Project-based teaching is a widely acknowledged methodology for education in engineering. Realistic working experiences enhance students' motivation and develop skills for practice. However, case studies based on real industry problems are usually time consuming and often request a deeper knowledge of the circumstances than it is achievable within a standard course. This paper covers the design and implementation of a laboratory manufacturing line for teaching in process simulation and optimization. Industrial engineering students of the third year in the Quantitative Methods for Industrial Engineering subject at the Universidade da Coruna were offered a project-based evaluation plan consisting of the modeling, simulation and optimization of a manufacturing line in which they worked as labors. The experimental unit provided with an ad hoc designed process in which relevant issues in simulation could be demonstrated.

Multimodal transport has been promoted by several transport commissions initiatives as an alternative to road transport. A key factor for improving its competitiveness is to provide private and public investors with means of evaluating and selecting the most profitable options. This paper presents a parameterisation schema of a freight transport model for the assessment of a multimodal transport service in terms of its internal rate of return (IRR). Parameterisation enables the application of optimisation algorithms to maximise the profitability. Finally, a case study consisting of the evaluation of a new maritime service for the interregional freight transport in Spain is used to verify the proposed parameterisation.

Autocorrelation has been pointed out as one of the most challenging issues in manufacturing systems modeling. Numerical experimentation has shown that it may either enhance or harm performance. Furthermore, there is not yet a general agreement in what a realistic autocorrelation model is or whether it is actually relevant for practical applications. This paper provides a simulation analysis of the effects on performance caused by manufacturing process parameters following autoregressive (AR) processes. AR time series are employed for modeling variations in parameters that happen at a time scale different from the corresponding to process cycle execution. Three basic configurations are analyzed: serial line, assembly process and a disassembly process. A case study from the natural slate tiles industry is presented showing the differences obtained in simulation results between a model in which independent and identically distributed (i.i.d.) assumptions are adopted and one in which autocorrelation effects are considered.

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