Total Setup Research Articles

Analysis of prostate bed motion using an endorectal balloon and cone beam computed tomography during postprostatectomy radiotherapy.

BackgroundThe authors conducted this prospective study to analyze the amount of interfractional prostate bed motion (PBM) and quantify its components with the use of an endorectal balloon (ERB).MethodsA total of 1,348 cone beam computed tomography images from 46 patients who underwent postprostatectomy radiotherapy were analyzed. For the pilot image, electronic portal imaging, guided by skin marks was performed to ensure proper positioning and inflation of the ERB. Then, for bone matching, manual or automatic registration of the planning and each cone beam computed tomography was performed, based on the bony anatomy of the pelvis. Shifts (bony misalignment [BM]) in three directions were recorded at each treatment session. For prostate bed matching, manual matching was conducted based on the anterior rectal wall and the shift (PBM) was recorded. Total setup error was defined as the shift from the skin mark to the prostate bed matching, based on anterior rectal wall stretched by the ERB. PBM was defined as the difference between the total setup error and BM.ResultsSystematic errors for the total setup error were 1.0, 1.3, and 1.0 mm in the right–left, anterior–posterior, and superior–inferior directions, with random errors of 1.9, 2.4, and 1.9 mm, respectively. Systematic errors were 1.6, 1.6, and 0.3 mm for BM and 0.8, 1.1, and 0.9 mm for PBM, with random errors of 2.4, 2.5, and 1.1 mm for BM and 1.8, 2.2, and 1.9 mm for PBM.ConclusionThe BM was the main component of the total setup error, suggesting that interfractional PBM was well controlled by the ERB device. Planning target volume margins of <5 mm were needed to include 95% of the interfractional variations when using an ERB.

Metal based nanoparticles as cancer antigen delivery vehicles for macrophage based antitumor vaccine

In the present study, we would like to evaluate the efficacy of modified metal oxide nanoparticles (NPs) as cancer antigen delivery vehicles for macrophage (MФs) based antitumor vaccine. The cobalt oxide nanoparticles (CoO NPs) were promising tools for delivery of antigens to antigen presenting cells and have induced an antitumor immune response. Synthesized CoO NPs were modified by N-phosphonomethyliminodiacetic acid (PMIDA), facilitated the conjugation of lysate antigen, i.e. cancer antigen derived from lysis of cancer cells. The cancer cell lysate antigen conjugated PMIDA-CoO NPs (Ag-PMIDA-CoO NPs) successfully activated macrophage (MФ) evident by the increasing the serum IFN-γ and TNF-α level. Immunization of mice with the Ag-PMIDA-CoO NPs constructed an efficient immunological adjuvant induced anticancer IgG responses, and increased the antibody dependent cellular cytotoxicity (ADCC) response than only lysate antigen treated group to combat the cancer cell. The nanocomplexes enhanced the anticancer CD4+T cell response in mice. The result showed that Ag-PMIDA-CoO NPs can stimulate the immune responses over only lysate antigens, which are the most important findings in this study. These NP-mediated Ag deliveries may significantly improve the anticancer immune response by activating MФs and may act as adjuvant and will balance the pro-inflammatory and anti-inflammatory immunoresponse. The crosstalk between the activated MФ with other immune competent cells will be monitored by measuring the cytokines which illustrate the total immunological network setups.

A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

Different from most researches focused on the single objective hybrid flowshop scheduling (HFS) problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS) is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

Restructuring of a plant production layout by using different array-based clustering techniques

This paper deals with restructuring of plant production layout by using two different clustering technique algorithms, namely rank order clustering (ROC) and genetic algorithm (GA) for manufacturing cell formation, with a real-life example to identify the effectiveness of the two clustering techniques. The objective is to cluster the machines and parts in such a manner, so that the advantages of cellular manufacturing systems/group technology are attained in terms of optimisation of setup time, reduction of material handling and reduction of total manufacturing lead time. A comparative study is done between the conventional layout and restructured layouts. The results obtained show that with ROC the total setup time for all 13 parts is reduced by 56%, total distance travelled during material handling is reduced by 56% and total lead time for all 13 parts is reduced by 20% as compared to the conventional layout, while with GA the total setup time for all 13 parts is reduced by 67%, the total distance travelled during material handling is reduced by 62% and total lead time for all 13 parts is reduced by 25% as compared to the conventional layout.

Facing energy-aware scheduling: a multi-objective extension of a scheduling support system for improving energy efficiency in a moulding industry

Nowadays most industries do not integrate product, process and energy data. Costs due to energy consumption are often considered externalities and energy efficiency is not deemed a relevant performance criterion. In energy-intensive processes, as injection moulding, the specific energy consumption, embedded inside the same products, depends on the machine–product combinations. Multi-objective scheduling, including the energy data acquired from shop floor and allocation criteria, is a valuable approach to improve energy efficiency. This paper presents the extension of a commercial detailed scheduling support system developed within a regional Italian project aiming at providing tools to manufacturing industry for improving energy efficiency. The project designed a monitoring system developed by instrumenting injection moulding presses to acquire the energy consumption for each product–machine combination. The commercial scheduling system was extended by implementing a multi-objective metaheuristic scheduling approach. The experimental assessment of the proposed approach involved a major producer of plastic dispensers. The extended algorithm simultaneously optimizes the total weighted tardiness, the total setup and the energy consumption costs. The obtained results, produced for a real test case and a set of random generated instances, show the effectiveness of the proposed approach.

Efficacy of insect-proof nets used in Tunisian tomato greenhouses against Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) and potential impact on plant growth and fruit quality

Insect-proof screens constitute efficient physical means of protecting horticultural crops against insect pests and their use has become widespread. However, they may have a negative impact on plant growth and fruit quality by modifying climatic parameters of greenhouses. In case of tomato crops, they are used mainly against white flies and the tomato leaf miner &lt;em&gt;Tuta absoluta&lt;/em&gt; (Meyrick). In Tunisia, tomato plastic tunnels are often netted following two modalities: i) complete netting of the greenhouse under the plastic screen (total netting); or ii) netting only doors and lateral aeration windows (partial netting). Weekly monitoring of &lt;em&gt;T. absoluta&lt;/em&gt; in two tomato greenhouses with different netting setups using pheromone traps and sampling of leaves and fruits showed no differences in the levels of infestation by the pest with a maximum average values of 6.66 eggs/leaf, 4.16 larvae/leaf and 4.16 mines/leaf. The maximum infestation rate of leaves was 86.66% and that of fruits was 10.83%. No effects of the netting setup used on plant growth parameters were detected. However, the study of fruit quality parameters revealed significant decrease in sugar contents in tomato fruits when using total netting setup (4.26°Brix &lt;em&gt;versus&lt;/em&gt; 3.68°Brix). Recommendations regarding the combined use of pheromones traps and insect-proof nets are given and possibilities to enhance the efficiency of nets as physical barrier against &lt;em&gt;T. absoluta&lt;/em&gt; are explored.

Feasibility recovery for the Unit-capacity Constrained Permutation Problem

The Unit-capacity Constrained Permutation Problem with Feasibility Recovery (UCPPFR) is to find a sequence of moves for pieces over a set of locations. From a given location, a piece can be moved to a unit capacity location, i.e. the latter location must be free of its original piece. Each piece has a specific type, and in the end every location must contain a piece of a required type. A piece must be handled using a specific tool, thus incurring a setup cost whenever a tool changeover is required. It could be necessary to use some Steiner locations to find a solution, thus incurring a Steiner cost. The aim of the UCPPFR is to find a sequence of moves with a minimum total setup and Steiner cost. We give a necessary and sufficient condition to check whether an instance admits a solution with no Steiner location. We show that the UCPPFR reduces to finding simultaneously a vertex-disjoint path cover and a shortest common supersequence. Finally, using a compact encoding for solutions and integer linear programming tools, we solve real instances coming from the nuclear power plant fuel renewal problem.

A novel fuzzy stochastic multi-objective linear programming for multi-level capacitated lot-sizing problem: a real case study of a furniture company

This paper develops a fuzzy stochastic multi-objective linear programming model for a multi-level, capacitated lot-sizing problem (ML-CLSP) in a mixed assembly shop. The proposed model aims to minimize the total cost consisting of total variable production cost, inventory cost, backorder cost, and setup cost while maximizing the resource utilization rate simultaneously. To cope with inherent mixed fuzzy stochastic uncertainty associated with input data, e.g., the demand and process-related parameters, they are treated as fuzzy stochastic parameters. We conducted a numerical example from literature to illustrate the efficiency of the proposed method against other ones. To validate the expediency of the proposed ML-CLSP and solution method, a real case study was executed in a furniture company. The results demonstrate the usefulness of the proposed model and its solution approach.

Planejamento da produção na indústria de embalagens de polpa moldada

Resumo Este trabalho aborda o problema de planejamento e programação da produção na indústria de embalagens de polpa moldada, particularmente o sistema de produção de uma fábrica de embalagens para acondicionamento de ovos e frutas. O processo de produção envolve a utilização de padrões de moldagem, através dos quais são produzidos os diferentes produtos demandados. Desta forma, as decisões no planejamento da produção envolvem a escolha dos padrões de moldagem a serem utilizados, o tempo de produção de cada um deles em cada linha de produção, e a forma como devem ser sequenciados. Para representar o problema, foi proposto um modelo matemático baseado no Problema de Dimensionamento e Sequenciamento de Lotes Geral (GLSP), com tempos e custos de preparação dependentes da sequência. Os resultados do modelo sugerem planos de produção significativamente melhores que os planos de produção da fábrica em estudo, sendo que, em todos os experimentos realizados com dados reais, a demanda é atendida com menor consumo de capacidade, menor tempo total dedicado às operações de setup e melhor controle nos níveis de estoque, além de uma redução de aproximadamente 36% dos custos totais envolvidos.

Effect of surface plasmons at the Al/alumina interface on the formation of nanopores in Al anodization

We investigated the formation mechanism of nanoporous alumina in the electrochemical reaction of aluminium with oxalic acid solution in terms of the pinning effect of Fermi level at the metal–oxide interface. On the Al metal surface, the image potential state pins the standing mode of collectively excited surface electrons and the evanescent wave forms the plasmon mode, which can be reflected in oxide barrier formation. A nanoporous alumina thin film with an amorphous phase oxide layer on the Al surface can enhance light absorption at a shorter wavelength than 382 nm and provide strong Fabry–Perot oscillation in photoreflectance. The cathodoluminescence spectra show the surface plasmon mode as a consequence of the self-ordered oxide nanopores. The Kretschmann configuration of an attenuated total reflection set-up for prism/oxalic solution/Al interface, which also provides a prism-coupled surface plasmon and forms oxide nanopores on the Al surface via a laser-enhanced anodization process.

Exact and heuristic algorithms for the design of hub networks with multiple lines

In this paper we study a hub location problem in which the hubs to be located must form a set of interconnecting lines. The objective is to minimize the total weighted travel time between all pairs of nodes while taking into account a budget constraint on the total set-up cost of the hub network. A mathematical programming formulation, a Benders-branch-and-cut algorithm and several heuristic algorithms, based on variable neighborhood descent, greedy randomized adaptive search, and adaptive large neighborhood search, are presented and compared to solve the problem. Numerical results on two sets of benchmark instances with up to 70 nodes and three lines confirm the efficiency of the proposed solution algorithms.

Performance analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times: Simulation approach

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under different levels of shop utilization and setup time. The important aspects of the results of the simulation investigation are also discussed in detail.

Performance analysis of higher mode spoof surface plasmon polariton for terahertz sensing

We investigated the spoof surface plasmon polaritons (SSPPs) on 1D grooved metal surface for terahertz sensing of refractive index of the filling analyte through a prism-coupling attenuated total reflection setup. From the dispersion relation analysis and the finite element method-based simulation, we revealed that the dispersion curve of SSPP got suppressed as the filling refractive index increased, which cause the coupling resonance frequency redshifting in the reflection spectrum. The simulated results for testing various refractive indexes demonstrated that the incident angle of terahertz radiation has a great effect on the performance of sensing. Smaller incident angle will result in a higher sensitive sensing with a narrower detection range. In the meanwhile, the higher order mode SSPP-based sensing has a higher sensitivity with a narrower detection range. The maximum sensitivity is 2.57 THz/RIU for the second-order mode sensing at 45° internal incident angle. The proposed SSPP-based method has great potential for high sensitive terahertz sensing.

Differential evolution to solve the lot size problem in stochastic supply chain management systems

An advanced resource planning model is presented to support optimal lot size decisions for overall performance improvement of real-life supply chain management systems in terms of either total delivery time or total setup costs. Based on a queueing network, a model is developed for a mix of products, which follow a sequence of operations taking place at multiple interdependent supply chain members. At the same time, various sources of uncertainty, both in demand and process characteristics, are taken into account. In addition, the model includes the impact of parallel servers for multiple resources with period dependent time schedules. The corrupting influence of variabilities from rework and breakdown is also explicitly modeled. This integer non-linear problem is solved by standard differential evolution algorithms. They are able to find each product’s lot size that minimizes its total supply chain lead time. We show that this solution approach outperforms the steepest descent method, an approach commonly used in the search for optimal lot sizes. For problems of realistic size, we propose appropriate control parameters for an efficient differential evolutionary search process. Based on these results, we add a major conclusion on the debate concerning the convexity between lot size and lead time in a complex supply chain environment.

Stochastic Dynamic Job Shop Scheduling with Sequence-Dependent Setup Times: Simulation Experimentation

Stochastic dynamic job shop (SDJS) scheduling problems with sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of five dispatching rules (DRLs) in such shop from makespan, mean flow time, mean tardiness, number of tardy jobs, total setups, and mean setup time performance measures viewpoint. A discrete event simulation model of a SDJS manufacturing system is developed for investigation purpose. Five DRLs, that is, first come first serve (FCFS), shortest processing time (SPT), shortest setup time (SIMSET), earliest due date (EDD) and shortest sum of setup times and processing time (SSPT) are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 and setup time less than processing time. Results indicate that SIMSET rule provides best performance for mean flow time and number of tardy jobs performance measures. The SPT rule provides best performance for mean tardiness measure. The EDD rule is best-performing DRL for makespan, total setups and mean setup time measures.

Evaluation of analytical errors in a clinical chemistry laboratory: a 3 year experience.

Background:Proficient laboratory service is the cornerstone of modern healthcare systems and has an impact on over 70% of medical decisions on admission, discharge, and medications. In recent years, there is an increasing awareness of the importance of errors in laboratory practice and their possible negative impact on patient outcomes.Aim:We retrospectively analyzed data spanning a period of 3 years on analytical errors observed in our laboratory. The data covered errors over the whole testing cycle including pre-, intra-, and post-analytical phases and discussed strategies pertinent to our settings to minimize their occurrence.Materials and Methods:We described the occurrence of pre-analytical, analytical and post-analytical errors observed at the Komfo Anokye Teaching Hospital clinical biochemistry laboratory during a 3-year period from January, 2010 to December, 2012. Data were analyzed with Graph Pad Prism 5(GraphPad Software Inc. CA USA).Results:A total of 589,510 tests was performed on 188,503 outpatients and hospitalized patients. The overall error rate for the 3 years was 4.7% (27,520/58,950). Pre-analytical, analytical and post-analytical errors contributed 3.7% (2210/58,950), 0.1% (108/58,950), and 0.9% (512/58,950), respectively. The number of tests reduced significantly over the 3-year period, but this did not correspond with a reduction in the overall error rate (P = 0.90) along with the years.Conclusion:Analytical errors are embedded within our total process setup especially pre-analytical and post-analytical phases. Strategic measures including quality assessment programs for staff involved in pre-analytical processes should be intensified.

MAC-layer concurrent beamforming protocol for indoor millimeter-wave networks

In this paper, we study concurrent beamforming issue for achieving high capacity in indoor millimeter-wave (mmWave) networks. The general concurrent beamforming issue is first formulated as an optimization problem to maximize the sum rates of concurrent transmissions, considering the mutual interference. To reduce the complexity of beamforming and the total setup time, concurrent beamforming is decomposed into multiple single-link beamforming, and an iterative searching algorithm is proposed to quickly achieve the suboptimal transmission/reception beam sets. A codebook-based beamforming protocol at medium access control (MAC) layer is then introduced in a distributive manner to determine the beam sets. Both analytical and simulation results demonstrate that the proposed protocol can drastically reduce total setup time, increase system throughput, and improve energy efficiency.

English

The present work is done in graphical based software called LabVIEW to develop and model a distillation column and study a basic crude oil plant in which different products are obtained and controlling of the process is done. By this virtual instrumentation software saves the cost, time and energy that are used in the traditional instrumentation where the total setup is to be done. The method used here for the designing of the number of trays and feed trays in the distillation column is the MC CABE THIELE method in which the mole fraction of liquid and vapour are taken into consideration and the number of trays and feed trays are calculated and the basic vapour - liquid equilibrium differential equations are used for the construction of trays, condenser, boiler vapour, feed tray in the process. This work shows the effective use of virtual instrumentation in the process monitoring and control. A split range type of setup is present in the reflux drum to control the product. In this project we present and crude oil plant setup in which the different products are received at different trays and temperature and controlling is done.

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.

An Image-Guided Study of Setup Reproducibility of Postmastectomy Breast Cancer Patients Treated With Inverse-Planned Intensity Modulated Radiation Therapy

To calculate planning target volume (PTV) margins for chest wall and regional nodal targets using daily orthogonal kilovolt (kV) imaging and to study residual setup error after kV alignment using volumetric cone-beam computed tomography (CBCT). Twenty-one postmastectomy patients were treated with intensity modulated radiation therapy with 7-mm PTV margins. Population-based PTV margins were calculated from translational shifts after daily kV positioning and/or weekly CBCT data for each of 8 patients, whose surgical clips were used as surrogates for target volumes. Errors from kV and CBCT data were mathematically combined to generate PTV margins for 3 simulated alignment workflows: (1) skin marks alone; (2) weekly kV imaging; and (3) daily kV imaging. The kV data from 613 treatment fractions indicated that a 7-mm uniform margin would account for 95% of daily shifts if patients were positioned using only skin marks. Total setup errors incorporating both kV and CBCT data were larger than those from kV alone, yielding PTV expansions of 7 mm anterior-posterior, 9 mm left-right, and 9 mm superior-inferior. Required PTV margins after weekly kV imaging were similar in magnitude as alignment to skin marks, but rotational adjustments of patients were required in 32% ± 17% of treatments. These rotations would have remained uncorrected without the use of daily kV imaging. Despite the use of daily kV imaging, CBCT data taken at the treatment position indicate that an anisotropic PTV margin of 6 mm anterior-posterior, 4 mm left-right, and 8 mm superior-inferior must be retained to account for residual errors. Cone-beam CT provides additional information on 3-dimensional reproducibility of treatment setup for chest wall targets. Three-dimensional data indicate that a uniform 7-mm PTV margin is insufficient in the absence of daily IGRT. Interfraction movement is greater than suggested by 2-dimensional imaging, thus a margin of at least 4 to 8 mm must be retained despite the use of daily IGRT.