A functional failure reasoning methodology for evaluation of conceptual system architectures

In this paper, we introduce a new methodology for reasoning about the functional failures during early design of complex systems. The proposed approach is based on the notion that a failure happens when a functional element in the system does not perform its intended task. Accordingly, a functional criticality is defined depending on the role of functionality in accomplishing designed tasks. A simulation-based failure analysis tool is then used to analyze functional failures and reason about their impact on overall system functionality. The analysis results are then integrated into an early stage system architecture analysis framework that analyzes the impact of functional failures and their propagation to guide system-level architectural design decisions. With this method, a multitude of failure scenarios can be quickly analyzed to determine the effects of architectural design decisions on overall system functionality. Using this framework, design teams can systematically explore risks and vulnerabilities during the early (functional design) stage of system development prior to the selection of specific components. Application of the presented method to the design of a representative aerospace electrical power system (EPS) testbed demonstrates these capabilities.     

Architectural design and reliability analysis of a fail-operational brake-by-wire system from ISO 26262 perspectives

Next generation drive-by-wire automotive systems enabling autonomous driving will build on the fail-operational capabilities of electronics, control and software (ECS) architectural solutions. Developing such architectural designs that would meet dependability requirements and satisfy other system constraints is a challenging task and will possibly lead to a paradigm shift in automotive ECS architecture design and development activities. This aspect is becoming quite relevant while designing battery-driven electric vehicles with integrated in-wheel drive-train and chassis subsystems.In such highly integrated dependable systems, many of the primary features and functions are attributed to the highest safety critical ratings. Brake-by-wire is one such system that interfaces with active safety features built into an automobile, and which in turn is expected to provide fail-operational capabilities. In this paper, building up on the basic concepts of fail-silent and fail-operational systems design we propose a system-architecture for a brake-by-wire system with fail-operational capabilities. The design choices are supported with proper rationale and design trade-offs. Safety and reliability analysis of the proposed system architecture is performed as per the ISO 26262 standard for functional safety of electrical/electronic systems in road vehicles.     

Learn to survive crises: The role of firm resilience,innovation capabilities and environmental dynamism

Exogenous crises, while disruptive, may also present learning opportunities that could affect a firm's viability and performance. In this study, we examine how exogenous crises can constitute learning opportunities and assess their impact on firm survival. In particular, we investigate the role of learning in response to exogenous crises and how firm resilience, innovation capabilities, and environmental dynamism influence this relationship. Drawing from crisis management and organisational learning literature, we propose that these factors can bolster the connection between learning from crises and firm survival. To test our hypotheses, we conduct a nuanced analysis using both regression analysis and Fuzzy Set Qualitative Comparative Analysis (fsQCA) on data from 249 Italian manufacturing Small and Medium-sized Enterprises (SMEs). This approach allows us to simultaneously examine the impact of firm resilience, innovation capabilities, and environmental dynamism on the relationship between learning from crises and firm survival. Our findings offer theoretical and practical insights into the role of learning from crises in a firm's survival. They also highlight the importance of embracing learning opportunities in crisis situations and suggest that how firms deal with crises could be an opportunity to fine-tune their internal processes and thrive in the long run.     

Individual latent error detection: is there a time and a place for the recall of past errors?

A task carried out in error creates a latent condition that can result in a future undesirable outcome if the error is not detected later. The paper presents a study of the relatively under-researched phenomenon of post-task latent error detection. Focusing on UK naval aircraft maintenance, it was hypothesised that time, location and systems cues influence individual latent error detection amongst naval air engineers who experience the phenomenon. The systems view of human error is combined with a multi-process approach to post-task latent error research, for which findings suggest that distributed cognition across the entire socio-technical system may be influential in post-task latent error detection. Directions for future research will be of benefit to those interested in furthering safety resilience using a systems approach to minimise the consequences arising from latent error.

Relevance to human factors/ergonomics theoryThe nature and extent of post-task latent error detection is explored using a systems approach, for which distributed cognition across the entire socio-technical system appears influential. The aim of current research is to develop interventions to further mitigate for latent errors and thus advance the systems application of ergonomics theory.     

‘A blessing in disguise’ or ‘as if it wasn’t hard enough already’: reciprocal and aggravate vulnerabilities in the supply chain

We investigate the interrelations of structural and operational vulnerabilities in the supply chain (SC) using discrete-event simulation for a real life case study. We theorise a notion of SC overlays and explore conditions surrounding their appearance. Such overlays occur if the negative consequences of changes in a SC structure as a result of a disruption are either amplified or mitigated by changes in the operational environment. We hypothesise that these overlays can be both reciprocal (i.e. complementary or mitigating) and aggravate (i.e. concurrent or enhancing). Our approach can be used for an efficient management of SC resilience capabilities by varying their levels over time. We show different ripple and bullwhip effect profiles, which lead to either reciprocal or aggravate overlays, and then we develop recommendations on the overlay-driven dynamic variation of resilience capability levels in order to enhance both SC resilience and efficiency through dynamic redundancy allocation. The results can be of value in selecting and deploying operational policies at the right time and scale during and after the recovery periods. Restricting analysis to the disruption period only and ignoring operational dynamics after capacity recovery can result in misleading or inefficient SC resilience and recovery policies.     

Scheduling of recovery actions in the supply chain with resilience analysis considerations

Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.     

Agent-based manufacturing control based on distributed bid selection and publish-subscribe messaging: a simulation case study

Bidding-based negotiation schemes play a major role in multi-agent manufacturing systems research. Despite some concerns with message congestion, researchers have been proposing and studying negotiation schemes based on the contract net protocol (CNP). On the other hand, research in robotics has considered a variant of CNP based on publish-subscribe messaging designed for multi-robot coordination. A distinct feature of this variant involves distributing the bid evaluation and selection functions among robot agents. This paper discusses our adaptation of this design variant for multi-agent manufacturing systems and examines its performance implications. Using discrete-event simulation, we study how the adapted CNP design can help address the message congestion problem by cutting down on negotiation slack time. Our case study results show that it can enhance the resilience of the agent negotiation process to message congestion, thereby contributing to the overall performance of a multi-agent manufacturing system.     

Service organisations resilience through the application of the vanguard method of systems thinking: a case study approach

The construct of organisational resilience is embedded in a set of individual level attributes and organisational level processes; however, there seems to be scarcity in the current literature of resilient models of operation that can amalgamate these two interlinked levels. This paper is an attempt to empirically explore the relationship of applying the vanguard method of systems thinking in service organisations with enhancing organisational resilience. Two case studies were conducted in two service organisations in the UK. Data were collected via semi-structured interviews, observations, and archival documents, followed by the use of the nine-item Organisational Commitment Questionnaire. Cross-case analysis of the results shows that the employment of the vanguard method in service organisations operationalized two-dimensional determinants for improving organisational resilience; an organically structured organisation (i.e. organisational level), and highly affectively committed core employees (i.e. individual level).The value of this paper is the identification of two-level service organisations capabilities that can support organisational resilience and how these capabilities emerge as a result of employing the vanguard method.     

Large-scale systems resilience: A survey and unifying framework

A unifying framework in defining and measuring resilience has been an intense research topic. In this paper, resilience is measured as a function of intrinsic capacities of a system, the effectiveness of recovery, and the extrinsic random shock process. Some existing resilience measures are analyzed as special cases of the proposed unifying measure. Then, we develop a framework in which the key constituents in achieving resilience are identified. Resilience is represented by four key dimensions: reliability, robustness, recovery, and reconfigurability. Finally, some practical and specific strategies are proposed to enhance the resilience of critical infrastructure systems under the proposed framework.     

Spatial filter pinhole for high-energy pulsed lasers

Spatial filters are essential components for maintaining high beam quality in high-energy pulsed laser systems. The long-duration (21 ns) high-energy pulses envisioned for future inertial-confinement fusion drive systems, such as the U.S. National Ignition Facility (NIF), are likely to lead to increased plasma generation and closure effects within the pinholes in the spatial filters. The design goal for the pinhole spatial filter for the NIF design is to remove small-angle scatter in the beam to as little as a ?100-murad divergence. It is uncertain whether this design requirement can be met with a conventional pinhole design. We propose a new pinhole architecture that addresses these issues by incorporating features intended to reduce the rate of plasma generation. Initial experiments with this design have verified its performance improvement relative to a conventional pinhole design.     

Enhancing dependency pair method using strong computability in simply-typed term rewriting

We enhance the dependency pair method in order to prove termination using recursive structure analysis in simply-typed term rewriting systems, which is one of the computational models of functional programs. The primary advantage of our method is that one can exclude higher-order variables which are difficult to analyze theoretically, from recursive structure analysis. The key idea of our method is to analyze recursive structure from the viewpoint of strong computability. This property was introduced for proving termination in typed λ-calculus, and is a stronger condition than the property of termination. The difficulty in incorporating this concept into recursive structure analysis is that because it is defined inductively over type structure, it is not closed under the subterm relation. This breaks the correspondence between strong computability and recursive structure. In order to guarantee the correspondence, we propose plain function-passing as a restriction, which is satisfied by many non-artificial functional programs.     

Ordinal profile monitoring with random explanatory variables

Profiles characterise the functional relationship between the response variable and one or more explanatory variables and have been playing an important role in many applications. Profile monitoring mainly aims at checking the stability of this relationship. In many situations, we observe that the response variable is categorical with three or more attribute levels, and that there is natural order among the levels. Moreover, the explanatory variables are also random rather than fixed at some predefined values. To fully exploit the ordinal information, it is assumed that there is an unknown latent continuous distribution determining the levels of the ordinal response. Based on this, we propose a novel control chart for jointly monitoring the functional relationship, location shifts in the latent continuous distribution, and the random explanatory variables. Simulation results show that our proposed chart is efficient in detecting abnormalities and is robust to various latent distributions.     

Medium-range order dictates local hardness in bulk metallic glasses

Bulk metallic glasses (BMGs) are materials with outstanding strength and elastic properties that make them tantalizing for engineering applications, yet our poor understanding of how their amorphous atomic arrangements control their broader mechanical properties (hardness, wear, fracture, etc.) impedes our ability to apply materials science principles in their design. In this work, we uncover the hierarchical structure that exists in BMGs across the nano- to microscale by using nanobeam electron diffraction experiments. Our findings reveal that local hardness of microscale domains decreases with increasing size and volume fraction of atomic clusters with higher local medium range order (MRO). Furthermore, we propose a model of ductile phase softening that will enable the future design of BMGs by tuning the MRO size and distribution in the nanostructure.     

Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?

The purpose of this research is to develop a better understanding of smart systems and autonomous processes of the Industry 4.0 era. Does the implementation of Industry 4.0 processes and systems expose firms to higher levels of risk in the supply chain through capability loss or does Industry 4.0 spur capability enhancement and thereby increase supply chain resilience? Industry 4.0 is centred on the idea that certain tasks and decisions can be automated through smart systems and autonomous processes. However, is there a risk of losing critical capabilities and the ability to be flexible, agile and resilient to unexpected disruptions in the supply chain? In order to address these questions, this research presents results from semi-structured interviews across multiple industries to provide findings on firms’ uses of smart systems and capability development associated with these systems. Results from this exploratory study may be classified into two primary insights. First, although Industry 4.0 systems are new and, in many cases untested, firms are eager regarding the potential of smart systems to positively impact firm performance and to leverage Industry 4.0 processes for a competitive supply chain advantage. Second, companies did not claim any human capability loss associated with Industry 4.0. In fact, these smart systems may lead to increased supply chain resilience because of capability enhancement and new skill development.     

Reconfigurable supply chain: the X-network

Research on supply chain (SC) digitalization, resilience, sustainability and leagility has remarkably progressed, most of it focused on the individual contributions of these four major frameworks. However, a lack of integration spanning these individual frameworks can be observed. In this conceptual paper, we hypothesize that reconfigurability can be considered such an integral perspective that consolidates the research in SC adaptation to ever changing environments. We theorize a new notion – a Reconfigurable SC or the X-network – that exhibits some crucial design and control characteristics for complex value-adding systems in highly vulnerable environments. We support our argumentation and conceptual viewpoints by a literature analysis along with tertiary studies to review and structure contextual factors of designing the X-networks. We propose respective frameworks and discuss the implementation principles and technologies at the macro and micro levels. Two novel concepts – dynamic SC meta-structures and dynamic autonomous services – are introduced. Distinctively, we go beyond the existing knowledge to predict proactively the future directions in the reconfigurable SCs. Our results can be of value for decision-makers to decipher chances and barriers in contemporary SC transformations.     

Model selection and optimal sampling in high-throughput experimentation

The practical difficulties encountered in analyzing the kinetics of new reactions are considered from the viewpoint of the capabilities of state-of-the-art high-throughput systems. There are three problems. The first problem is that of model selection, i.e., choosing the correct reaction rate law. The second problem is how to obtain good estimates of the reaction parameters using only a small number of samples once a kinetic model is selected. The third problem is how to perform both functions using just one small set of measurements. To solve the first problem, we present an optimal sampling protocol to choose the correct kinetic model for a given reaction, based on T-optimal design. This protocol is then tested for the case of second-order and pseudo-first-order reactions using both experiments and computer simulations. To solve the second problem, we derive the information function for second-order reactions and use this function to find the optimal sampling points for estimating the kinetic constants. The third problem is further complicated by the fact that the optimal measurement times for determining the correct kinetic model differ from those needed to obtain good estimates of the kinetic constants. To solve this problem, we propose a Pareto optimal approach that can be tuned to give the set of best possible solutions for the two criteria. One important advantage of this approach is that it enables the integration of a priori knowledge into the workflow.     

Design resilience in the fuzzy front end (FFE) context: an empirical examination

This study provides a detailed understanding of the flexibilities that affect performance of innovation projects in the fuzzy front end (FFE) stage. We use the ambidextrous theory approach along with theories on flexibility to propose key drivers of design resilience in innovation projects. A set of six in-depth case studies across a variety of contextual settings is used to investigate important sources of flexibilities that contribute to design resilience. The effects of different design flexibility on the firms’ design resilience are examined. Specifically, an in-depth examination of ‘within case’ trends suggested key design flexibilities to be further examined in the ‘across case’ analyses. Our findings provide valuable insights about the enabling design flexibilities and contextual effects of design resilience in the FFE stage of innovation projects. Based on the findings from the case studies, four sources of design flexibility emerged that vary in terms of their influence on design resilience: (1) iterative learning, (2) modularity, (3) engineering change management and (4) design reuse. Patterns from the ‘across case’ analyses were then used to isolate specific types of design flexibilities that are important for design resilience and organisational resilience. We also provide categorisation of these drivers of design resilience in the context of passive flexibility and active flexibility practices. One of the major contributions of the study is that it provides a detailed categorisation of design resilience in relation to organisational resilience.     

Semiconductor quantum templates: bottom-up design of optical devices and photonic circuits using sub-nanoscale high monolayer features and quantum optics

We propose an alternative bottom-up technique for designing, fabricating and monolithically integrating optical components, including functional distributed feedback lasers, modulators, waveguides, etc in a single semiconductor wafer without any need for etching or post-processing epitaxial growth. The proposed technique is based on the formation of semiconductor quantum templates at the well/barrier interfaces of quantum well structures. Such templates are responsible for changing the thickness of a quantum well in designated regions by adding one extra monolayer of the well material in those regions during the growth process. We show that, using a control laser field, these templates or sub-nanoscale high monolayer features allow us to spatially control the formation of electromagnetically induced transparency, gain without inversion, and coherent enhancement/suppression of the refractive index along the plane of the quantum well. We demonstrate that this can lead to bottom-up design capabilities for functional optical devices and their monolithic integration using a single epitaxial growth process.     

Supporting design via the System Operational Dependency Analysis methodology

In this paper, we introduce the system operational dependency analysis methodology. Its purpose is to assess the effect of dependencies between components in a monolithic complex system, or between systems in a system-of-systems, and to support design decision making. We propose a parametric model of the behavior of the system. This approach results in a simple, intuitive model, whose parameters give a direct insight into the causes of observed, and possibly emergent, behavior. Using the proposed method, designers, and decision makers can quickly analyze and explore the behavior of complex systems and evaluate different architecture under various working conditions. Thus, the system operational dependency analysis method supports educated decision making both in the design and in the update process of systems architecture, without the need to execute extensive simulations. In particular, in the phase of concept generation and selection, the information given by the method can be used to identify promising architectures to be further tested and improved, while discarding architectures that do not show the required level of global features. Application of the proposed method to a small example is used to demonstrate both the validation of the parametric model, and the capabilities of the method for system analysis, design and architecture.