Survey of trace elements (Al, As, Cd, Cr, Co, Hg, Mn, Ni, Pb, Se, and Si) in retail samples of flavoured and bottled waters

Concentrations of eleven trace elements (Al, As, Cd, Cr, Co, Hg, Mn, Ni, Pb, Se, and Si) were measured in 39 (natural and flavoured) water samples. Determinations were performed using graphite furnace electrothermetry for almost all elements (Al, As, Cd, Cr, Co, Mn, Ni, Pb, and Si). For Se determination hydride generation was used, and cold vapour generation for Hg. These techniques were coupled to atomic absorption spectrophotometry. The trace element content of still or sparkling natural waters changed from brand to brand. Significant differences between natural still and natural sparkling waters (p<0.001) were only apparent for Mn. The Mann–Whitney U-test was used to search for significant differences between flavoured and natural waters. The concentration of each element was compared with the presence of flavours, preservatives, acidifying agents, fruit juice and/or sweeteners, according to the labelled composition. It was shown that flavoured waters generally increase the trace element content. The addition of preservatives and acidifying regulators had a significant influence on Mn, Co, As and Si contents (p<0.05). Fruit juice can also be correlated to the increase of Co and As. Sweeteners did not provide any significant difference in Mn, Co, Se and Si content.

Logística e estão da cadeia de abastecimento

Relatório apresentado ao Instituto Superior De Contabilidade e Administração Do Porto para obtenção do grau de Mestre em Logística Orientado por António Jorge S. T. Duarte

Lean applied to logistics: a case study

This project aims to study the implementation of Lean principles and tools in several levels of logistics, from internal logistics to interface with distribution center and suppliers, in an industrial plant. The main focus of all efforts is to create the conditions to approach the continuous flow scenario in the manufacturing processes. The subject of improvement actions is a company whose core activity is car seat production, more specifically the car seat cover production and assembly. This focuses the assembly process, which requires the usage of a considerable variety of components and therefore is an important obstacle to the implementation of continuous flow. The most salient issues are related with inefficient interaction between sections and late supply of components in assembly lines, forcing the operator to abandon his work station and leading to production interruption. As an operational methodology, actions from Lean philosophy and optimization were implemented according to project management principles.

Aplicação da metodologia Kaizen em gestão de armazém de peças

Mestrado em Engenharia Mecânica - Especialização em Gestão Industrial

Significance of Biogenic Amines in Cold-Smoked Fish and Their Relation to Microbiological Characteristics of Products Available in Portuguese Retail Markets

Studies on microbial characterization of cold-smoked salmon and salmon trout during cold storage were performed on samples available in the Portuguese market. Samples were also classified microbiologically according to guidelines for ready-to-eat (RTE) products. Further investigations on sample variability and microbial abilities to produce tyramine and histamine were also performed. The coefficient of variation for viable counts of different groups of microorganisms of samples collected at retail market point was high in the first 2 wk of storage, mainly in the Enterobacteriaceae group and aerobic plate count (APC), suggesting that microbiological characteristics of samples were different in numbers, even within the same batch from the same producer. This variation seemed to be decreased when storage and temperature were controlled under lab conditions. The numbers of Enterobacteriaceae were influenced by storage temperature, as indicated by low microbial numbers in samples from controlled refrigeration. Lactic acid bacteria (LAB) and Enterobacteriaceae were predominant in commercial products, a significant percentage of which were tyramine and less histamine producers. These results might be influenced by (1) the technological processes in the early stages of production, (2) contamination during the smoking process, and (3) conditions and temperature fluctuations during cold storage at retail market point of sale.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Reengenharia do processo de reclamações das lojas

Num contexto global de incerteza, as cadeias de abastecimento mais ágeis e os clientes com mais exigências manifestam uma constante preocupação com a melhoria contínua da eficiência das operações logísticas. O presente projeto foi desenvolvido na empresa Sonae Modelo Continente Hipermercados, S.A, uma das duas principais empresas do retalho da grande distribuição alimentar em Portugal. Sendo a logística um fator chave de sucesso, uma das atividades críticas de uma empresa, é identificada a oportunidade de melhoria operacional do processo de negócio, a partir das reclamações dos clientes internos. O tratamento destas reclamações, incidências, é de grande complexidade e responsabilidade para a área do Logistics Customer Service. O projeto desenvolvido, a ‘Reengenharia do processo de reclamações das Lojas’, surgiu da necessidade de criar um modelo e processo de negócio de melhoria contínua, que solucione falhas operacionais com implicação na Logística, Supply Chain e em outras áreas da empresa. A procura dessa melhoria é o objetivo deste trabalho. Pretende-se, com a proposta aqui apresentada, a interligação e automatização da cadeia abastecimento, para superar as ocorrências operacionais, elevar a qualidade do serviço, aumentar a capacidade do processo e incorporar uma monitorização das atividades de input (Lojas) e output (Entrepostos), para futura rastreabilidade das operações, através da integração da cadeia de abastecimento, para a satisfação do cliente interno. Para a elaboração do novo modelo de processo foi seguida a orientação da reengenharia de processos de negócio, nas suas linhas orientadoras: identificação do modelo de processo atual e das suas necessidades; definição dos objetivos norteadores do projeto a apresentar; redesenhar novo modelo de processo de negócio, de modo a dar resposta às necessidades detetadas nos clientes internos.

Sistema de apoio à decisão para o reaprovisionamento intercontinental

Este estudo foi desenvolvido em contexto empresarial e apresenta o levantamento de uma oportunidade de melhoria conjunta nos processos de gestão de stocks, compras e logística com o objetivo de otimizar a seleção e envio dos artigos com necessidade de reposição. O caso de estudo apresentado neste documento retrata o circuito logístico entre uma empresa sediada em Angola e outra em Portugal. A primeira dedica-se à venda por grosso e a retalho que é fornecida pela segunda, onde também está concentrada a gestão de aprovisionamento. Integrando uma sociedade menos desenvolvida como Angola, a delicadeza e complexidade dos problemas associam-se à incerteza, tornando um ambiente propício para a identificação e implantação de melhorias nos processos de decisão, colmatando a dependência de apoio em sistemas e serviços externos. Com uma logística de abastecimento intercontinental, a seleção e envio de mercadoria é uma preocupação dos gestores, uma vez que o tempo de fornecimento é longo e poderá afetar a performance das vendas caso seja uma decisão não sustentada. Com o foco no apoio à decisão, desenvolveu-se uma ferramenta que incorpora os detalhes da atividade empresarial que permite selecionar os artigos para reposição, maximizando o seu potencial valor de vendas.

Inovação no modelo de negócio: o caso do setor grossista alimentar em Portugal

Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Professor Doutor José de Freitas Santos

Internacionalização do vinho do Porto – estudo de caso Grupo Sogevinus

Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Professor Doutor José Freitas Santos

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

An integrated system to support electricity tariff contract definition

This paper presents an integrated system that helps both retail companies and electricity consumers on the definition of the best retail contracts and tariffs. This integrated system is composed by a Decision Support System (DSS) based on a Consumer Characterization Framework (CCF). The CCF is based on data mining techniques, applied to obtain useful knowledge about electricity consumers from large amounts of consumption data. This knowledge is acquired following an innovative and systematic approach able to identify different consumers’ classes, represented by a load profile, and its characterization using decision trees. The framework generates inputs to use in the knowledge base and in the database of the DSS. The rule sets derived from the decision trees are integrated in the knowledge base of the DSS. The load profiles together with the information about contracts and electricity prices form the database of the DSS. This DSS is able to perform the classification of different consumers, present its load profile and test different electricity tariffs and contracts. The final outputs of the DSS are a comparative economic analysis between different contracts and advice about the most economic contract to each consumer class. The presentation of the DSS is completed with an application example using a real data base of consumers from the Portuguese distribution company.

Scheduling in holonic manufacturing systems

This chapter presents some of the issues with holonic manufacturing systems. It starts by presenting the current manufacturing scenario and trends and then provides some background information on the holonic concept and its application to manufacturing. The current limitations and future trends of manufacturing suggest more autonomous and distributed organisations for manufacturing systems; holonic manufacturing systems are proposed as a way to achieve such autonomy and decentralisation. After a brief literature survey a specific research work is presented to handle scheduling in holonic manufacturing systems. This work is based on task and resource holons that cooperate with each other based on a variant of the contract net protocol that allow the propagation of constraints between operations in the execution plan. The chapter ends by presenting some challenges and future opportunities of research.