Juan R. Trapero

Juan R. Trapero
University of Castilla-La Mancha · Departamento de Administración de Empresas

Ph. D. Industrial Engineering

About

72
Publications
33,838
Reads
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1,644
Citations
Introduction
I am working as Full Professor at University of Castilla-La Mancha (Spain), Department of business administration. My research interests are focused on forecasting problems, supply chain, bullwhip effect, energy forecasting, control and system identification.
Additional affiliations
May 2008 - August 2010
Lancaster University
Position
  • Posdoctoral researcher
May 2008 - August 2010
Lancaster University
Position
  • posdoc position

Publications

Publications (72)
Article
Full-text available
Shorter product life cycles and aggressive marketing, among other factors, have increased the complexity of sales forecasting. Forecasts are often produced using a Forecasting Support System that integrates univariate statistical forecasting with managerial judgment. Forecasting sales under promotional activity is one of the main reasons to use exp...
Article
Full-text available
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
Article
Global Horizontal Irradiation forecasts are necessary for an efficient use of fluctuating energy output from photovoltaic plants. The purpose of this paper is to provide efficient, easy-to-implement Global Horizontal Irradiation forecasts on an hourly basis for a medium-term horizon (longer than 48 h). These forecasts are essential for the strategi...
Article
The development of circular economies due to the limitation of natural resources is becoming a common strategy of paramount importance among different countries. In Spain, given the strategic nature of its olive industry, trying to value one of its main residuals (olive pomace) alone or together with other residues through its chemical transformati...
Preprint
Full-text available
My contributions to this voluminous publication can be found on pp 38-40 "The natural law of growth in competition" and on pp 169-170 "Dealing with logistic forecasts in practice"
Chapter
Automatic identification of time series models is a necessity once the big data era has come and is staying among us. This has become obvious for many companies and public entities that have passed from a crafted analysis of each individual problem to handle a tsunami of information that has to be processed efficiently, online and in record time. A...
Article
An economic assessment of methanol production from syngas obtained by co-gasification of petcoke and olive pomace was performed. This process was simulated with Aspen Plus® software. Net Price Value (NPV), Internal Rate of Return (IRR), Payback period (PBP), break-even and minimum product sales price were the techno-economic parameters used for ana...
Chapter
One of the main objectives of an inventory system consists of guarantee a target service level. However, classical approaches are based on assumptions that introduce significant errors. This fact can lead to design inventory policies that do not guarantee the achievement of the target service level. This paper suggests an expression to compute the...
Article
Full-text available
Throughout the last decades, collaborative schemes, under an amalgam of different acronyms (ECR, CPFR, VMR, etc.), have been developed to mitigate the problematic Bullwhip effect. Essentially, companies work together by either sharing information, making joint decisions, or sharing benefits to reach potential synergies. This work aims at reviewing...
Article
Full-text available
Inaccurate forecasts can be costly for company operations, in terms of stock-outs and lost sales, or over-stocking, while not meeting service level targets. The forecasting literature, often disjoint from the needs of the forecast users, has focused on providing optimal models in terms of likelihood and various accuracy metrics. However, there is e...
Chapter
SSpace is a MATLAB toolbox for State-Space modeling that provides the user with tools for linear Gaussian, nonlinear, and non-Gaussian systems with the most advanced and up-to-date features available in any State-Space framework. Great flexibility is achieved because each model is coded on a standard MATLAB function, thence having absolute control...
Article
Full-text available
The safety stock calculation requires a measure of the forecast error uncertainty. Such errors are usually assumed Gaussian iid (independent, identically distributed). However, deviations from iid deteriorate the supply chain performance. Recent research has shown that, alternatively to theoretical approaches, empirical techniques that do not rely...
Article
Full-text available
Supply chain risk management has drawn the attention of practitioners and academics alike. One source of risk is demand uncertainty. Demand forecasting and safety stock levels are employed to address this risk. Most previous work has focused on point demand forecasting, given that the forecast errors satisfy the typical normal i.i.d. assumption. Ho...
Article
Time series forecasting has been an active research area for decades, receiving considerable attention from very different domains, such as econometrics, statistics, engineering, mathematics, medicine and social sciences. Moreover, with the emergence of the big data era, the automatic identification with the appropriate techniques remains an interm...
Article
Over the last decade, Microbial Fuel Cells (MFCs) have experienced significant scientific and technological development, to the point of becoming close to commercialization. One key assessment that clearly establishes whether one technology can fully enter the market is the profitability demonstration. For this demonstration, classical evaluation c...
Article
Full-text available
In order to integrate solar energy into the grid it is important to predict the solar radiation accurately, where forecast errors can lead to significant costs. Recently, the increasing statistical approaches that cope with this problem is yielding a prolific literature. In general terms, the main research discussion is centred on selecting the “be...
Article
Full-text available
Supply chain risk management is drawing the attention of practitioners and academics. A source of risk is demand uncertainty. To deal with it demand forecasting and safety stocks are employed. Most of the work has focused on point demand forecasting, assuming that forecast errors follow the typical normal i.i.d. assumption. The variability of the f...
Presentation
Full-text available
Solar power generation has been steadily increasing worldwide as a response to environmental concerns. Unfortunately, the integration of solar energy into the energy mix of a country brings new challenges. The main problem is due to the variability of the solar energy, which is not available ``on demand’’. In Spain, forecasts of production have to...
Data
Bullwhip effect is a problem of paramount importance that reduces competitiveness of supply chains around the world. A significant effort is being devoted by both practitioners and academics to understand its causes and to reduce its pernicious consequences. Nevertheless, limited research has been carried out to analyze potential metrics to measure...
Article
Full-text available
Solar power generation is a crucial research area for countries that suffers from high dependency on external energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate this generated energy into the grid, solar irradiation must be forecasted, where deviations of the forecasted value involv...
Article
The main objective of this paper is to estimate the impact that the expansion of the HSR network has had on air transport in Spain by estimating the substitution effect between the two types of transportation. This paper considers the way that the HSR network has grown and how this growth could have affected air transport dynamically. The findings...
Chapter
Due to modern economies moving towards a more sustainable energy supply, solar power generation is becoming an area of paramount importance. In order to integrate this generated energy into the grid, solar irradiation must be forecasted, where deviations of the forecasted value involve significant costs. Intermittence, high frequency, and nonstatio...
Article
Full-text available
Bullwhip effect is a problem of paramount importance that reduces com-petitiveness of supply chains around the world. A significant effort is being devoted by both practitioners and academics to understand its causes and to reduce its pernicious consequences. Nevertheless, limited research has been carried out to analyze potential metrics to measur...
Article
Full-text available
Decision making process in maintenance management produces a final choice. Fault Tree Analysis (FTA) is proposed as a graphical representation of logical relationships between the elements that comprise the decision making process in maintenance management. A Fault Tree (FT) is compound by different events and logic gates. Complex systems analysis...
Article
Full-text available
The juice industry wastewater is characterized by a high organic load concentration, which requires an expensive treatment. Recent investigations propose microbial fuel cells as a wastewater treatment alternative. This article reports an economic assessment of the implementation of 10 microbial fuel cells to deal with wastewaters in a juice Industr...
Article
Full-text available
Identifying the appropriate time series model to achieve good forecasting accuracy is a challenging task. We propose a novel algorithm that aims to mitigate the importance of model selection, while increasing accuracy. From the original time series, using temporal aggregation, multiple time series are constructed. These derivative series highlight...
Book
Decision making process in maintenance management produces a final choice. Fault Tree Analysis (FTA) is proposed as a graphical representation of logical relationships between the elements that comprise the decision making process in maintenance management. A Fault Tree (FT) is compound by different events and logic gates. Complex systems analysis...
Article
The structure of the wind turbines nowadays is a critical element due to their importance from the reliability, availability, safety, and cost points of view. This is more relevant when the offshore wind turbine is considered. This paper introduces a novel design of a Fault Detection and Diagnosis (FDD) model based on ultrasound technique. The FDD...
Chapter
The bullwhip effect (BE) consists of the demand variability amplification that exists in a supply chain when moving upwards. This undesirable effect produces excess inventory and poor customer service. Recently, several research papers from either a theoretical or empirical point of view have indicated the nature of the demand process as a key aspe...
Conference Paper
Full-text available
Demand forecasting is a complex topic due to different factors like promotions. Generally, promotions may be forecast by using an univariate statistical approach (system forecast) that is judgmentally adjusted by company experts. The present work reports an analysis of the managerial adjustments accuracy when promotions are taking place. Additional...
Article
Full-text available
Sales forecasting is increasingly complex due to a range of factors, such as the shortening of product life cycles, increasingly competitive markets, and aggressive marketing. Often, forecasts are produced using a Forecasting Support System that integrates univariate statistical forecasts with judgment from experts in the organization. Managers the...
Article
Full-text available
Forecasts of demand are crucial to drive supply chains and enterprise resource planning systems. Usually, well-known univariate methods that work automatically such as exponential smoothing are employed to accomplish such forecasts. The traditional Supply Chain relies on a decentralised system where each member feeds its own Forecasting Support Sys...
Article
This work proposes an adaptive control scheme applied to single link-flexible manipulators, which combines a feedback controller of the joint angle with an adaptive input shaper updated by an algebraic non-asymptotic identification. The feedback controller is designed to guarantee trajectory tracking of the joint angle, simplifying thus the input s...
Chapter
Demand forecasts are crucial to drive supply chains and enterprise resource planning systems. Improved accuracy in forecasts directly affects all levels of the supply chain, reducing stock costs and increasing customer satisfaction. Usually, this problem is faced by testing various time series methods with a different level of complexity to find ou...
Chapter
This paper presents the ECOnometrics TOOLbox (ECOTOOL), a new MATLAB forecasting toolbox that embodies several tools for identification, validation and forecasting of dynamic models based on time series analysis. Tools to perform a wide range of exploratory and statistical tests with visual counterparts are included, designed in easy-to-use front e...
Article
The residual vibrations of highly resonant flexible structures can be usually composed of sinusoidal signals. The identification of the frequencies, amplitudes and/or phases of these sinusoidal signals may be of interest for health monitoring or to update controller parameters in active vibration control systems. This work considers a previously de...
Article
Prediction of demand is a key component within supply chain management. Improved accuracy in forecasts directly affects all levels of the supply chain, reducing stock costs and increasing customer satisfaction. In many application areas, demand prediction relies on statistical software which provides an initial forecast subsequently modified by the...
Article
A pneumatic suspension that can adapt itself to the incoming vibration is presented in this paper. A switching control strategy between two different configurations is proposed and studied. The objective is to avoid undesirable resonant frequencies. The control procedure is based on the pre-knowledge of the incoming vibration frequency, and when th...
Article
Full-text available
Load demand prediction for mid or long-term horizons is important for the development of any model for electric power system planning. Literature on this topic is much scarcer than short-term forecasting, mainly due to the inherent difficulties in long-term modelling. The aim of this paper is to develop a general multi-rate methodology in order to...
Article
The changes taking place in electricity markets during the last two decades have produced an increased interest in the problem of forecasting, either load demand or prices. Many forecasting methodologies are available in the literature nowadays with mixed conclusions about which method is most convenient. This paper focuses on the modeling of elect...
Article
Input shaping is an efficient feedforward control technique which has motivated a great number of contributions in recent years. Such a technique generates command signals with which manoeuvre flexible structures without exciting their vibration modes. This paper presents a novel adaptive input shaper based on an algebraic non-asymptotic identifica...
Article
Full-text available
In this paper, we propose a fast online closed-loop identification method combined with an output-feedback controller of the generalized proportional integral (GPI) type for the control of an uncertain flexible robotic arm with unknown mass at the tip, including a Coulomb friction term in the motor dynamics. A fast nonasymptotic algebraic identific...
Conference Paper
The problem of estimating the defining parameters in a sinusoidal signal corrupted by noise is very important in the vibration analysis of flexible structures. Such estimations can be used in Health Monitoring or in adaptive control applications. Usually, pure sinusoidal models are used in order to represent the mechanical vibration. The main probl...
Article
An algebraic identification approach is used for the fast and reliable on-line determination of the defining parameters of two sinusoidal signals of different, unknown, amplitudes, phases and frequencies from their noise-perturbed measured sum. The proposed method is based on the algebraic derivative approach, defined in the frequency domain, yield...
Article
A significant research effort has been conducted in the past to achieve a reliable on-line vibration mode estimator. Frequently, pure sinusoidal models of the underlying mechanical system have been used to accomplish the estimation task. In this paper, an algebraic approach is proposed for the fast and reliable, on-line identification of the natura...
Conference Paper
Full-text available
Palabras clave: ciclo económico, fi ltro adaptativo, estimación de frecuencia, Espacio de los Estados. 1. Introducción Desde el siglo XIX diferentes investigadores han realizado un gran esfuerzo en buscar una explicación a las dramáticas caídas que cada cierto tiempo registraba la actividad económica. En 1863, el francés Clement Juglar demostró con...
Article
An algebraic approach is proposed for the fast and reliable, on line, identification of the amplitude, frequency and phase parameters in unknown noisy sinusoidal signals. The proposed method uses the algebraic derivative method in the frequency domain yielding exact formulae, when placed in the time domain, for the unknown parameters. These formula...
Article
The changes experienced by electricity markets in recent years have created the necessity for more accurate forecast tools of electricity prices, both for producers and consumers. Many methodologies have been applied to this aim, but in the view of the authors, state space models are not yet fully exploited. The present paper proposes a univariate...
Conference Paper
Full-text available
In this article, we propose a fast on-line closed loop identification method of continuous-time combined with an output feedback controller of the generalized proportional integral type (GPI), for the control of an uncertain flexible robotic arm with unknown mass at the tip, including a Coulomb friction term in the motor dynamics. A fast, non-asymp...
Conference Paper
In this article, we propose an output feedback controller of the generalized proportional integral type (GPI), combined with an on-line closed loop identification method, for the control of an uncertain flexible robotic arm with unknown mass at the tip, motor inertia, viscous friction and electromechanical constant, and including a Coulomb friction...
Conference Paper
An algebraic approach is proposed for the fast and reliable, on line, identification of the amplitude, frequency and phase parameters in unknown noisy sinusoidal signals. The proposed method uses the algebraic derivative method in the frequency domain yielding exact formulae, when placed in the time domain, for the unknown parameters: Amplitude, fr...
Article
Full-text available
En el seno de la Unión Europea, la política común del transporte ferroviario encuentra su origen a nivel constitucional en el Título IV del Tratado de Roma (1957). Desde entonces se han desarrollado numerosas directivas con el fin de velar por la seguridad en dicho transporte. Continuando en dicha línea, las nuevas directivas siguen poniendo de man...
Article
Full-text available
Palabras clave: Máxima verosimilitud, dominio de la frecuencia, espacio de los estados, mercados eléctricos, predicción. 1. Introducción La industria de la electricidad ha estado inmersa en un proceso de reestructuración durante los últimos años en muchas partes del mundo. Una de las causas principales de tales cambios es la liberalización del merc...

Questions

Questions (4)
Question
I am working with probability forecasts and I want to estimate the probability distribution of a discrete random variable. I've tried the histogram, but not sure it is a good option. Can you help me, please?
Thanks!
Question
Currently, I am teaching a subject about operations management and I have to introduce to my students the importance of safety stocks and the different ways to determine it. At this point, I was analyzing how this issue is explained in operations management books, and I realized that some of them compute the safety stock on the basis of the lead time demand distribution (Heizer and Render,  2008), whereas books more specialized in inventory management (Silver et al, 1998) and (Nahmias, 2004), they suggest to use the lead time forecast demand error distribution.
I think that we should use the lead time forecast demand error, what do you think?
Question
Regarding solar irradiation forecasting in the short-term, there are two main approaches from a statistical point of view to deal with seasonality. The first one is to remove seasonality by computing clearness indexes, the second one is to remove seasonality by using a statistical approach as the harmonic regression, for example. My question is: which of those alternatives is the best option to improve the solar irradiation forecasting accuracy? Is there any work that has analyzed such a question?
Thanks!
JR
Question
A simple but tricky question. Any opinion?

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Projects (2)
Project
Industry globalization is making that Spanish and European companies should become more competitive. In that sense, it is crucial to improve the supply chain management (SCM) in order to reduce costs and enhance customer service level. In fact, many authors claim that the strategy should be focused on obtaining a global supply chain optimum rather than local suboptimum. Nonetheless, traditionally, supply chain members establish a minimal collaboration between them. This type of SCM is known to be responsible of an undesired phenomenon called the bullwhip effect, which consists of the demand variability amplification when moving upwards in the supply chain. This effect is behind of losing up to 30% of the supply chain profits. Among the consequences of this amplification, for instance, we might find excess inventory, poor customer service and poor product forecasts. In order to reduce the bullwhip effect different collaborative schemes in terms of planning and/or replenishment policies have been proposed. Unfortunately, the industry application of these collaborative schemes have turned out not to be as successful as it was expected. In particular, different case studies describe how, despite the considerable investment in a business software, which enables the information exchange between echelons in the supply chain, the returns obtained were not satisfactory. Essentially, although the companies had available an increasing vast amount of information of other supply chain echelons or even external information coming from social networks (big data), their business intelligence schemes particularized in traditional forecasting and replenishment policies could not handle efficiently such new valuable information. Therefore, the aim of this project is to investigate novel forecasting and stock control methodologies capable of incorporating efficiently the key information from the rest of the supply chain and its environment to achieve a considerable reduction of costs as a consequence of the bullwhip effect reduction. Simulation results will provide the theoretical basis to determine the improvement extent obtained by the development of the proposed forecasting and stock control techniques under collaboration between companies’ schemes. In order to validate the results of the project, a dataset comprising sales, shipments, promotional activities and forecasts obtained from companies interested in our research will be also tested