes called for crisis management and relief of symptoms or for patients receiving palliative care. To address the mismatch between the system protocols and resources, and patient’s goals of care, a new protocol, new medications, and an 8-hour training program Learning Essentials Approach to Palliative Care (LEAP) were implemented in our provincial EMS system. Methods: Prior to attending their training session paramedics received an invitation to complete an online survey regarding their comfort, confidence, and attitudes toward delivering palliative care. Comfort and confidence questions were scored on a 4-point Likert scale, while attitudes toward specific aspects of care were scored on a 7-point Likert scale. Descriptive statistics were calculated. Identifiers will permit linkage of these responses to a repeat survey post-implementation. Results: 188 (58%) paramedics completed the survey of the 325 who opened the link. 134 (68%) were male with a mean age of 38.5 years. 95 (50%) were primary care paramedics. The average experience as a paramedic was 12.7 years, with an estimated mean number of palliative calls per year of 9.6 each. On a 4 point scale, most (156, 83%) were comfortable with providing care to someone with palliative goals, and 130 (69.1%) were comfortable providing care without transport. Only 82 (43.6%) were confident they had the tools to deliver this care, and 76 (40.4%) were confident they could do so without transport to hospital. On a 7 point scale, paramedics disagreed with the statement “caring for dying persons is not a worthwhile experience for me”, median 7 (IQR 5-7). Paramedics also disagreed with the statement “Dying persons make me feel uneasy”, median 5 (IQR 4-6). Conclusion: Prior to the implementation of the new protocol, medications, and training, most paramedics were comfortable with the concept of providing care with palliative goals and felt that caring for dying persons is a worthwhile experience, but they were not confident that they have the tools and resources to do so. This suggests paramedics would be open to system improvements to meet an unmet healthcare need for crisis management of patients with palliative goals of care.

Though simulation models are extensively used for detailed design analysis, they find limited role in preliminary design decisions. We have developed a machine learning based approach to enable detailed simulation models to be harvested for supporting early-stage design of engineering systems.

This paper presents a methodology for assessment of diagnosability of mechanical and hydraulic systems. The method is developed on the basis of relationships between system performance parameters and physical objects, that is, components of the system. These relationships are identified by system functional domain and are modeled in terms of a bipartite graph, called Diagnosability Bipartite Graph (DBG). A matrix called Diagnosability Matrix (DM) represents the DBG. Various diagnosability parameters of the system are derived from the DBG and the DM and these are useful in evaluation and comparison of design variants of the system. These parameters: are maximum number of set conflicts (MNS), maximum number of components in a set conflict (MNCS), diagnosability effort and cost (DEC), and average merit of diagnosability (AMD). The design having the lowest value of MNCS, AMD, and DEC; and highest value of MNS has the highest diagnosability. On the basis of these, a best design alternative is selected from diagnosability point of view. Moreover, components, which have poor diagnosability, are also identified. Maximum number of set conflicts (MNS) also guides in system fault diagnosis. The proposed procedure aids in the design and development of maintainable systems from diagnosability consideration. The method can also be used for evaluating and comparing the diagnosability of the systems. This method is illustrated with the help of two examples.

A fixed set of components with a fixed set of properties is often regarded as a defining characteristic of configuration design problems. In configuration design for larger and more complex systems (e.g., street cars), however, this often is not really true. The reason is that sometimes the component library offers no component that meets the actual requirements, so that a new component has to be added to the library. In general, configuration design for larger products must be interactive: interactive in the sense that the user controls the configuration process and in the sense that the phases of knowledge acquisition and configuration are partly mixed. This paper describes a method and a corresponding software tool (SyDeR, System Design for Reusability) that support the interactive configuration design of complex products, especially in the tendering phase. It combines three different technologies:

[bull ] structural modeling of technical systems;

[bull ] a library for technical solutions, which is based upon taxonomies and allows the reuse of the technical solutions;

[bull ] constraint techniques to propagate design decisions and check designs for consistency to support interactive configuration design.

This paper gives an overview of the functionality of the SyDeR tool and describes the main ideas behind the modeling language, which is especially oriented towards the requirements of system design problems. It also explains how we integrated structural modeling, taxonomies, and advanced constraint reasoning techniques into real-world applications.