Rullaavan ennustamisen kehittäminen CASE: ABB Oy Service

Tutkimuksen tavoitteena oli kehittää rullaavan ennustamisen toimintaa, jotta se tuottaisi relevanttia informaatiota tapausyrityksen ohjaukselle. Tutkimuksessa sovellettiin konstruktiivista tutkimusotetta, joka on ratkaisumenetelmä liikkeenjohdollisiin ongelmiin. Tutkimustulos eli ratkaisukonstruktio innovoitiin tutkijan luoman viitekehyksen ja empiirisen tutkimuksen havaintojen avulla. Tutkimustuloksien perusteella analyyttisen rullaavan ennustamisen tarkoituksena on tyydyttää eri ohjaustasojen informaatiotarpeita ja tukea asiakaslähtöisen tapausyrityksen liiketoimintaympäristöön sopeutumista. Tutkimuksen mukaan rullaava ennustaminen on suunnittelua, joka pyrkii organisatoriseen oppimiseen. Kehittämiseen liittyviä näkökulmia, organisatorisia ja järjestelmällisiä tekijöitä löydettiin useita. Nämä eivät rajoittuneet ainoastaan johdon laskentatoimen alueelle.

Rullaava ennustaminen talousohjauksen välineenä

Kiinnostus rullaavaa ennustamista kohtaan on kasvanut 2000-luvulla sen tarjotessa vaihtoehdon perinteiselle budjetoinnille. Rullaavasta ennustamisesta ei ole kuitenkaan tehty viimeisimpiin tietoihin perustuvaa tutkielmaa, jossa yhdistetään analyyttisesti uusinta tutkimus- ja kirjallisuustietoa. Tämän lisäksi rullaavaan ennustamiseen liittyvä termistö ei ole vakiintunutta, eikä termistöä ole tutkittu tai vertailtu. Nopeasti muuttuvassa liiketoimintaympäristössä perinteinen budjetointi ei enää vastaa siihen tarpeeseen, mihin se on tarkoitettu. Kritiikki budjetointia kohtaan on kasvanut mutta edelleen suurin osa yrityksistä käyttää sitä talousohjauksessa. Perinteinen budjetointi koetaan kalliiksi, aikaa vieväksi sekä irralliseksi strategiasta. Lisäksi se ei ota huomioon muuttuvaa ympäristöä ja on usein vanhentunut jo käyttöönotettaessa. Näitä budjetoinnin heikkouksia voidaan poistaa ottamalla käyttöön rullaava ennustaminen talousohjauksen välineenä. Rullaavassa ennustamisessa on kyse siirtymisestä kiinteästä budjettivuodesta esimerkiksi neljännesvuosittain ylemmällä tasolla tapahtuvaan ennustamiseen ennusteajanjakson ulottuessa aina seuraavalle vuodelle. Rullaavaa ennustamista voidaan käyttää budjetoinnin ohella, mikä on tutkimusten mukaan selvästi suosituin menetelmä. Toinen vaihtoehto on korvata perinteinen budjetointi rullaavalla ennustamisella. Tällöin prosessia kutsutaan rullaavaksi budjetoinniksi tai suunnitteluksi. Kolmas vaihtoehto on budjetoinnin hylkääminen ja uusien taloudenohjauksen ja prosessien soveltaminen eli Beyond Budgeting. Tämä korostaa budjetoinnin hylkäämisen lisäksi suorituskyvyn mittaamista ja palkitsemista suhteellisiin tuloksiin ja ulkoiseen sekä sisäiseen vertailuun perustuen sekä vallan hajauttamista organisaatiossa tavoitteena asiakasarvon kasvattaminen.

Forecasting human entrances at a commercial store using facial recognition data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

Thermodynamic and topological instability approaches for forecasting glass-forming ability in the ternary Al-Ni-Y system

A thermodynamic approach to predict bulk glass-forming compositions in binary metallic systems was recently proposed. In this approach. the parameter gamma* = Delta H-amor/(Delta H-inter - Delta H-amor) indicates the glass-forming ability (GFA) from the standpoint of the driving force to form different competing phases, and Delta H-amor and Delta H-inter are the enthalpies for-lass and intermetallic formation, respectively. Good glass-forming compositions should have a large negative enthalpy for glass formation and a very small difference for intermetallic formation, thus making the glassy phase easily reachable even under low cooling rates. The gamma* parameter showed a good correlation with GFA experimental data in the Ni-Nb binary system. In this work, a simple extension of the gamma* parameter is applied in the ternary Al-Ni-Y system. The calculated gamma* isocontours in the ternary diagram are compared with experimental results of glass formation in that system. Despite sonic misfitting, the best glass formers are found quite close to the highest gamma* values, leading to the conclusion that this thermodynamic approach can lie extended to ternary systems, serving as a useful tool for the development of new glass-forming compositions. Finally the thermodynamic approach is compared with the topological instability criteria used to predict the thermal behavior of glassy Al alloys. (C) 2007 Elsevier B. V. All rights reserved.

Electric Power Forecasting Methodologies of Some South American Countries: A Comparative Analysis

In this paper, a comparative analysis of the long-term electric power forecasting methodologies used in some South American countries, is presented. The purpose of this study is to compare and observe if such methodologies have some similarities, and also examine the behavior of the results when they are applied to the Brazilian electric market. The abovementioned power forecasts were performed regarding the main four consumption classes (residential, industrial, commercial and rural) which are responsible for approximately 90% of the national consumption. The tool used in this analysis was the SAS (c) program. The outcome of this study allowed identifying various methodological similarities, mainly those related to the econometric variables used by these methods. This fact strongly conditioned the comparative results obtained.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Texture and mechanical properties evolution of a deep drawing medium carbon steel during cold rolling and subsequent recrystallization

Medium carbon steels are mostly used for simple applications; however, new applications have been developed for which good sheet metal formability is required. These types of steels have an inherent low formability. A medium-carbon hot-rolled SAE 1050 steel was selected for this study. It has been cold rolled with thickness reductions varying between 7 and 80%. The samples obtained were used to evaluate the strain hardening curve. For samples with a 50 and 80% thickness reduction, an annealing heat treatment was performed to achieve recrystallization. The material was characterized in the ""as-received"", cold rolled and annealed conditions using several methods: optical metallography, X-ray diffraction (texture), Vickers hardness, and tensile testing. For large thickness reductions, the SAE 1050 steel presented low elongation, less than 2%, and yield strength (YS) and tensile strength (TS) around 1400 MPa. Texture in the ""as-received"" condition showed strong components on the {001} plane, in the < 100 >, < 210 > and (110) directions. After cold rolling, the texture did not present any significant changes for small thickness reductions, however. It changed completely for large ones, where gamma, < 111 >//ND, alpha, < 110 > HRD, and gamma prime, < 223 >//ND, fibres were strengthened. After annealing, the microstructure of the SAE 1050 steel was characterized by recrystallized ferrite and globular cementite. There was little change in the alpha fibre for the 50% reduction, whereas for the 80% reduction, its intensity increased. Both gamma and gamma prime fibres vanished upon annealing for 50 and 80% reductions alike. (c) 2008 Elsevier B.V. All rights reserved.

Medium carbon steel deep drawing: A study on the evolution of mechanical properties, texture and simulations, from cold rolling to the end product

Medium carbon steels are mostly used for simple applications; nevertheless new applications have been developed for which good sheet formability is required. This class of steels has an inherent low formability. A medium carbon hot rolled SAE 1050 steel has been selected for this study. It has been cold rolled with reductions in the 7-80% range. Samples have been used to assess the cold work hardening curve. For samples with a 50 and 80% thickness reduction, an annealing heat treatment has been performed to obtain recrystallization. The material has been characterized in the ""as received"", cold rolled and annealed conditions, using several methods: optical microscopy, X-ray diffraction (texture), Vickers hardness and tensile testing. The 50% cold rolled and recrystallized material has been further studied in terms of sheet metal formability and texture evolution during the actual stamping of a steel toecap that has been used to validate the finite element simulations. (C) 2008 Elsevier B.V. All rights reserved.

Effect of rolling on the residual stresses and magnetic properties of a 0.5% Si electrical steel

Cold-rolled (0-19% of reduction) 0.5% Si electrical steel sheets were studied in detail, including macro and micro residual stress measurements, crystallographic texture, dc-hysteresis curves and iron losses. Even for the smallest deformation, losses increase significantly, with large increase of the hysteresis losses, whereas the anomalous losses reduce slightly. The residual microstresses are similar to 150-350 MPa, whereas residual macrostresses are compressive, similar to 50 MPa. The large increase of the hysteresis losses is attributed to the residual microstresses. The dislocation density estimated by X-ray diffraction is in reasonable agreement with that predicted from the Sablik et al. model for effect of plastic deformation on hysteresis. The intensity of the texture fibers {1 1 1}< u v w > and < 110 >//RD (RD = rolling direction) increases with the reduction. (C) 2008 Elsevier B.V. All rights reserved.

Adequacy of Cold Rolling Models to Upgrade Set-up Generation Systems

This paper presents two strategies for the upgrade of set-up generation systems for tandem cold mills. Even though these mills have been modernized mainly due to quality requests, their upgrades may be made intending to replace pre-calculated reference tables. In this case, Bryant and Osborn mill model without adaptive technique is proposed. As a more demanding modernization, Bland and Ford model including adaptation is recommended, although it requires a more complex computational hardware. Advantages and disadvantages of these two systems are compared and discussed and experimental results obtained from an industrial cold mill are shown.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.