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This paper aims to develop a risk assessment framework that addresses both the complexities of the risk landscape that green transition portfolios face, but is recognizable and easily understandable by stakeholders. For this purpose, we build upon the framework of NASA Technology Readiness Levels (TRLs). This study analyzes six existing readiness levels framework that are held towards uncertainty factors from the Green Transition. The TRL scale are coupled with Risk, Uncertainty, and Ignorance to score the individual level of uncertainty. The paper ends with suggestion for further studies.

The operation of large production assets requires many decisions from the acquisition and design of new assets to the choice of lubricant for a specific piece of equipment. The decisions made in maintenance have a direct effect on the management of the production process, making it important to ensure correct maintenance decision making. However, studies on maintenance decision making tend to focus on smaller areas of decisions being made in a process, but rarely the entire process. To introduce more studies that consider the entire maintenance process, this paper proposes using a modular Maintenance Decision Architecture. The paper introduces a framework for structuring information sources into standardized information modules and mapping them to maintenance decisions made across the entire organization. The application of approaches from product, system, and service engineering are used to support the management of the complexities of maintenance of large production facilities.

In this paper, a case study of a redesign process for 3D-printed parts has been analysed. The purpose was to compare the implementation of specialist knowledge in hands-on engineering tasks with the previous experience-based approach. Here, specialist knowledge refers to systematic experimental work as a basis for Computer Aided Engineering (CAE). The case involves a set of compliant arms for an oil extraction device developed by a start-up company. Tensile tests of 3D printed dog-bone were performed to characterise the Young's modulus, tensile strength, and orthotropic behaviour of the material to build a material model based on Finite Element Analysis (FEA). With the material characteristics and three simple tests to estimate the optimisation constraints, the existing solution was disproven. Then, new solution candidates were generated and evaluated with input from the start-up company. The process resulted in a feasible solution as well as a reduction of maximum stress from 54MPa to 20MPa. The case highlights the value of specialist knowledge for characterisation of new technologies and design space constraints to reduce and improve iterations to solve a practical design problem.

Aiming to decouple value creation from resource consumption, the Circular Economy is considered an alternative to the current linear model of production and consumption. Among the innovative circular business models, Product-Service Systems (PSS) have been recognized as a possible route to achieve enhanced sustainability performance through the extension of product lifespans and the reduction of product substitution. However, PSS may lead to rebound effects due to less careful behavior during the use phase, which compromises product durability. Currently, the effect of non-ownership models on product care is not yet fully understood, nor are the strategies that could enable better product care. This research aims to deeper comprehend the consumer-product relationships in PSS solutions, as well as to shed light on the potential role of emotional durability in PSS development for product attachment. In order to do so, this paper analyses twelve Product-Service System cases derived from a systematic literature review, categorizing the emotional attachment strategies in each case, and identifying how these strategies might hinder or potentialize PSS solutions.

With the continuously increasing integration of (mechanical) products, the identification and management of trade-offs becomes a major task in product synthesis, with substantial effect on optimality and robustness of the final solution. At the same time, a rigorous and comprehensive study of trade-offs through mathematical design optimisation is often impractical in design, as efforts spent on modeling and optimizing are likely wasted if a chosen design is changed. Extending research on configuration redesign based on a multiobjective monotonicty analysis (MOMA), this paper presents three levels of evaluation for early design or redesign: (I) informal evaluation, (II) opportunistic evaluation, and (III) exhaustive evaluation. The chosen level depends on what knowledge the designer wants to gain, and the higher the level, the larger the analysis effort, the lesser the re-use of the information gained from the initial MOMA analysis respectively. The approach is illustrated using a novel drug delivery device, the Self-Orienting Millimeter-Scale Applicator (SOMA), for the oral delivery of protein compounds such as insulin.

Robust Design offers a coherent and widely appreciated approach for the parametric exploration of the design space by means of simulation or experimentation, which is well-established in the quality-by design domain. From the perspective of design research, however, this only addresses a relatively narrow part of the design process and is not fully integrated with other design decisions such as concept exploration, the suitable configuration of system elements, or the design of interfaces. Particularly in light of the growing importance of developing technologically advanced and “smart” systems, it seems that a new methodical perspective on Robust Design is needed. Against this background, this paper consolidates knowledge and insights from different research fields and industry sectors. On this basis, new angles to the discussion on product robustness in different domains are explored in order to suggests directions for action and new research areas, both with respect to a methodical RD approach as well as the question of systematic research procedures.

The Danish Energy Islands are one of the world’s most ambitious clean energy program The construction of the Energy Islands on Bornholm in the Baltic Sea and in the North Sea, approximately 80 km from Thorsminde, a town on the cost of western Jutland, are one of the world’s most ambitious green energy programs. The Islands will serve as hubs for connecting and distributing power from the surrounding offshore wind farms (OWF) to several countries. It is expected to have an initial capacity of 3 GW of offshore wind and later reach full capacity at 10 GW for the island in the North Sea, which will be the first of several hubs in the North Sea that is planned to be put into operation in 2033 [1]. Given the scale of the new system and outstanding challenges, the time window of 10 years is rather narrow to design, build and guarantee that risks to health, safety, environment, assets, cost, and uninterrupted electricity supply are under control for the whole lifetime of +80 years. The consequences of failing to predict and manage the risks of complex global systems, like the Energy Island and connected to it systems, can be immense. The Island will have broad social impact and deficits in risk governance that, in particular, do not properly account for the diversity of different values of involved stakeholders may result in loss of credibility in management institutions. Insufficiently managed risks - from health & safety to cost - can bring the largest engineering programs to a sudden halt: For good reason, injuries, and deaths on construction sites and during operations are unacceptable – both from an ethical as well from a legal and reputational point of view. And we can expect significant public scrutiny regarding promised budgets, schedules, and technical performance. The technology to build the Energy Island and the whole offshore wind power system is largely available. However, the scale of the new system, the interconnectivit

The recently proposed glycogen accumulating organisms (GAOs)-driven anammox process, which terminates nitrate (NO3–) reduction to nitrite (NO2–) without external carbon source addition, has emerged as a promising alternative for supplying NO2– to anammox bacteria. The endogenous partial denitrification anammox (EPDA) process demonstrates superior nitrogen elimination efficiency, cost-effectiveness, and operational stability in low C/N wastewater treatment, concurrently mitigating greenhouse gas releases. This comprehensive review presents and discusses an in-depth analysis of the notable progress in EPDA, covering the physiology and biochemistry of diverse GAO-lineages under specified conditions, intricate microbial interactions and metabolic pathways shared between GAOs and anammox bacteria, and appropriate process modifications. Strategies for sludge morphology, carbon content, and spatial distribution of functional bacteria are discussed in detail to regulate the metabolic activity of EPDA. Future research needs to focus on balancing the competitiveness between functional consortia such as GAOs, phosphorus accumulating organisms (PAOs) and anammox bacteria in the synergetic system, and countermeasures to deal with the effects of adverse conditions on nutrient removal performance of the EPDA-based processes.

Objective To identify whether a diagnosis of depression combined with rurality, compared with either depression or living in metropolitan areas alone, is associated with experiencing more stressful life events in pregnancy. Design This study uses data from 402 pregnant women (206 metropolitan and 196 rural), enrolled in the Western Australian arm of the Mercy Pregnancy and Emotional Wellbeing Study. Mercy Pregnancy and Emotional Wellbeing Study is a prospective, longitudinal cohort with women recruited during early pregnancy (<20 weeks) across 3 groups: those with diagnosed depression, those taking antidepressant medication and control. Participants Women were recruited from 3 metropolitan and 3 rural hospitals in Western Australia from 2017 to 2018 and 2018 to 2020, respectively. This study uses antenatal data collected at recruitment and during third trimester (weeks 32-34). Main outcome measures The Stressful Life Events Scale was used to measure the number of self-reported stressful events. The degree of perceived stress due to the stressful event was also reported. Results Compared to pregnant metropolitan women diagnosed with depression, pregnant rural women with depression were more likely to report experiencing at least 1 stressful life event. Despite this, pregnant women with depression in both regions reported similar numbers of stressful life events. Conclusions This study highlights women in rural Western Australia diagnosed with depression might be more vulnerable to experiencing stressful life events than rural women without depression and their metropolitan counterparts. Due to known adverse effects of antenatal depression and stress on maternal well-being and child outcomes, there is a clear need for targeted, preventative interventions for Australian rural women during this period.

Objective To identify whether a diagnosis of depression combined with rurality, compared with either depression or living in metropolitan areas alone, is associated with experiencing more stressful life events in pregnancy. Design This study uses data from 402 pregnant women (206 metropolitan and 196 rural), enrolled in the Western Australian arm of the Mercy Pregnancy and Emotional Wellbeing Study. Mercy Pregnancy and Emotional Wellbeing Study is a prospective, longitudinal cohort with women recruited during early pregnancy (<20 weeks) across 3 groups: those with diagnosed depression, those taking antidepressant medication and control. Participants Women were recruited from 3 metropolitan and 3 rural hospitals in Western Australia from 2017 to 2018 and 2018 to 2020, respectively. This study uses antenatal data collected at recruitment and during third trimester (weeks 32-34). Main outcome measures The Stressful Life Events Scale was used to measure the number of self-reported stressful events. The degree of perceived stress due to the stressful event was also reported. Results Compared to pregnant metropolitan women diagnosed with depression, pregnant rural women with depression were more likely to report experiencing at least 1 stressful life event. Despite this, pregnant women with depression in both regions reported similar numbers of stressful life events. Conclusions This study highlights women in rural Western Australia diagnosed with depression might be more vulnerable to experiencing stressful life events than rural women without depression and their metropolitan counterparts. Due to known adverse effects of antenatal depression and stress on maternal well-being and child outcomes, there is a clear need for targeted, preventative interventions for Australian rural women during this period.

Never before has the recognition of the need for solutions to the challenges of sustainability been greater. With a rising population of increasing wealth, we have recognised that humankind is “out of planetary compliance”. Or in other words, we are borrowing from next generations, each and every day, with the direct negative effects of raising atmospheric temperatures (global warming), poisoning of our land and waterways, and threatening the biodiversity of the planet – to name but a few. The response to these challenges is finally reaching critical mass. From Climate Summits, through United Nations Sustainable Development Goals, to Circular Economy campaigns, global action is happening. International associations, geographical regions, and individual countries are making bold moves to enact action against climate change. Measurements are being made on numerous sustainability goals. And the younger generation is successfully increasing its pressure on the incumbent world and industry leaders. But how can engineering systems interpret these agendas and make a contribution to sustainability transition? What is the potential of taking a socio-technical holistic view on large and complex engineering systems, with a view to improving its sustainability performance? This chapter provides a brief overview of key sustainability developments in the past, which have laid the foundation for how engineering systems can contribute to a sustainable future through holistic socio-technical design. It also provides some paths forward for engineering systems, but some of the paving stones are still missing, so this chapter is also intended as a call to action.

Engineering Systems Design is an emerging perspective with a growing community. The preceding chapters in the Handbook of Engineering Systems Design presented the engineering systems perspective, models for describing and methods for designing interventions in engineering systems, as well as reflections on the use of those methods and upcoming practice, educational and policy challenges. In this chapter, we are taking a look at the future of Engineering Systems Design. We start by highlighting productivity, sustainability and resilience as three societal objectives, and proceed to discuss critical paradoxes we must address through engineering systems interventions: providing a high standard of living for everyone, without paying the environmental price; a fast minimisation and mitigation of climate change without taking risks; and the challenge of global transformations respecting local needs. We continue to discuss what we consider three critical engineering systems design capabilities we must develop to resolve these paradoxes: the ability to manage systems requirements at societal scale; the development of scale-covariant engineering systems; and mastering connectability. We conclude the chapter with a call to action for researchers, practitioners and policy makers to advance theory, design methods and tools, and stakeholder outreach development to strengthen our engineering systems design capabilities., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Ethics & Philosophy of Technology

Uncertainty is the third major perspective in understanding and designing engineering systems, along with complexity and human behaviour. Risk, a corollary of uncertainty, is understood as the effect of uncertainty on objectives. When designing engineering systems, you cannot not manage risk - even ignoring risk equates to a decision to accept it. Engineering systems are characterised by long life cycles, changing operational environments, and evolving stakeholder values, leading to a wide range of uncertainties in their design and operation. Productively engaging with this uncertainty is critical for successfully operating and especially (re-)designing engineering systems. This chapter provides an overview of managerial practices to address the three levels of increasing uncertainty in engineering systems design: from (1) managing risk, to (2) managing uncertainty, to (3) managing ignorance. We differentiate for each level of uncertainty between two levels of value diversity: (1) primarily commensurate values (i.e. agreement on core values by critical stakeholders) and (2) primarily incommensurate values (i.e. no agreement on core values). The managerial practices we discuss are “classic” risk management, public engagement, scenario planning, robust decision-making, resilience, and applying the precautionary principle. In addition, we briefly illuminate the actuality of management practices dealing with the different levels of uncertainty beyond explicit, formal processes, the understanding of managing uncertainty as both modelling and decision support practices and personal and organisational biases in the context of addressing uncertainty., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Policy Analysis

Unplanned design iterations are considered one of the reasons for the high failure rate of new product development (NPD) projects. Generally, organisations employ ‘proactive risk management’ (PRM) and ‘reactive fast learning’ (RFL) to manage unplanned design iterations. This paper aims to explore how organisations employ PRM and RFL approaches to manage unplanned design iterations in the NPD process. To that end, a cross-sectional interview study was conducted in eight organisations. The interview transcripts were analysed as a primary data source using thematic qualitative text analysis technique. For PRM approach, results demonstrate that the design teams were more active in risk monitoring in the design phase as compared to risk identification in the concept development phase. Generally, design teams reduced the likelihood of unplanned design iteration risks by employing learning methods in addition to risk mitigation strategies. For RFL approach, results reveal that organisations lacked a structured approach to select suitable learning methods for fast resolution of unplanned design iterations and to convert new knowledge into organisational learning. We conclude that PRM is more established as compared to RFL in managing unplanned design iterations. We develop recommendations of how organisations can use RFL approaches more efficiently alongside PRM approaches.

Engineering-heavy new product development (NPD) projects face unplanned design iterations, which can cause failure in terms of missed targets for cost, schedule, quality, and customer satisfaction. These unplanned design iterations can be understood as the occurrence of a specific category of engineering project risks. As a result, companies employ structured actions to mitigate these risks in projects. However, even with such strategies in place, projects can still struggle to achieve their targets. This study aims to explore how companies employ risk mitigation actions to manage risks in engineering-based NPD projects. To investigate this topic, a survey of employees in the aerospace and defense industries was conducted. We analyzed the responses using statistical methods. The results indicate that risk mitigation actions are used according to thematic clusters, in line with our findings from the literature. Furthermore, the selected mitigation measures show collective explanatory power for handling engineering project risks, suggesting that while some projects that employ mitigation actions may still fail, their use of such measures does still reduce the overall impact of risks. Interestingly, the results of the statistical analysis show no significant difference in the employment of risk mitigation actions in engineering-based NPD projects, whether they employ waterfall or agile NPD methods, or a mixture of both. These results suggest that companies should consider all classes of risk mitigation actions to manage engineering project risks. On this basis, the wider contextualization of individual mitigating actions should be taken into account when planning risk mitigation for engineering-based NPD projects.

The objectives and scope of a construction project is defined in the early design stage, the fuzzy front-end. This stage is crucial for project risk management and success, but traditional risk management tend to focus on operational risk in later design stages. This action research study leverages co-design methodology and the project management actuality perspective to tailor a risk management process for the fuzzy front-end of construction projects in a large client organization. The co-design process help enchance stakeholder value perception of the designed solution.

This report explores the mitigation of non-communicable disease (NCD) risk factors asso-ciated with out of home modern food culture through a system-oriented design approach. Using a holistic approach, the authors explored the food system surrounding the modern out of home food culture in Denmark with a focus on stakeholder interviews. From this, the authors identified online food delivery (OFD) as an area in need of innovative solutions to mitigate the threat OFD pose to public health by giving consumers easy access to food prepared away from home anytime and anywhere. The report primarily investigates the connection between healthy diets and the type of OFD platform defined as meal delivery (MD) applications (apps). An analysis of how the five MD apps operating in Denmark impact food choices in the Danish digital foodscape was conducted. This report offers a tangible overview of MD apps and the opportunities and challenges related to NCDs that these platforms pose. It is determined that MD apps contribute to food accessibility by extending reach of food outlets (FO) and that they operate in both urban and rural areas. Further, it is found that there exists misinformation and that current policies on provision of food information to consumers are not adhered to. Moreover, it is found that the MD apps have the potential to nudge consumer decisions through their user interface and the companies’ use of digital marketing. This report does not aim to stop OFD but investigates what measures should be made to ensure the expansion of the digital foodscape will not lead to an increased health burden.

With further emancipation of once subdued or marginalized stakeholders, a growing number of megaprojects face increasingly significant social resistance. Asymmetries of support for the projects emerge, rooted in different perceptions of legitimacy across different stakeholder groups. In this paper, we ask how these diverging perceptions of legitimacy develop across stakeholders of cross-border megaprojects. We conduct a multi-site ethnography at one of the biggest contemporary cross-border transport megaprojects in the world – the Danish/German Fehmarnbelt Fixed Link. Tying together three streams of the legitimacy literature in a new analytical approach, we suggest three dimensions of project legitimacy perception: trust, majority, and morality. In doing so, we provide a new integrative model of legitimacy perception in megaprojects. We illustrate how these legitimacy dimensions dynamically interact. We thus provide new insights on how project legitimacy is continuously renegotiated in megaprojects with implications for future developments of project governance.

Purpose: Most complex engineering projects encounter unexpected events through their life cycle. These are traditionally attributed to inaccurate foresight and poor planning. Outlining a nonanticipatory alternate, the authors seek to explain the ability to rebound from unexpected events, without foresight, using resilient systems theory. This paper seeks to outline the theoretical underpinnings of project resilience and to identify criteria for planning and selecting projects for greater resilience. Design/methodology/approach: Investigating project resilience, this paper studies the relationship between unexpected events and project performance in 21 projects. The authors perform a systematic review of project ex post evaluations 3–12 years after project completion. Findings: First, the authors find that all projects encountered unexpected events, even when discounting planning error. Second, the authors show that, as a consequence, projects underperformed, not necessarily relative to formal criteria, but in terms of subjective opportunity cost, that is, relative to competing alternates – known or imagined – foregone by their implementation. Finally, the authors identify four types of resilient projects – superior, equivalent, compensatory and convertible projects – as opportunities for building project resilience. Practical implications: The properties of resilient projects provide opportunities for building resilience in complex projects. Originality/value: Departing from traditional efforts to “de risk” plans and “de-bias” planners, this paper focuses on the properties of projects themselves, as an alternate to improved foresight and up-front planning.

Sie müssen kurzfristig einen Projektplan skizzieren oder überarbeiten, oder eine wichtige Projektbesprechung vorbereiten? Konzentrieren Sie sich auf die folgenden sechs Bereiche und die dazugehörigen Fragen: 1. Stakeholder: Wer sind Freunde und Unterstützer für dieses Projekt? Mit wem stehen wir in Konkurrenz? Wie erarbeiten Sie sich die Unterstützung aller wichtigen Stakeholder? Abschn. 17.2.2 2. Umfang und Ziel: Was ist das Ergebnis des Projekts, was sind die Teilergebnisse und was die Hauptarbeitsschritte (Arbeitspakete)? Abschn. 17.3.1 3. Zeitplan: Wie ist der logische und zeitliche Ablauf der Arbeitspakete, was sind die Hauptabhängigkeiten, wie lange dauert jede Aktivität und was die Gesamtdauer (x Pufferfaktor)? Abschn. 17.3.2 4. Ressourcenbedarf: Welche personellen und technischen Ressourcen, wann und in welchem Umfang benötigen Sie für das Projekt (x Pufferfaktor)? Abschn. 17.3.3 5. Finanzbedarf: Welches Budget wird für das Projekt benötigt (Personentage x interner Verrechnungssatz x Aufschlag für nicht-personelle Ressourcen x Pufferfaktor)? Abschn. 17.3.4

As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

Uncertainty exists when action must be taken without knowledge of the possible outcomes and the probabilities of their occurrence. This is evidently the case in many real-life projects. Recent literature calls such projects ‘exploratory’, i.e. their goals and the means to attain them are uncertain at the outset. This presents a challenge to traditional project management—working from known means towards known ends—and may explain high rates of project failure. Nonetheless, prescriptions for managing exploratory projects remain situational and fragmented across schools of thought. The aim of this paper is to identify the repertoire of approaches adopted in practice by managers of such projects, and to outline the theoretical underpinnings of exploratory project management. Through the lens of resilience theory, we investigate the approaches adopted by 19 managers of exploratory projects across 14 Danish firms. The paper's contribution is two-fold: First, we present a consistent repertoire of eleven generalizable approaches to managing exploratory projects across a range of industries and project types. Second, outlining shared theoretical underpinnings, we explain the repertoire as preparatory, (pre-action), attemptive (during action) and responsive (post outcome) efforts to achieve resistance to and recoverability from unexpected events. Fundamentally, we argue for shifting focus from ‘what we know’ to ‘how we act’ when faced with exploratory projects.

Purpose - The Digital Transformation brings change to organizations, their processes, and their production systems. Nevertheless, most efforts observed in its context tend to be technology-driven, and it is often argued that Quality Management is inadequately integrated into the discussion. Design/methodology/approach - Surveying the literature, this work reviews, list, and organizes the different technological concepts and integration opportunities that have been explored in the scope of Quality Management in the Digital Transformation. Findings - Findings include the expanded capacity of quality tools and methods for managerial purposes; the reinforced importance of Data Quality; the increased automation and augment resources for Quality control; and the increased process optimization and integration of systems and between organizational areas. Originality/value - It is demonstrated that although scattered in the literature, there are already a number of works exploring the impacts of technology in the management of Quality in the scope of the Digital Transformation. Three main areas for integration arise: (a) Digital Quality Management (application of industry 4.0 technologies to Quality Management itself, its tools, methods, and systems), (b) the management of the Quality of digital products and services, and (c) the management of the Quality of digital product development and production processes.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

Soon, we will all have convinced ourselves that we knew all along what was going to happen. Hindsight bias is how our brain manages its scarce resources and protects us from losing faith. The reality is that for the time being, both policy makers and business leaders have to keep making some of the biggest decisions of their lives under some of the worst uncertainty of their lives. In a previous article, we talked about how we can use resilience thinking to make better choices. Today, we want to look at another crucial aspect: how can we ensure the legitimacy of our actions, i.e., reflect on how much support we can expect from the general public or our employees for what we are about to ask of them. Megaproject management may not be the first area of expertise you turn to for advice in the current situation. We will explain in a little while why you should. Our interest in megaproject management focuses on the risk management side of things, particularly risks surrounding public support (or opposition) of these rather impactful and wide ranging endeavours. Here is why looking at megaprojects for inspiration in the current situation is interesting: They are very significant investments, they cause changes at societal scale (at least locally), they are unique, with a significant dose of first-of-a-kind actions, and at some point they are over and transition what they build into operations. That does sound a bit familiar these days. While legitimacy is important, there are also other factors. Most notably, legality and feasibility. A common pitfall for managers of megaprojects and business leaders or policymakers alike, is to take action that is legal (or at least: later legalised) and feasible, but not seen as legitimate. That leads into dangerous territory of provoking significant resistance. There are three aspects to the legitimacy of megaprojects that also apply to the legitimacy of the rather drastic actions being taken today b

When I started running the numbers at the end of January, I reluctantly began to draw my own conclusions regarding plausible future scenarios. I had a hard time convincing myself. I subsequently (re) learned that good old fashioned ‘denial’ is the first step of dealing with any crisis. As any good academic, I had written about it, but was strangely irritated when I experienced it myself. First, inside my own head, then with people I talked to. I’m writing when the coronavirus pandemic is in its initial stages. We are collectively snapping out of ‘denial’ right now, which is followed by panic, then anger, and eventually, a new pragmatism (discussed nicely by Karl Taro Greenfeld in this article for The Atlantic). I want to share some thoughts on fast-tracking your organisation towards the ‘new pragmatism’ stage. If you think risk management is a fairly specialised field, wait until you discover the many tribes that share it and constantly bicker about what exactly it is and means. I will highlight some thinking principles from corners that rarely make front page news: deep uncertainty, resilience and psychometric risk assessment.

Rare events are common: Even though any particular type of ‘rare event’ - a world war, global economic collapse, or pandemic for that matter - should only occur once every 100 years, there are enough of those types of ‘rare events’ that overall, they commonly occur about once every 10 years. As we are currently experiencing with the COVID-19 pandemic, we do not sufficiently leverage the rich toolset that risk management offers to prepare for and mitigate the resulting uncertainty. This article highlights four aspects of risk management, and their practical and theorical implications. They are: 1) Risk (in the narrower sense), where possible future outcomes can be captured through probability distributions. 2) A situation of uncertainty, where there is transparency regarding what is not known, but probability distributions are unknown, as well as causal relationships influencing the outcome in question. 3) A situation of ignorance, where there is no understanding that certain possible future developments are even relevant. And finally: 4) The emergence of organizational and inter-organizational myopia as an effect of risk, uncertainty and ignorance on collective human behaviour.

It is now widely recognized that many important events in the life cycle of complex engineering systems cannot be foreseen in advance. From its origin in ecological systems, operating without the use of foresight, resilience theory prescribes presuming ignorance about the future, and designing systems to manage unexpected events in whatever form they may take. However, much confusion remains as to what constitutes a resilient system and the implications for engineering systems. Taking steps toward a synthesis across a fragmented body of research, this paper analyses 251 definitions in the resilience literature, aiming to clarify key distinctions in the resilience concept. Asking resilience of what, to what, and how, we first distinguish systems serving higher ends and systems that are ends in themselves, and, within these, performance variables to be minimized, preserved, or maximized. Second, we distinguish systems subject to adverse events, adverse change, turbulence, favorable events, favorable change, and variation. Finally, we distinguish systems capable of recovery, absorption, improvement, graceful degradation, minimal deterioration, and survival. Together, these distinctions outline a morphology of resilient systems and suggest answers to the principal design questions, which must be asked of any resilient engineering system.

Mixed culture anaerobic processes are important to environmental systems, including the global carbon cycle, and industrial and environmental biotechnology. Mixed culture metabolic modelling (MM) is an essential tool to analyse these systems. MM predicts microbial function based on knowledge or assumption of cellular metabolism. It may be developed based on observations at the process level – biochemical process modelling (BPM) or fundamental knowledge of the cell being modelled – cellular level modelling (CLM). There is a substantial gap between these two fields, with BPM not considering genetic constraints, particularly where this may be important to interspecies interactions (e.g. amino acid transfer), and CLM commonly not considering mass transfer principles, such as advection/diffusion/migration. No unified approach is useful for all applications, but there is an increasing need to consider genetic information and constraints in developing BPM, and translate BPM principles (including mass-transfer and inorganic chemistry) for application to CLM.

How did your organization handle its last major transformation? You had a detailed plan, discussed at length – and then what happened? We recently put that question to 40 senior executives responsible for transforming organizations in the production, engineering, consulting, and financial service sectors. Most stories had three parts: The plan, a surprising “but then… ,” and finally a response to the “post-surprise reality” (or what we may just call “reality”). The third part is the most important part of any transformation, because this is where the transformation happens in the organization. We argue that the success or failure of major transformations depends not on better predictions, better plans, or better visions. Transformations depend on responding effectively to what we cannot practically know in advance: surprises.

Risk management is a common and widely adopted project practice. Practitioners use risk management based on a common assumption that risk management adds value to projects. Yet, in the complex and ambiguous environment of a project, value is often subjective. If this is the case, then how do stakeholders perceive project risk management to create value? This paper presents a literature review and an empirical study of project risk management as a means of creating value. The empirical study is based on interviews, analyzed through qualitative analysis, to unravel the subjective value of project risk management. Specifically, we addressed how practitioners perceived the connection between project risk management practices and value creation. We found that stakeholders' perceptions of value played an important role in how value was created through project risk management. What a stakeholder perceives to be important, such as the prospective outcomes of a project, influences the perceived value of a given project risk management practice. The empirical findings indicate the need for a contextualized understanding of the value of project risk management, and thereby provide a more nuanced view of the variety of forms through which project risk management can create value. The findings question the “universal ideal” of PRM value creation portrayed in the academic and practitioner literature.

Mixed culture anaerobic processes are important to environmental systems, including the global carbon cycle, and industrial and environmental biotechnology. Mixed culture metabolic modelling (MM) is an essential tool to analyse these systems. MM predicts microbial function based on knowledge or assumption of cellular metabolism. It may be developed based on observations at the process level – biochemical process modelling (BPM) or fundamental knowledge of the cell being modelled – cellular level modelling (CLM). There is a substantial gap between these two fields, with BPM not considering genetic constraints, particularly where this may be important to interspecies interactions (e.g. amino acid transfer), and CLM commonly not considering mass transfer principles, such as advection/diffusion/migration. No unified approach is useful for all applications, but there is an increasing need to consider genetic information and constraints in developing BPM, and translate BPM principles (including mass-transfer and inorganic chemistry) for application to CLM.

To drive your digital transformation, you need to become skilful in connecting the past, present and future in a compelling story, write Verena Stingl, Marcus Lantz and Josef Oehmen

There is an abundance of theoretical models of how to engage stakeholders in infrastructure projects. So far, however, there is very little empirical evidence of how, if ever, these models are put to use by project developers and managers in real projects. This paper thus explores how selected PIARC members perceive and work with stakeholders. It reviews attitudes, strategies and techniques used to identify, assess and mitigate stakeholder-related risks and securing additional social value out of the projects. It gives examples of best practice as well as recommendations for improvements. The findings are based on the outcomes of an on-line survey among 21 PIARC members conducted in 2018. In addition, a case study of a Danish road project is presented.

Product development (PD) faces uncertainties caused by rapidly developing technologies, shifting market demands and the changes occasioned by these developments, including new requirements for products being developed and increased difficulty for companies to reliably execute state-of-the-art processes. In this paper, we argue that classic PD risk management methods and tools are based on the ‘predict and plan’ paradigm, which assumes that organisation members involved in PD have sufficient time and resources to identify, analyse and mitigating technology risks and organisational risks. However, the reality of product development is that time and resources are rarely sufficient, and uncertainty is currently being introduced to the development process at an accelerated rate by trends such as pervasive digitalisation. This paper therefore investigates a resilience-inspired approach to PD risk management that abandons the predict and plan paradigm in favour of a ‘monitor and adapt’ approach. We argue that, in industrial practice, predict and plan approach is the de facto risk management baseline, and suggest deliberately tailoring risk management and PD processes to incorporate resilience-based practices. To that end, we provide suggestions for process frameworks and tools organisations may adopt and discuss how resilience and risk management are complementary approaches to traditional PD. Our arguments are supported by a case study of an engineering organisation and additional interviews conducted with members of similar organisations for purposes of validation.

In the design phase of product development (PD) process, most new products face significant uncertainties and risks. Uncertainty is typically associated with a lack of information, while learning is a process that acquires information. Therefore, learning fast and at low cost decreases the uncertainty and increases the efficiency of the product design phase. This paper investigates the concept of the cost of learning in PD’s design phase. Reviewing the literature, we conceptualize the cost of learning and review the learning methods considering three aspects in the design phase of the PD process: (1) costs associated with learning from mistakes and failures, (2) learning methods and (3) categories of learners. This paper thus provides the conceptual foundations for future work to increase the efficiency of the PD process by reducing the cost of learning from mistakes and failures.

Risk management (RM) in new product development (NPD) is often implemented as a standardized framework and ends up being carried out as a tick the box, non-value adding activity. To avoid this problem, RM needs to be tailored to the organization and NPD project. This paper identifies a gap in both understanding and facilitating tailoring, i.e. design of RM systems in NPD. To understand how to design RM systems, we must better understand how RM adds value to NPD activities. We applied Product Development Value Stream Mapping (PDVSM) to RM and conceptualized a Risk Value Stream Mapping (RVSM) framework to support design. Through a state-of-the-art literature review, we identified typical categories of value and waste in RM as well as approaches to model the RM in NPD. We developed and tested components of the RVSM framework based on PDVSM in three case companies. In this paper, results are presented regarding waste, value and potential ways to model the value stream in RM. The framework enables a diagnosis of the current state of RM in companies and supports future design activities pertaining to RM systems. This paper is positioned at the intersection of design, lean thinking and RM.

Effective risk management is complex, as it affects a company at all organizational levels – as does controlling, with which it is closely intertwined. In this article, we explore the question of what an „ideal” risk management for technology companies may look like from the perspective of value creation. This includes both risks in terms of an overarching technology management, as well as risks for single development projects (including large engineering projects). The core questions are: What does value creation mean for risk management? And: Is an ideal risk management for company 1 the same ideal risk management for company 2?

Background: The frequency of late-onset Huntington's disease (>59 years) is assumed to be low and the clinical course milder. However, previous literature on late-onset disease is scarce and inconclusive. Objective: Our aim is to study clinical characteristics of late-onset compared to common-onset HD patients in a large cohort of HD patients from the Registry database. Methods: Participants with late- and common-onset (30–50 years)were compared for first clinical symptoms, disease progression, CAG repeat size and family history. Participants with a missing CAG repeat size, a repeat size of ≤35 or a UHDRS motor score of ≤5 were excluded. Results: Of 6007 eligible participants, 687 had late-onset (11.4%) and 3216 (53.5%) common-onset HD. Late-onset (n = 577) had significantly more gait and balance problems as first symptom compared to common-onset (n = 2408) (P <.001). Overall motor and cognitive performance (P <.001) were worse, however only disease motor progression was slower (coefficient, −0.58; SE 0.16; P <.001) compared to the common-onset group. Repeat size was significantly lower in the late-onset (n = 40.8; SD 1.6) compared to common-onset (n = 44.4; SD 2.8) (P <.001). Fewer late-onset patients (n = 451) had a positive family history compared to common-onset (n = 2940) (P <.001). Conclusions: Late-onset patients present more frequently with gait and balance problems as first symptom, and disease progression is not milder compared to common-onset HD patients apart from motor progression. The family history is likely to be negative, which might make diagnosing HD more difficult in this population. However, the balance and gait problems might be helpful in diagnosing HD in elderly patients.

Building project delivery is beset with many long-standing problems. Often, these problems, resulting in failures of facilities and cost-time overruns, are directly related to poor design and design management practices. This motivated the definition of the main aim to develop an initial framing for the design process support systems, incorporating ideas from the human error and performance management domains, and on checklists. In this conceptual paper, a literature review method is used. It is suggested that cognitive systems engineering could be used to conceptualize the designers work and to incorporate checklists into the design process. Then, key aspects and elements for the development of design process support systems are addressed.

Uncertainty assessment and management, as well as the associated decision making are increasingly important in a variety of scientific fields. While uncertainty analysis has a long tradition, meeting sustainable development goals through long-term Life Cycle Engineering (LCE) decision making demands addressing Deep Uncertainty (DU). DU characterizes situations where there is no agreement on exact causal structures, let alone probabilities. In this case traditional, probability based approaches cannot produce reliable results, as there is a lack of information and experts are unlikely to agree upon probabilities. Due to the nature of LCE, this paper argues that methods to better cope with DU can make a significant contribution to the management of LCE. We introduce a set of methods that use computational experiments to analyze DU and have been successfully applied in other fields. We describe Robust Decision Making (RDM) as the most promising approach for addressing DU challenges in LCE. We then illustrate the difference between applying traditional risk management approaches and RDM through an example, complemented with the interview findings from a company using RDM. We conclude with a discussion on future research directions., Policy Analysis