33 resultados para supply lead time


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We report on the temporally and spatially resolved detection of the precursory stages that lead to the formation of an unmagnetized, supercritical collisionless shock in a laser-driven laboratory experiment. The measured evolution of the electrostatic potential associated with the shock unveils the transition from a current free double layer into a symmetric shock structure, stabilized by ion reflection at the shock front. Supported by a matching particle-in-cell simulation and theoretical considerations, we suggest that this process is analogous to ion reflection at supercritical collisionless shocks in supernova remnants.

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Nonadherence to prescribed treatment is an important cause of difficult asthma. Rates of nonadherence amongst asthmatic patients have been shown to range between 30% and 70%. This is associated with poor health care outcomes and increased health care costs. There is no such thing as a "typical" nonadherent patient. The reasons driving nonadherence are multifactorial. Furthermore, adherence is a variable behavior and not a trait characteristic. Adherence rates can vary between the same individual across treatments for different conditions. There is no consistent link between socioeconomic status and nonadherence, and although some studies have shown that nonadherence is more common amongst females, this is not a universal finding. The commonly held perception that better adherence is driven by greater disease severity has been demonstrated to not be the case, in both pediatric and adult patients. Identification of nonadherence is the first step. If adherence is not checked, it is likely that poor adherence will be labeled as refractory disease. Failure to identify poor adherence may lead to inappropriate escalation of therapy, including the potential introduction of complex biological therapies. Surrogate measures, such as prescription counting, are not infallible. Nonadherence can be difficult to identify in clinical practice, and a systematic approach using a variety of tools is required. Nonadherence can be successfully addressed. Therefore, assessment of adherence is of paramount importance in difficult asthma management, in order to reduce exacerbations and steroid-related side effects as well as hospital and intensive care admissions, health care cost, and inappropriate treatment escalation. In this paper, we present an overview of the literature surrounding nonadherence in difficult asthma. We explore the facts and myths surrounding the factors driving nonadherence as well as how it can be identified and addressed.

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With many real world decisions being made in conjunction with other decision makers, or single agent decisions having an influence on other members of the decision maker's immediate entourage, there is strong interest in studying the relative weight assigned to different agents in such contexts. In the present paper, we focus on the case of one member of a two person household being asked to make choices affecting the travel time and salary of both members. We highlight the presence of significant heterogeneity across individuals not just in their underlying sensitivities, but also in the relative weight they assign to their partner, and show how this weight varies across attributes. This is in contrast to existing work which uses weights assigned to individual agents at the level of the overall utility rather than for individual attributes. We also show clear evidence of a risk of confounding between heterogeneity in marginal sensitivities and heterogeneity in the weights assigned to each member. We show how this can lead to misleading model results, and argue that this may also explain past results showing bargaining or weight parameters outside the usual [0,1] range in more traditional joint decision making contexts. In terms of substantive results, we find that male respondents place more weight on their partner's travel time, while female respondents place more weight on their partner's salary.

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The aim of this paper is to develop a new generation of extruder control system for recycled materials which has ability to automatically maintain constant a polymer melt viscosity of mixed recycled polymers during extrusion, regardless of variations in the Melt Flow Index (MFI) of recycled mixed grade high density polyethylene (HDPE) feedstock. The variations in MFI are due to differences in the source of the recycled material used. The work describes how melt viscosity for specific extruder/die system is calculated in real time using the rheological properties of the materials, the pressure drop through the extruder die and the actual throughput measurements using a gravimetric loss-in-weight hopper feeder. A closed-loop controller is also developed to automatically regulate screw speed and barrel temperature profile to achieve constant viscosity and enable consistent processing of variable grade recycled HDPE materials. Such a system will improve processability of mixed MFI polymers may also reduce the risk of polymer melt degradation, reduce producing large volumes of scrap/waste and lead to improvement in product quality. The experimental results of real time viscosity measurement and control using a 38 mm single screw extruder with different recycled HDPEs with widely different MFIs are reported in this work.

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A debate on the effect of environmental practices on performance has been taking place in the academic literature over the last two decades. In recent years this has involved researchers looking beyond the direct relationship between practices and performance to consider other potential contributing factors. This paper considers the extent to which environmental proactivity influences the practices that firms adopt and the associated performance outcomes. Data were collected from sample of UK food manufacturers and analysed using multiple regression analysis. Findings suggest that proactivity is an important antecedent to practices but these practices may not lead to improvements beyond environmental performance.

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Complex collaboration in rapidly changing business environments create challenges for management capability in Utility Horizontal Supply Chains (UHSCs) involving the deploying and evolving of performance measures. The aim of the study is twofold. First, there is a need to explore how management capability can be developed and used to deploy and evolve Performance Measurement (PM), both across a UHSC and within its constituent organisations, drawing upon a theoretical nexus of Dynamic Capability (DC) theory and complementary Goal Theory. Second, to make a contribution to knowledge by empirically building theory using these constructs to show the management motivations and behaviours within PM-based DCs. The methodology uses an interpretive theory building, multiple case based approach (n=3) as part of a USHC. The data collection methods include, interviews (n=54), focus groups (n=10), document analysis and participant observation (reflective learning logs) over a five-year period giving longitudinal data. The empirical findings lead to the development of a conceptual framework showing that management capabilities in driving PM deployment and evolution can be represented as multilevel renewal and incremental Dynamic Capabilities, which can be further understood in terms of motivation and behaviour by Goal-Theoretic constructs. In addition three interrelated cross cutting themes of management capabilities in consensus building, goal setting and resource change were identified. These management capabilities require carefully planned development and nurturing within the UHSC. 

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We investigate line formation processes in Type IIb supernovae (SNe) from 100 to 500 days post-explosion using spectral synthesis calculations. The modelling identifies the nuclear burning layers and physical mechanisms that produce the major emission lines, and the diagnostic potential of these. We compare the model calculations with data on the three best observed Type IIb SNe to-date - SN 1993J, SN 2008ax, and SN 2011dh. Oxygen nucleosynthesis depends sensitively on the main-sequence mass of the star and modelling of the [O I] lambda lambda 6300, 6364 lines constrains the progenitors of these three SNe to the M-ZAMS = 12-16 M-circle dot range (ejected oxygen masses 0.3-0.9 M-circle dot), with SN 2011dh towards the lower end and SN 1993J towards the upper end of the range. The high ejecta masses from M-ZAMS greater than or similar to 17 M-circle dot progenitors give rise to brighter nebular phase emission lines than observed. Nucleosynthesis analysis thus supports a scenario of low-to-moderate mass progenitors for Type IIb SNe, and by implication an origin in binary systems. We demonstrate how oxygen and magnesium recombination lines may be combined to diagnose the magnesium mass in the SN ejecta. For SN 2011dh, a magnesium mass of 0.02-0.14 M-circle dot is derived, which gives a Mg/O production ratio consistent with the solar value. Nitrogen left in the He envelope from CNO burning gives strong [N II] lambda lambda 6548, 6583 emission lines that dominate over Ha emission in our models. The hydrogen envelopes of Type IIb SNe are too small and dilute to produce any noticeable H alpha emission or absorption after similar to 150 days, and nebular phase emission seen around 6550 angstrom is in many cases likely caused by [N II] lambda lambda 6548, 6583. Finally, the influence of radiative transport on the emergent line profiles is investigated. Significant line blocking in the metal core remains for several hundred days, which affects the emergent spectrum. These radiative transfer effects lead to early-time blueshifts of the emission line peaks, which gradually disappear as the optical depths decrease with time. The modelled evolution of this effect matches the observed evolution in SN 2011dh.

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Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.

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In order to investigate the compatibility of candidate structural materials with liquid metals, two kinds of ferritic/martensitic steels were chosen to contact with lead–bismuth eutectic in sealed quartz–glass tubes. The corrosion exposures were for 500 and 3000 h. Results showed that the oxidation layer and carbide dissolution layer on the two steels grew with contact time under oxygen unsaturated condition. Short-term corrosion behavior of a newly developed steel showed better lead–bismuth eutectic corrosion resistance than T91 at 873 K.

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The desire for more robust supply chains has led to a growth in theoretical and practical interest in the application of both preventive and impact reductive disturbance management principles. This application should ultimately lead to less vulnerable and more competitive supply chains. Based on the extant literature we identify fresh food supply chain's contextual factors (products, processes, supply chain networks and supply chain business environment) and their corresponding characteristics, as well as the main disturbance management principles used. To analyse their influence on the selection and application of disturbance management principles in fresh food supply chains we conducted three case studies. In each case we collected data on the relevant contextual factors, disturbance management principles applied and company background. As an underlying methodology, we first conduct within-case analysis and then expand the analyses to a cross-case context. Based on the findings from these case studies, propositions are built concerning the nature of contextual factors and their characteristics, and their influence on the selection and application of disturbance management principles in fresh food supply chains. Our main findings are related to the identification of contextual characteristics of fresh food supply chains that are either critical vulnerability sources, critical enablers or conditionals and as such require, facilitate or condition selection and application of disturbance management principles.

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Purpose
– This paper aims to examine what drives the adoption of different social sustainability supply chain practices. Research has shown that certain factors drive the adoption of environmental sustainability practices but few focus on social supply chain practices, delineate which practices are adopted or what drives their adoption.

Design/methodology/approach
– The authors examine the facilitative role of sustainability culture to explain the adoption of social sustainability supply chain practices: basic practices, consisting of monitoring and management systems and advanced practices, which are new product and process development and strategic redefinition. The authors then explore the role played by a firm’s entrepreneurial orientation in shaping and reinforcing the adoption of social sustainability supply chain practices. A survey of 156 supply chain managers in multiple industries in Ireland was conducted to test the relationship between the variables.

Findings
– The findings show that sustainability culture is positively related to all the practices, and entrepreneurial orientation impacts and moderates social sustainability culture in advanced social sustainability supply chain adoption.

Research limitations/implications
– As with any survey, this is a single point in time with a single respondent. Implications for managers include finding the right culture in the organisation to implement social sustainability supply chain management practices that go beyond monitoring to behavioural changes in the supply chain with implications beyond the dyad of buyer and supplier to lower tier suppliers and the community surrounding the supply chain.

Practical implications
– The implications for managers include developing and fostering cultural attributes in the organisation to implement social sustainability supply chain management practices that go beyond monitoring suppliers to behavioural changes in the supply chain with implications beyond the dyad of buyer and supplier to lower tier suppliers and the community surrounding the supply chain.

Originality/value
– This is the first time, to the authors’ knowledge, that cultural and entrepreneurial variables have been tested for social sustainability supply chain practices, giving them new insights into how and why social sustainability supply chain practices are adopted.

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Reasoning that is deliberative and reflective often requires the inhibition of intuitive responses. The Cognitive Reflection Test (CRT) is designed to assess people’s ability to suppress incorrect heuristic responses in favour of deliberation. Correct responding on the CRT predicts performance on a range of tasks in which intuitive processes lead to incorrect responses, suggesting indirectly that CRT performance is related to cognitive control. Yet little is known about the cognitive processes underlying performance on the CRT. In the current research, we employed a novel mouse tracking mjavascript:void(0);ethodology to capture the time-course of reasoning on the CRT. Analysis of mouse cursor trajectories revealed that participants were initially drawn towards the incorrect (i.e., intuitive) option even when the correct (deliberative) option was ultimately chosen. Conversely, participants were not attracted to the correct option when they ultimately chose the incorrect intuitive one. We conclude that intuitive processes are activated automatically on the CRT and must be inhibited in order to respond correctly. When participants responded intuitively, there was no evidence that deliberative reasoning had become engaged.

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This study was conducted to explore the effect of different autoclave heating times (30, 60 and 90 min) on fatty acids supply and molecular stability in Brassica carinata seed. Multivariate spectral analyses and correlation analyses were also carried out in our study. The results showed that autoclaving treatments significantly decreased the total fatty acids content in a linear fashion in B. carinata seed as heating time increased. Reduced concentrations were also observed in C18:3n3, C20:1, C22:1n9, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), omega 3 (ω-3) and 9 (ω-9) fatty acids. Correspondingly, the heated seeds showed dramatic reductions in all the peak intensities within lipid-related spectral regions. Results from agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) indicated that the raw oilseed had completely different structural make-up from the autoclaved seeds in both CH3 and CH2 asymmetric and symmetric stretching region (ca. 2999–2800 cm−1) and lipid ester Cdouble bond; length as m-dashO carbonyl region (ca. 1787–1706 cm−1). However, the oilseeds heated for 30, 60 and 90 min were not grouped into separate classes or ellipses in all the lipid-related regions, indicating that there still exhibited similarities in lipid biopolymer conformations among autoclaved B. carinata seeds. Moreover, strong correlations between spectral information and fatty acid compositions observed in our study could imply that lipid-related spectral parameters might have a potential to predict some fatty acids content in oilseed samples, i.e. B. carinata. However, more data from large sample size and diverse range would be necessary and helpful to draw up a final conclusion.

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Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.

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Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.