Technology roadmap for new sales support and management system for crane manufacturing company

Sales configurators are essential tools for companies that offer complicated case specifically crafted products for customers. Most sophisticated of them are able to design an entire end product on the fly according to given constraints, calculate price for the offer and move the order into production. This thesis covers a sales configurator acquisition project in a large industrial company that offers cranes for its customers. The study spans the preliminary stages of a large-scale software purchase project starting from the specification of problem domain and ending up presenting the most viable software solution that fulfils the requirements for the new system. The project consists of mapping usage environment, use cases, and collecting requirements that are expected from the new system. The collected requirements involve fitting the new sales system into enterprise application infrastructure, mitigating the risks involved in the project and specifying new features to the application whilst preserving all of the admired features of the old sales system currently used in the company. The collected requirements were presented to a number of different sales software vendors who were asked to provide solution suggestions that would fulfil all the demands. All of the received solution proposals were exposed to an evaluation to determine the most feasible solutions, and the construction of evaluation criteria itself was a part of the study. The final outcome of this study is a short-list of the most feasible sales configurator solutions together with a description of how software purchase process in large enterprises work, and which aspects should be paid attention in large projects of similar kind.

Role of references in international industrial marketing : a theory-building case study about supplier’s processes of utilizing references

Scientific studies regarding specifically references do not seem to exist. However, the utilization of references is an important practice for many companies involved in industrial marketing. The purpose of the study is to increase the understanding about the utilization of references in international industrial marketing in order to contribute to the development of a theory of reference behavior. Specifically, the modes of reference usage in industry, the factors affecting a supplier's reference behavior, and the question how references are actually utilized, are explored in the study. Due to the explorative nature of the study, a research design was followed where theory and empirical studies alternated. An Exploratory Framework was developed to guide a pilot case study that resulted in Framework 1. Results of the pilot study guided an expanded literature review that was used to develop first a Structural Framework and a Process Framework which were combined in Framework 2. Then, the second empirical phase of the case study was conducted in the same (pilot) case company. In this phase, Decision Systems Analysis (DSA) was used as the analysis method. The DSA procedure consists of three interviewing waves: initial interviews, reinterviews, and validating interviews. Four reference decision processes were identified, described and analyzed in the form of flowchart descriptions. The flowchart descriptions were used to explore new constructs and to develop new propositions to develop Framework 2 further. The quality of the study was ascertained by many actions in both empirical parts of the study. The construct validity of the study was ascertained by using multiple sources of evidence and by asking the key informant to review the pilot case report. The DSA method itself includes procedures assuring validity. Because of the choice to conduct a single case study, external validity was not even pursued. High reliability was pursued through detailed documentation and thorough reporting of evidence. It was concluded that the core of the concept of reference is a customer relationship regardless of the concrete forms a reference might take in its utilization. Depending on various contingencies, references might have various tasks inside the four roles of increasing 1) efficiency of sales and sales management, 2) efficiency of the business, 3) effectiveness of marketing activities, and 4) effectiveness in establishing, maintaining and enhancing customer relationships. Thus, references have not only external but internal tasks as well. A supplier's reference behavior might be affected by many hierarchical conditions. Additionally, the empirical study showed that the supplier can utilize its references as a continuous, all pervasive decision making process through various practices. The process includes both individual and unstructured decision making subprocesses. The proposed concept of reference can be used to guide a reference policy recommendable for companies for which the utilization of references is important. The significance of the study is threefold: proposing the concept of reference, developing a framework of a supplier's reference behavior and its short term process of utilizing references, and conceptual structuring of an unstructured and in industrial marketing important phenomenon to four roles.

Piensarjatuotannon hitsauksen robotisointi

Diplomityön tarkoituksena on selvittää hitsauksen robotisointimahdollisuudet vakiintuneelle piensarjatuotteelle. Tarkastelun kohteeksi valittiin maanpäällisen porausyksikön runkopari, joka rakentuu ylä- ja alarungosta. Hitsaus on nykytilanteessa käsinhitsausta ja tuotetta tehdään noin 300 kpl / vuosi. Hitsauksen robotisoinnilla halutaan aikaansaada kustannussäästöä hitsauksen osalta ja tuotantokapasiteetin nousua. Työn teoriaosa voidaan jakaa neljään osaan: hitsaustekniikka, robottihitsattava tuote, robotisoituhitsaus ja investointilaskelmat. Hitsaustekniikassa lähdetään liikkeelle hitsauksen kannalta oleellisimmista perusasioista, jolloin lukijalle syntyy laajempi kokonaiskuva asiasta. Hitsauksen robotisointia suunniteltaessa korostuu tuotteen hitsattavuus. Hyvin suunniteltu tuote mahdollistaa robotisoidun hitsauksen ja luo edellytykset laadukkaalle, taloudelliselle ja tuottavalle hitsaukselle. Robotisoidun hitsauksen osassa rakennetaan kokonaisuus, jolloin lopputuloksena on tehokas robottijärjestelmä. Samalla käsitellään sekä varsinaista hitsausteknistä toteutusta että robottijärjestelmän komponentteja. Investointilaskelmien avulla varmistetaan robottijärjestelmän ja koko tuotantoketjun kannattavuus. Käytännön osuudessa selvitetään robotisoidun hitsauksen mahdollisuudet valitulle tuotteelle ja robotisoinnin aikaansaamat kustannussäästöt. Tuotteen ylärungosta valitaan etuosa tarkempaa CASE tyylistä tarkastelua varten. CASE:ssa käydään läpi etuosan valmistettavuus ja selvitetään robotisoinnista aikaansaamat säästöt. Investointilaskelmien avulla selvitetään käytännön osuudessa robotisoidun hitsauksen kannattavuus tietyille robottijärjestelmille.

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

Real-Time Simulation of Mobile and Industrial Machines Using the Multibody Simulation Approach

This thesis introduces a real-time simulation environment based on the multibody simulation approach. The environment consists of components that are used in conventional product development, including computer aided drawing, visualization, dynamic simulation and finite element software architecture, data transfer and haptics. These components are combined to perform as a coupled system on one platform. The environment is used to simulate mobile and industrial machines at different stages of a product life time. Consequently, the demands of the simulated scenarios vary. In this thesis, a real-time simulation environment based on the multibody approach is used to study a reel mechanism of a paper machine and a gantry crane. These case systems are used to demonstrate the usability of the real-time simulation environment for fault detection purposes and in the context of a training simulator. In order to describe the dynamical performance of a mobile or industrial machine, the nonlinear equations of motion must be defined. In this thesis, the dynamical behaviour of machines is modelled using the multibody simulation approach. A multibody system may consist of rigid and flexible bodies which are joined using kinematic joint constraints while force components are used to describe the actuators. The strength of multibody dynamics relies upon its ability to describe nonlinearities arising from wearing of the components, friction, large rotations or contact forces in a systematic manner. For this reason, the interfaces between subsystems such as mechanics, hydraulics and control systems of the mechatronic machine can be defined and analyzed in a straightforward manner.

Älykkäät lääkkeenjakoratkaisut:Liiketoimintakonseptien nykytila

Älykkäille lääkkeenjakoratkaisuille tulee luultavasti olemaan tulevaisuudessa suuri kysyntä, sillä asiakasmäärät ja julkisen terveydenhuollon resurssit eivät kohtaa toisiaan. Säilyttääksemme yhteiskuntamme terveydenhuollon tason kohtuullisilla kustannuksilla on ainoana mahdollisuutena alan uudet innovaatiot. Älykkäillä lääkkeenjakoratkaisuilla tarkoitetaan älykkäitä lääkepakkauksia tai muita lääkintään liittyviä tuotteita tai palveluja, jotka mahdollistavat teknologisen edistyksellisyyden avulla ihmistyömäärän vähentämisen terveydenhuollossa. Raportti esittelee tapaustutkimuksen alustavia tuloksia, joissa on tarkoituksena tuoda esille yleiskatsaus tuotteista ja asiakaseduista. Tuotteet on kuvattu niihin liittyvien liiketoimintamallinen tarjoomien avulla. Analyysi rakentuu liiketoimintamallin neljän peruspilarin mukaisesti, Tuote, Asiakassuhde, Rakenne, ja Talous, jotka määrittävät mallin asiakasarvon. Lähtökohtana liiketoimintamallien mittaamisessa on neljä arvon päämittaria: tekniset, taloudelliset, palvelulliset, ja sosiaaliset attribuutit. Esimerkin avulla voidaan huomata, että tarjoamaa markkinoilla on vakiintumaton. Yksi malli painotti lääkkeiden annosjakelun tehokkuutta, toinen nautittujen lääkkeiden oton valvontaa ja kolmas yritti pärjätä molemmissa. Suurimmat hyödyt voidaan nähdä, jos pystytään yhdistämään koneellinen jakelu älykkäisiin jakelulaitteisiin.

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Pinnoiteteollisuudessa syntyvien maalijätteiden hyötykäyttö ja uudet liiketoimintamahdollisuudet

Tämän diplomityön tavoite on kartoittaa maalien ja lakkojen valmistuksessa syntyvien sivuvirtojen hyötykäyttöä ja hyötykäyttöpotentiaalia nykyisellään. Työn tarkoitus on toimia esiselvityksenä pinnoiteteollisuuden sivuvirtojen hyötykäyttöön liittyvien liiketoimintamahdollisuuksien syvemmälle analyysille. Teollisuuden sivuvirtoihin liittyvää tietoa kerätään tilastoista ja olemassa olevista raporteista sekä haastattelemalla teollisuus- ja palveluyritysten edustajia sekä alan asiantuntijoita. Sivuvirtojen teknisten hyötykäyttömahdollisuuksien ja liiketoiminnallisten mahdollisuuksien tarkastelua varten järjestetään työpajoja asiantuntijoille Apila Group Oy Ab:n asiantuntijaverkostossa. Neljässä haastatellussa tuotantolaitoksissa syntyi vuonna 2008 yhteensä 6 662 tonnia kiinteää jätettä ja lietteitä. 68 % näistä sivuvirroista hyötykäytettiin energiana tai polttoaineen valmistuksessa. Materiaalina sivuvirtoja hyötykäytettiin 16 % sivuvirroista, pääasiassa pahvia, paperia, metalleja sekä tynnyreitä ja kontteja. Myös merkittävä osa liuottimista otettiin talteen uudelleenhyödyntämistä varten. Tässä diplomityössä hyötykäyttömahdollisuuksien tarkempaa tarkastelua varten valittiin tavanomaisiksi jätteiksi luokiteltuja maalisivuvirtoja, joita haastatelluissa tuotantolaitoksissa syntyi noin 1 500 tonnia. Maalisivuvirtojen tärkeimmät materiaaliominaisuudet liittyvät niiden sisältämiin täyte- ja sideaineisiin, jotka muodostavat merkittävän osan maalien koostumuksesta. Selvityksen mukaan nämä ominaisuudet voidaan ottaa hyötykäyttöön erilaisissa yhdistelmämateriaaleissa, esimerkiksi ekstruusiopuristetuissa tai ahtopuristetuissa muovikuitukomposiiteissa. Komposiittien raaka-aineena käytetään jo erilaisia sivuvirtoja ja lisäksi erilaisten komposiittien markkinoiden ennustetaan kasvavan. Tämä voi tarjota mahdollisuuksia uusille palvelu-, t&k- tai tuotteistusliiketoiminnoille. Kuivilla maalijätteillä on myös hyvä lämpöarvo, jolloin energiahyötykäytön ja palamisjäännöksen materiaalihyötykäytön yhdistäminen mm. keramiikka- tai sementtiteollisuudessa voi tarjota mahdollisuuksia uusille liiketoiminnoille.

Country Risk and Market Reactions to Earnings Announcements: Evidence from Finnish Stock Markets

The objective of this thesis is to examine the market reaction around earnings announcements in Finnish stock markets. The aim is to find out whether the extreme market conditions during the financial crisis are reflected in stock prices as a stronger reaction. In addition to this, the purpose is to investigate how extensively Finnish listed companies report the country segmentation of revenues in their interim reports and whether the country risk is having a significant impact on perceived market reaction. The sample covers all companies listed in Helsinki stock exchange at 1.1.2010 and these companies’ interim reports from the first quarter of 2008 to last quarter of 2009. Final sample consists of 81 companies and 630 firm-quarter observations. The data sample has been divided in two parts, of which country risk sample contains 17 companies and 127 observations and comparison sample covers 66 companies and 503 observations. Research methodologies applied in this thesis are event study and cross-sectional regression analysis. Empirical results indicate that the market reaction occurs mainly during the announcement day and is slightly stronger in case of positive earnings surprises than the reactions observed in previous studies. In case of negative earnings surprises no significant differences can be observed. In case of country risk sample and negative earnings surprise market reaction is negative already in advance of the disclosure contrary to comparison sample. In case of positive surprise no differences can be observed. Country risk variable developed during this study seems to explain only minor part of the market reaction.

Regional potential for collaborative implementation of small CHP plants in bioenergy technology

This thesis is a preliminary study targeting South-Eastern Finland. The objective was to find out the financial and functional readiness and willingness of the small and medium-sized enterprises of the region to manufacture and sell distributed bioenergy solutions collaboratively as a business network. In this case these solutions mean small-scale (0.5 - 3 MW) woodchips-operated combined heat and power (CHP) plants. South-Eastern Finland has suffered from a decline in the recent years, mostly due to the problems of the traditionally strong industrial know-how area of the region, the paper industry. Local small and medium-sized companies will have to find new ways to survive the toughening competition. A group of 40 companies from suitable industries were selected and financial and comparative analysis was performed on them. Additionally 19 managing directors of the companies were selected for an interview to find out their views on networking, its requirements, advantages and the general interest in it. The studied companies were found to be generally in fairly good financial condition and in that sense, fit for networking activities. The interviews revealed that the companies were capable of producing all the needed elements for the plants in question, and the managers appeared to be very interested in and have a positive attitude towards such business networks. Thus it can be said that the small and medium-sized companies of the region are capable of and interested in manufacturing small bio-CHP plants as a production network.

Induction Motor Drive Energy Efficiency - Simulation and Analysis

A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.