The drug logistics process: an innovation experience

Purpose - The purpose of this paper is to present the latest innovations in the drug distribution processes of hospital companies, which are currently dealing with high inventory and storage costs and fragmented organizational responsibilities. Design/methodology/approach - The literature review and the in-depth analysis of a case study support the understanding of the unit dose drug distribution system and the subsequent definition of the practical implications for hospital companies. Findings - Starting from the insights offered by the case study, the analysis shows that the unit dose system allows hospitals to improve the patient care quality and reduce costs. Research limitations/implications - The limitations of the research are those related to the theoretical and exploratory nature of the study, but from a practical point of view, the work provides important indications to the management of healthcare companies, which have to innovate their drug distribution systems. Originality/value - This paper analyzes a new and highly topical issue and provides several insights for the competitive development of a fundamental sector

Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution

Theoretical formulations of dynamic heterogeneous-agent economiestypically include a distribution as an aggregate state variable. This paperintroduces a method for computing equilibrium of these models by including a distribution directly as a state variable if it is finite-dimensional or a fine approximation of it if infinite-dimensional. The method accurately computes equilibrium in an extreme calibration of Huffman's (1987) overlapping-generations economy where quasi-aggregation, the accurate forecasting of prices using a small state space, fails to obtain. The method also accurately solves for equilibrium in a version of Krusell and Smith's (1998) economy wherein quasi-aggregation obtains but households face occasionally binding constraints. The method is demonstrated to be not only accurate but also feasible with equilibria for both economies being computed in under ten minutes in Matlab. Feasibility is achieved by using Smolyak's (1963) sparse-grid interpolation algorithm to limit the necessary number of gridpoints by many orders of magnitude relative to linear interpolation. Accuracy is achieved by using Smolyak's algorithm, which relies on smoothness, only for representing the distribution and not for other state variables such as individual asset holdings.Numerical Solutions, Heterogeneous Agents, Projection Methods

Models of Transportation and Land Use Change: A Guide to the Territory

Modern urban regions are highly complex entities. Despite the difficulty of modeling every relevant aspect of an urban region, researchers have produced a rich variety models dealing with inter-related processes of urban change. The most popular types of models have been those dealing with the relationship between transportation network growth and changes in land use and the location of economic activity, embodied in the concept of accessibility. This paper reviews some of the more common frameworks for modeling transportation and land use change, illustrating each with some examples of operational models that have been applied to real-world settings.Transport, land use, models, review network growth, induced demand, induced supply

Lost in Translation: Interpreting the Brazilian Electric Power Privatisation Failure.

Did Latin American privatisation polices fail because of flawed implementation of fundamentally sound policies or because privatisation policies were themselves seriously flawed?Using the Brazilian electric power reforms as a narrative tool, this paper examines the causal chain assumed by large-scale privatisation policies implemented as part of structural reformand adjustment programmes. The paper concludes that many privatisation policies and the economic stabilisation programmes within which they were embedded were not mutually reinforcingas policymakers had expected and that in their application, much of what privatisation theories claimed was lost in translation.Brazil;privatisation;infrastructure;electric power

AGILE Paradigm: The next generation collaborative MDO for the development of aeronautical systems

The research and innovation EU funded AGILE project has developed the next generation of aircraft Multidisciplinary Design and Optimization (MDO) processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. 19 industry, research and academia partners from Europe, Canada and Russia have developed solutions to cope with the challenges of collaborative design and optimization of complex aeronautical products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization, a novel approach, the so-called “AGILE Paradigm”, has been conceived. The AGILE Paradigm is defined as a “blueprint for MDO”, accelerating the deployment and the operations of collaborative “MDO systems” and enabling the development of complex products practiced by multi-site and cross-organizational design teams, having heterogeneous expertise. A set of technologies has been developed by the AGILE consortium to enable the implementation of the AGILE Paradigm principles, thus delivering not only an abstract formalization of the approach, but also an applicable framework. The collection of all the technologies constitutes the so-called “AGILE Framework”, which has been applied for the design and the optimization of multiple aircraft configurations. The ambition of the AGILE Paradigm was set to reduce the lead time of 40% with respect to the current state-of-the-art. This work reviews the evolution of the MDO systems, underlines the open challenges tackled by the AGILE project, and introduces the main architectural concepts behind the AGILE Paradigm. Thereafter, an overview of the application design cases is presented, focusing of the main challenges and achievements. The AGILE technologies enabled the consortium to formulate and to solve in 15 months 7 MDO applications in parallel for the development of 7 novel aircraft configurations, demonstrating time savings beyond the 40% goal

Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity

The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species’ metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques

Determining the efficacy of additive manufacturing for the aerospace spare parts supply chain

This thesis investigates how additive manufacturing (AM) based on-demand part production can supplement or replace the traditional production and inventory in typical aerospace’s spare parts supply chain systems. This study focuses on the operational characteristics of AM and its impacts on the overall logistics of plant-level operations. To capture the microscopic operational aspects of the AM production, a discrete-event simulation based approach was adopted, with key AM operation resources (e.g. AM system, operator) and attributes (e.g. AM manufacturing speed, individual part characteristics and demands) accounted for in the modeling process. In addition, a benchmark warehouse inventory model was also established separately based on classic theories, which was subsequently utilized to create a cost/benefit analysis for the AM based part supply strategies versus the traditional strategies. The results from virtual experiments with these models were analyzed in order to gain an understanding of the operational characteristics (e.g., production cost, system utilization, lead time) as a function of various production policies such as machine/operator configurations and part prioritization. Data analysis shows cost savings for AM as an alternative to warehousing under high penalty scenarios. Results also indicate higher cost savings with the addition of extra machines over extra operators to meet capacity. Finally, analysis shows that reprioritizing orders waiting in a queue has higher savings when assessing due date and penalty outcomes