Balancing and lot-sizing mixed-model lines in the footwear industry

This report describes the full research proposal for the project \Balancing and lot-sizing mixed-model lines in the footwear industry", to be developed as part of the master program in Engenharia Electrotécnica e de Computadores - Sistemas de Planeamento Industrial of the Instituto Superior de Engenharia do Porto. The Portuguese footwear industry is undergoing a period of great development and innovation. The numbers speak for themselves, Portugal footwear exported 71 million pairs of shoes to over 130 countries in 2012. It is a diverse sector, which covers different categories of women, men and children shoes, each of them with various models. New and technologically advanced mixed-model assembly lines are being projected and installed to replace traditional mass assembly lines. Obviously there is a need to manage them conveniently and to improve their operations. This work focuses on balancing and lot-sizing stitching mixed-model lines in a real world environment. For that purpose it will be fundamental to develop and evaluate adequate effective solution methods. Different objectives may be considered, which are relevant for the companies, such as minimizing the number of workstations, and minimizing the makespan, while taking into account a lot of practical restrictions. The solution approaches will be based on approximate methods, namely by resorting to metaheuristics. To show the impact of having different lots in production the initial maximum amount for each lot is changed and a Tabu Search based procedure is used to improve the solutions. The developed approaches will be evaluated and tested. A special attention will be given to the solution of real applied problems. Future work may include the study of other neighbourhood structures related to Tabu Search and the development of ways to speed up the evaluation of neighbours, as well as improving the balancing solution method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Strawberries from integrated pest management and organic farming: phenolic composition and antioxidant properties

Consumer awareness, pesticide and fertilizer contaminations and environmental concerns have resulted in significant demand for organically grown farm produce. Consumption of berries has become popular among health-conscious consumers due to the high levels of valuable antioxidants, such as anthocyanins and other phenolic compounds. The present study evaluated the influence that organic farming (OF) and integrated pest management (IPM) practise exert on the total phenolic content in 22 strawberry samples from four varieties. Postharvest performance of OF and IPM strawberries grown in the same area in the centre of Portugal and harvested at the same maturity stage were compared. Chemical profiles (phenolic compounds) were determined with the aid of HPLC-DAD/MS. Total phenolic content was higher for OF strawberry extracts. This study showed that the main differences in bioactive phytochemicals between organically and IPM grown strawberries concerned their anthocyanin levels. Organically grown strawberries were significantly higher in antioxidant activity than were the IPM strawberries, as measured by DPPH and FRAP assays.

Pesticide residues in Portuguese strawberries grown in 2009–2010 using integrated pest management and organic farming

Pesticides are among the most widely used chemicals in the world. Because of the widespread use of agricultural chemicals in food production, people are exposed to low levels of pesticide residues through their diets. Scientists do not yet have a total understanding of the health effects of these pesticide residues. This work aims to determine differences in terms of pesticide residue content in Portuguese strawberries grown using different agriculture practices. The Quick, Easy, Cheap, Effective, Rugged, and Safe sample preparation method was conducted and shown to have good performance for multiclass pesticides extraction in strawberries. The screening of 25 pesticides residue was performed by gas chromatography–tandem mass spectrometry. In quantitative validation, acceptable performances were achieved with recoveries of 70–120 and <12 % residual standard deviation for 25 pesticides. Good linearity was obtained for all the target compounds, with highly satisfactory repeatability. The limits of detection were in the range of 0.1–28 μg/kg. The method was applied to analyze strawberry samples from organic and integrated pest management (IPM) practices harvested in 2009–2010. The results showed the presence of fludioxonil, bifenthrin, mepanipyrim, tolylfluanid, cyprodinil, tetraconazole, and malathion when using IPM below the maximum residue levels.

Organochlorine pesticide residues in strawberries from integrated pest management and organic farming

A rapid, specific, and sensitive method based on theQuick Easy Cheap Effective Rugged and Safe (QuEChERS) method and a cleanup using dispersive solid-phase extraction with MgSO4, PSA, and C18 sorbents has been developed for the routine analysis of 14 pesticides in strawberries. The analyses were performed by three different analytical methodologies: gas chromatography (GC) with electron capture detection (ECD), mass spectrometry (MS), and tandem mass spectrometry (MS/MS). The recoveries for all the pesticides studied were from 46 to 128%, with relative standard deviation of <15% in the concentration range of 0.005-0.250 mg/kg. The limit of detection (LOD) for all compoundsmetmaximumresidue limits (MRL) accepted in Portugal for organochlorine pesticides (OCP). A survey study of strawberries produced in Portugal in the years 2009-2010 obtained from organic farming (OF) and integrated pest management (IPM) was developed. Lindane and β-endosulfan were detected above the MRL in OF and IPM. Other OCP (aldrin, o,p0-DDT and their metabolites, and methoxychlor) were found below the MRL. The OCP residues detected decreased from 2009 to 2010. The QuEChERS method was successfully applied to the analysis of strawberry samples.

Application of integer and fractional models in electrochemical systems

This paper describes the use of integer and fractional electrical elements, for modelling two electrochemical systems. A first type of system consists of botanical elements and a second type is implemented by electrolyte processes with fractal electrodes. Experimental results are analyzed in the frequency domain, and the pros and cons of adopting fractional-order electrical components for modelling these systems are compared.

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.

How realistic is the mixed-criticality real-time system model?

23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France. Best Paper Award Nominee

MASDSheGATS – Scheduling System for Dynamic Manufacturing Environments

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.

Basic dyestuffs removal from textile effluents using feathers: equilibrium, kinetic and column studies

This research work has been focused in the study of gallinaceous feathers, a waste that may be valorised as sorbent, to remove the Dark Blue Astrazon 2RN (DBA) from Dystar. This study was focused on the following aspects: optimization of experimental conditions through factorial design methodology, kinetic studies into a continuous stirred tank adsorber (at pH 7 and 20ºC), equilibrium isotherms (at pH 5, 7 and 9 at 20 and 45ºC) and column studies (at 20ºC, at pH 5, 7 and 9). In order to evaluate the influence of the presence of other components in the sorption of the dyestuff, all experiments were performed both for the dyestuff in aqueous solution and in real textile effluent. The pseudo-first and pseudo-second order kinetic models were fitted to the experimental data, being the latter the best fit for the aqueous solution of dyestuff. For the real effluent both models fit the experimental results and there is no statistical difference between them. The Central Composite Design (CCD) was used to evaluate the effects of temperature (15 - 45ºC) and pH (5 - 9) over the sorption in aqueous solution. The influence of pH was more significant than temperature. The optimal conditions selected were 45ºC and pH 9. Both Langmuir and Freundlich models could fit the equilibrium data. In the concentration range studied, the highest sorbent capacity was obtained for the optimal conditions in aqueous solution, which corresponds to a maximum capacity of 47± 4 mg g-1. The Yoon-Nelson, Thomas and Yan’s models fitted well the column experimental data. The highest breakthrough time for 50% removal, 170 min, was obtained at pH 9 in aqueous solution. The presence of the dyeing agents in the real wastewater decreased the sorption of the dyestuff mostly for pH 9, which is the optimal pH. The effect of pH is less pronounced in the real effluent than in aqueous solution. This work shows that feathers can be used as sorbent in the treatment of textile wastewaters containing DBA.

O Controlo interno e a gestão de risco nas empresas da área metropolitana do Porto

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação da Doutora Alcina Augusta de Sena Portugal Dias

Copper, nickel and zinc removal by peanut hulls: batch and column studies in mono, tri-component systems and with real effluent

The main goal of this research study was the removal of Cu(II), Ni(II) and Zn(II) from aqueous solutions using peanut hulls. This work was mainly focused on the following aspects: chemical characterization of the biosorbent, kinetic studies, study of the pH influence in mono-component systems, equilibrium isotherms and column studies, both in mono and tri-component systems, and with a real industrial effluent from the electroplating industry. The chemical characterization of peanut hulls showed a high cellulose (44.8%) and lignin (36.1%) content, which favours biosorption of metal cations. The kinetic studies performed indicate that most of the sorption occurs in the first 30 min for all systems. In general, a pseudo-second order kinetics was followed, both in mono and tri-component systems. The equilibrium isotherms were better described by Freundlich model in all systems. Peanut hulls showed higher affinity for copper than for nickel and zinc when they are both present. The pH value between 5 and 6 was the most favourable for all systems. The sorbent capacity in column was 0.028 and 0.025 mmol g-1 for copper, respectively in mono and tri-component systems. A decrease of capacity for copper (50%) was observed when dealing with the real effluent. The Yoon-Nelson, Thomas and Yan’s models were fitted to the experimental data, being the latter the best fit.

Adsorption behavior of α-cypermethrin on cork and activated carbon

Studies were undertaken to determine the adsorption behavior of α-cypermethrin [R)-α-cyano-3-phenoxybenzyl(1S)-cis- 3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropanecarboxylate, and (S)-α-cyano-3-phenoxybenzyl (1R)-cis-3-(2,2-dichlorovinyl)-2,2- dimethylcyclopropanecarboxylate] in solutions on granules of cork and activated carbon (GAC). The adsorption studies were carried out using a batch equilibrium technique. A gas chromatograph with an electron capture detector (GC-ECD) was used to analyze α-cypermethrin after solid phase extraction with C18 disks. Physical properties including real density, pore volume, surface area and pore diameter of cork were evaluated by mercury porosimetry. Characterization of cork particles showed variations thereby indicating the highly heterogeneous structure of the material. The average surface area of cork particles was lower than that of GAC. Kinetics adsorption studies allowed the determination of the equilibrium time—24 hours for both cork (1–2 mm and 3–4 mm) and GAC. For the studied α-cypermethrin concentration range, GAC revealed to be a better sorbent. However, adsorption parameters for equilibrium concentrations, obtained through the Langmuir and Freundlich models, showed that granulated cork 1–2 mm have the maximum amount of adsorbed α-cypermethrin (qm) (303 μg/g); followed by GAC (186 μg/g) and cork 3-4 mm (136 μg/g). The standard deviation (SD) values, demonstrate that Freundlich model better describes the α-cypermethrin adsorption phenomena on GAC, while α-cypermethrin adsorption on cork (1-2 mm and 3-4 mm) is better described by the Langmuir. In view of the adsorption results obtained in this study it appears that granulated cork may be a better and a cheaper alternative to GAC for removing α-cypermethrin from water.

A lightweight indoor localization model based on motley-keenan and COST

This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.