Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

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.

Selection response of growth rate in rabbits for meat production

Genetic and environmental trends in 2 lines of rabbit (B and R) selected on individual weight gain (WG) from weaning (4 wk) to slaughter (11 wk) were estimated using mixed model methodology. Line B was derived from the California breed and line R was a synthetic of stock of different origin. The data were collected from a single herd and comprised 7 718 individuals in line B and 9 391 in line R, the lines having 12 and 9 generations of selection respectively. Realized responses in the 2 lines were 2.7% and 2.2% of the initial mean per year respectively and showed that selection on WG was effective but was less than expected. Selection on slaughter weight (SW) and effects of selection on other economic traits are discussed. It is concluded that selection on either WG or SW is a simple method for improving growth rate in rabbit sire line stocks.

Resolução do problema de sequenciamento de múltiplas linhas de montagem de modelos mistos em ambiente de produção enxuta

This work deals with the sequencing of Multi-Mixed-Model Assembly Lines in a lean manufacturing environment, where an operational structure where several kanbans support several mixed-model assembly lines, so that all assembly lines can receive parts or sub-assemblies from all suppliers. To optimize this system, the sequencing seeks to minimize the distance between the real consumption and the constant ideal consumption of parts or subassemblies, thereby reducing the scaling of kanbans and intermediate stocks. To solve the sequencing problems, the method Clustering Search was applied along with the metaheuristics Variable Neighborhood Search, Simulation Annealing and Iterative Local Search. Instances from the literature and generated instances were tested, thus allowing comparing the methods to each other and with other methods presented in the literature. The performance of the Clustering Search with Iterated Local Search stands out by the quality and robustness of their solutions, and mainly for its efficiency, whereas it converges to better results at a lower computational cost

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Job rotation in assembly lines employing disabled workers

In this paper we consider the programming of job rotation in the assembly line worker assignment and balancing problem. The motivation for this study comes from the designing of assembly lines in sheltered work centers for the disabled, where workers have different task execution times. In this context, the well-known training aspects associated with job rotation are particularly desired. We propose a metric along with a mixed integer linear model and a heuristic decomposition method to solve this new job rotation problem. Computational results show the efficacy of the proposed heuristics. (C) 2009 Elsevier B.V. All rights reserved.

One-sided tolerance interval in a two-way balanced nested model with mixed effects

In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.

An expression of mixed animal model equations to account for different means and variances in the base population

This paper presents a general expression to predict breeding values using animal models when the base population is selected, i.e. the means and variances of breeding values in the base generation differ among individuals. Rules for forming the mixed model equations are also presented. A numerical example illustrates the procedure.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

A transmission line model developed directly in phase domain

The phases of a transmission line are tightly coupled due to mutual impedances and admittances of the line. One way to accomplish the calculations of currents and voltages in multi-phase lines consists in representing them in modal domain, where its n coupled phases are represented by their n propagation modes. The separation line in their modes of propagation is through the use of a modal transformation matrix whose columns are eigenvectors associated with the parameters of the line. Usually, this matrix is achieved through numerical methods which do not allow the achievement of an analytical model for line developed directly in the phases domain. This work will show an analytical model for phase currents and voltages of the line and results it will be applied to a hypothetical two-phase. It will be shown results obtained with that will be compared to results obtained using a classical model. © 2012 IEEE.

A transmission line model developed directly in phase domain

The phases of a transmission line are tightly coupled due to mutual impedances and admittances of the line. One way to accomplish the calculations of currents and voltages in multi phase lines consists in representing them in modal domain, where its n coupled phases are represented by their n propagation modes. The separation line in their modes of propagation is through the use of a modal transformation matrix whose columns are eigenvectors associated with the parameters of the line. Usually, this matrix is achieved through numerical methods which do not allow the achievement of an analytical model for line developed directly in the phases domain. This work will show an analytical model for phase currents and voltages of the line and results it will be applied to a hypothetical two-phase. It will be shown results obtained with that will be compared to results obtained using a classical model © 2003-2012 IEEE.

Sequenciamento de linhas de montagem múltiplas em ambiente de produção enxuta utilizando simulação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fitting the frequency-dependent parameters in the Bergeron line model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic parameter estimates and principal component analysis on performance and carcass traits of a terminal pig sire line

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.

Antitumor Activity Of Irradiated Riboflavin On Human Renal Carcinoma Cell Line 786-o.

Riboflavin (vitamin B2) is a precursor for coenzymes involved in energy production, biosynthesis, detoxification, and electron scavenging. Previously, we demonstrated that irradiated riboflavin (IR) has potential antitumoral effects against human leukemia cells (HL60), human prostate cancer cells (PC3), and mouse melanoma cells (B16F10) through a common mechanism that leads to apoptosis. Hence, we here investigated the effect of IR on 786-O cells, a known model cell line for clear cell renal cell carcinoma (CCRCC), which is characterized by high-risk metastasis and chemotherapy resistance. IR also induced cell death in 786-O cells by apoptosis, which was not prevented by antioxidant agents. IR treatment was characterized by downregulation of Fas ligand (TNF superfamily, member 6)/Fas (TNF receptor superfamily member 6) (FasL/Fas) and tumor necrosis factor receptor superfamily, member 1a (TNFR1)/TNFRSF1A-associated via death domain (TRADD)/TNF receptor-associated factor 2 (TRAF) signaling pathways (the extrinsic apoptosis pathway), while the intrinsic apoptotic pathway was upregulated, as observed by an elevated Bcl-2 associated x protein/B-cell CLL/lymphoma 2 (Bax/Bcl-2) ratio, reduced cellular inhibitor of apoptosis 1 (c-IAP1) expression, and increased expression of apoptosis-inducing factor (AIF). The observed cell death was caspase-dependent as proven by caspase 3 activation and poly(ADP-ribose) polymerase-1 (PARP) cleavage. IR-induced cell death was also associated with downregulation of v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homologue (avian)/protein serine/threonine kinase B/extracellular signal-regulated protein kinase 1/2 (Src/AKT/ERK1/2) pathway and activation of p38 MAP kinase (p38) and Jun-amino-terminal kinase (JNK). Interestingly, IR treatment leads to inhibition of matrix metalloproteinase-2 (MMP-2) activity and reduced expression of renal cancer aggressiveness markers caveolin-1, low molecular weight phosphotyrosine protein phosphatase (LMWPTP), and kinase insert domain receptor (a type III receptor tyrosine kinase) (VEGFR-2). Together, these results show the potential of IR for treating cancer.