Lean learning academy: an innovative framework for lean manufacturing training

Worldwide competitiveness poses enormous challenges on managers, demanding a continuous quest to increase rationality in the use of resources. As a management philosophy, Lean Manufacturing focuses on the elimination of activities that do not create any type of value and therefore are considered waste. For companies to successfully implement the Lean Manufacturing philosophy it is crucial that the human resources of the organization have the necessary training, for which proper tools are required. At the same time, higher education institutions need innovative tools to increase the attractiveness of engineering curricula and develop a higher level of knowledge among students, improving their employability. This paper describes how Lean Learning Academy, an international collaboration project between five EU universities and five companies, from SME to Multinational/Global companies, developed and applied an innovative training programme for Engineers on Lean Manufacturing, a successful alternative to the traditional teaching methods in engineering courses.

Digital serious games and simulation games - comparison of two approaches to lean training

In an increasingly competitive and globalized world, companies need effective training methodologies and tools for their employees. However, selecting the most suitable ones is not an easy task. It depends on the requirements of the target group (namely time restrictions), on the specificities of the contents, etc. This is typically the case for training in Lean, the waste elimination manufacturing philosophy. This paper presents and compares two different approaches to lean training methodologies and tools: a simulation game based on a single realistic manufacturing platform, involving production and assembly operations that allows learning by playing; and a digital game that helps understand lean tools. This paper shows that both tools have advantages in terms of trainee motivation and knowledge acquisition. Furthermore, they can be used in a complementary way, reinforcing the acquired knowledge.

Shear modulus and strength of an acrylic adhesive by the notched plate shear method (Arcan) and the thick adherend shear test (TAST)

In this work, the shear modulus and strength of the acrylic adhesive 3M® DP 8005 was evaluated by two different methods: the Thick Adherend Shear Test (TAST) and the Notched Plate Shear Method (Arcan). However, TAST standards advise the use of a special extensometer attached to the specimen, which requires a very experienced technician. In the present study, the adhesive shear displacement for the TAST was measured using an optical technique, and also with a conventional inductive extensometer of 25 mm used for tensile tests. This allowed for an assessment of suitability of using a conventional extensometer to measure this parameter. Since the results obtained by the two techniques are identical, it can be concluded that using a conventional extensometer is a valid option to obtain the shear modulus for the particular adhesive used. In the Arcan tests, the adhesive shear displacement was only measured using the optical technique. This work also aimed the comparison of shear modulus and strength obtained by the TAST and Arcan test methods.

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Filtering method in backlash phenomena analysis

The behavior of robotic manipulators with backlash is analyzed. Based on the pseudo-phase plane two indices are proposed to evaluate the backlash effect upon the robotic system: the root mean square error and the fractal dimension. For the dynamical analysis the noisy signals captured from the system are filtered through wavelets. Several tests are developed that demonstrate the coherence of the results.

A quest for the right word enhancing reflexivity and technology in terminology training

INTED2010, the 4th International Technology, Education and Development Conference was held in Valencia (Spain), on March 8, 9 and 10, 2010.

The use of the boundary element method in the analysis of single lap joints

The most common techniques for stress analysis/strength prediction of adhesive joints involve analytical or numerical methods such as the Finite Element Method (FEM). However, the Boundary Element Method (BEM) is an alternative numerical technique that has been successfully applied for the solution of a wide variety of engineering problems. This work evaluates the applicability of the boundary elem ent code BEASY as a design tool to analyze adhesive joints. The linearity of peak shear and peel stresses with the applied displacement is studied and compared between BEASY and the analytical model of Frostig et al., considering a bonded single-lap joint under tensile loading. The BEM results are also compared with FEM in terms of stress distributions. To evaluate the mesh convergence of BEASY, the influence of the mesh refinement on peak shear and peel stress distributions is assessed. Joint stress predictions are carried out numerically in BEASY and ABAQUS®, and analytically by the models of Volkersen, Goland, and Reissner and Frostig et al. The failure loads for each model are compared with experimental results. The preparation, processing, and mesh creation times are compared for all models. BEASY results presented a good agreement with the conventional methods.

Adherend thickness effect on the tensile fracture toughness of a structural adhesive using an optical data acquisition method

Adhesive bonding is nowadays a serious candidate to replace methods such as fastening or riveting, because of attractive mechanical properties. As a result, adhesives are being increasingly used in industries such as the automotive, aerospace and construction. Thus, it is highly important to predict the strength of bonded joints to assess the feasibility of joining during the fabrication process of components (e.g. due to complex geometries) or for repairing purposes. This work studies the tensile behaviour of adhesive joints between aluminium adherends considering different values of adherend thickness (h) and the double-cantilever beam (DCB) test. The experimental work consists of the definition of the tensile fracture toughness (GIC) for the different joint configurations. A conventional fracture characterization method was used, together with a J-integral approach, that take into account the plasticity effects occurring in the adhesive layer. An optical measurement method is used for the evaluation of crack tip opening and adherends rotation at the crack tip during the test, supported by a Matlab® sub-routine for the automated extraction of these quantities. As output of this work, a comparative evaluation between bonded systems with different values of adherend thickness is carried out and complete fracture data is provided in tension for the subsequent strength prediction of joints with identical conditions.

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

Finding a school technological partner: a multicriteria method for school information system producer selection

The choice of an information systems is a critical factor of success in an organization's performance, since, by involving multiple decision-makers, with often conflicting objectives, several alternatives with aggressive marketing, makes it particularly complex by the scope of a consensus. The main objective of this work is to make the analysis and selection of a information system to support the school management, pedagogical and administrative components, using a multicriteria decision aid system – MMASSITI – Multicriteria Method- ology to Support the Selection of Information Systems/Information Technologies – integrates a multicriteria model that seeks to provide a systematic approach in the process of choice of Information Systems, able to produce sustained recommendations concerning the decision scope. Its application to a case study has identi- fied the relevant factors in the selection process of school educational and management information system and get a solution that allows the decision maker’ to compare the quality of the various alternatives.

Comparison of Disposable Pipette Extraction and Dispersive Solid-Phase Extraction in the QuEChERS Method for Analysis of Pesticides in Strawberries

In this study, we sought to assess the applicability of GC–MS/MS for the identification and quantification of 36 pesticides in strawberry from integrated pest management (IPM) and organic farming (OF). Citrate versions of QuEChERS (quick, easy, cheap, effective, rugged and safe) using dispersive solid-phase extraction (d-SPE) and disposable pipette extraction (DPX) for cleanup were compared for pesticide extraction. For cleanup, a combination of MgSO4, primary secondary amine and C18 was used for both the versions. Significant differences were observed in recovery results between the two sample preparation versions (DPX and d-SPE). Overall, 86% of the pesticides achieved recoveries (three spiking levels 10, 50 and 200 µg/kg) in the range of 70–120%, with <13% RSD. The matrix effects were also evaluated in both the versions and in strawberries from different crop types. Although not evidencing significant differences between the two methodologies were observed, however, the DPX cleanup proved to be a faster technique and easy to execute. The results indicate that QuEChERS with d-SPE and DPX and GC–MS/MS analysis achieved reliable quantification and identification of 36 pesticide residues in strawberries from OF and IPM.

The influence of pre-departure training on expatriate adjustment: an empirical investigation with portuguese international assignees

This chapter examines the cross-cultural influence of training on the adjustment of international assignees. We focus on the pre-departure training (PDT) before an international assignment. It is an important topic because in the globalized world of today more and more expatriations are needed. The absence of PDT may generate the failure of the expatriation experience. Companies may neglect PDT due to cost reduction practices and ignorance of the need for it. Data were collected through semi-structured interviews to 42 Portuguese international assignees and 18 organizational representatives from nine Portuguese companies. The results suggest that companies should develop PDT programs, particularly when the cultural distance to the host country is bigger and when there is no previous experience of expatriation to that country in the company. The study is original because it details in depth the methods of PDT, its problems, and consequences. Some limitations linked to the research design and detailed in the conclusion should be overcome in future studies.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

Inovação de técnicas administrativas para o melhoramento de desempenho das atividades organizacionais

Dissertação apresentada ao Instituto Politécnico do Porto - Instituto Superior de Contabilidade e Administração do Porto, para obtenção do Grau de Mestre em Assessoria e Administração de Organizações, sob orientação de Anabela Mesquita, PhD