PDM system functions and utilizations analysis to improve efficiency of sheet metal product design and manufacturing

This study will concentrate on Product Data Management (PDM) systems, and sheet metal design features and classification. In this thesis, PDM is seen as an individual system which handles all product-related data and information. The meaning of relevant data is to take the manufacturing process further with fewer errors. The features of sheet metals are giving more information and value to the designed models. The possibility of implementing PDM and sheet metal features recognition are the core of this study. Their integration should make the design process faster and manufacturing-friendly products easier to design. The triangulation method is the basis for this research. The sections of this triangle are: scientific literature review, interview using the Delphi method and the author’s experience and observations. The main key findings of this study are: (1) the area of focus in triangle (the triangle of three different point of views: business, information exchange and technical) depends on the person’s background and their role in the company, (2) the classification in the PDM system (and also in the CAD system) should be done using the materials, tools and machines that are in use in the company and (3) the design process has to be more effective because of the increase of industrial production, sheet metal blank production and the designer’s time spent on actual design and (4) because Design For Manufacture (DFM) integration can be done with CAD-programs, DFM integration with the PDM system should also be possible.

Energy saving potential in reservoir pumping

Pumping systems account for up to 22 % of the energy consumed by electrical motors in European industry. Many studies have shown that there is also a lot of potential for energy savings in these systems with the improvement of devices, flow control or surrounding sys-tem. The best method for more energy efficient pumping has to be found for each system separately. This thesis studies how energy saving potential in reservoir pumping system is affected by surrounding variables, such as the static head variation and friction factor. The objective is to create generally applicable graphs to quickly compare methods for reducing pumping system’s energy costs. The gained results are several graphs showcasing how the chosen variables affect energy saving potential of the pumping system in one specific case. To judge if these graphs are generally applicable, more testing with different pumps and environments are required.

Centralized IT management using SCCM in a large multinational company

Microsoft System Center Configuration Manager is a systems management product for managing large groups of computers and/or mobile devices. It provides operating system deployment, software distribution, patch management, hardware & software inventory, remote control and many other features for the managed clients. This thesis focuses on researching whether this product is suitable for large, international organization with no previous, centralized solution for managing all such networked devices and detecting areas, where the system can be altered to achieve a more optimal management product from the company’s perspective. The results showed that the system is suitable for such organization if properly configured and clear and transparent line of communication between key IT personnel exists.

Kaksifaasijäähdytysjärjestelmään liittyvien pumppujen vertailu ja kehittäminen sarjatuotannon tarpeisiin

Tehoelektroniikalta vaaditaan nykyään parempaa suorituskykyä entistä pienemmässä tilassa. Tämä luo haasteen riittävälle jäähdytykselle. Eräs ratkaisu on käyttää kaksifaasijäähdytystä, jolla aikaansaadaan tehokas lämmönsiirto komponenttien pinnalta. Lämmönsiirtonesteinä voidaan käyttää kylmäaineita tai muita alhaisessa lämpötilassa kiehuvia nesteitä. Tällaisille nesteille on tyypillistä alhainen höyrynpaine sekä matala viskositeetti. Nämä ominaisuudet tuovat haasteita nesteen pumppaukseen. Tässä työssä tarkastellaan R-134A:ta sekä Novec 7000:ta, perehdytään niiden fysikaalisiin ominaisuuksiin sekä materiaaliyhteensopivuuksiin ja näiden tietojen pohjalta etsitään sopivaa pumpputyyppiä kaksifaasijäähdytysjärjestelmään. Tehoelektroniikan jäähdytysjärjestelmän pumpun on oltava edullinen muuhun järjestelmään nähden. Tyypillinen kiertopumppu nestejäähdytysjärjestelmässä on pieni keskipakopumppu. Alhaisen kiehumispisteen vuoksi kavitointiriski kasvaa ja tämä voi vahingoittaa pumppua. Myös matala viskositeetti tuo haasteita vuotoherkkyyden kasvamisen myötä, joten mekaanisilla aksiaalitiivisteillä varustetut pumput eivät ole pitkäikäisiä. Kylmäainejärjestelmiin tarkoitetut pumput ovat arvokkaita, eikä näin ollen sovellu edullisiin jäähdytysjärjestelmiin. Tässä työssä käydään läpi erilaisia pumpputyyppejä, jotka voisivat soveltua pitkäikäiseen pumppaukseen ilman huoltotöitä. Näiden tietojen perusteella kehitetään edullista ja pitkäikäistä pumppua pieniin kaksifaasijäähdytysjärjestelmiin nesteiden fysikaaliset ominaisuudet huomioon ottaen. Kehitetyn pumpun ominaisuuksia ja kustannuksia vertaillaan kaupallisiin ratkaisuihin ottaen huomioon sarjavalmistus. Itse valmistettuna pienelle sisäryntöiselle hammaspyöräpumpulle jää hintaa alle kymmenesosa markkinoilta löytyviin kylmäaineille soveltuviin pumppuun.

Design, implementation, and evaluation of an online water quality monitoring system in Lake Saimaa, Finland

Environmental threats are growing nowadays, they became global issues. People around the world try to face these issues by two means: solving the current affected environs and preventing non-affected environs. This thesis describes the design, implementation, and evaluation of online water quality monitoring system in Lake Saimaa, Finland. The water quality in Lake Saimaa needs to be monitored in order to provide responsible bodies with valuable information which allows them to act fast in order to prevent any negative impact on the lake's environment. The objectives were to design a suitable system, implement the system in Lake Saimaa, and then to evaluate the applicability and reliability of such systems for this environment. The needs for the system were first isolated, and then the design, needed modifications, and the construction of the system took place. After that was the testing of the system in Lake Saimaa in two locations nearby Mikkeli city. The last step was to evaluate the whole system. The main results were that the application of online water quality monitoring systems in Lake Saimaa can benefit of many advantages such as reducing the required manpower, time and running costs. However, the point of unreliability of the exact measured values of some parameters is still the drawback of such systems which can be developed by using more advanced equipments with more sophisticated features specifically for the purpose of monitoring in the predefined location.

Novel virtual environment and real-time simulation based methods for improving life-cycle efficiency of non-road mobile machinery

Virtual environments and real-time simulators (VERS) are becoming more and more important tools in research and development (R&D) process of non-road mobile machinery (NRMM). The virtual prototyping techniques enable faster and more cost-efficient development of machines compared to use of real life prototypes. High energy efficiency has become an important topic in the world of NRMM because of environmental and economic demands. The objective of this thesis is to develop VERS based methods for research and development of NRMM. A process using VERS for assessing effects of human operators on the life-cycle efficiency of NRMM was developed. Human in the loop simulations are ran using an underground mining loader to study the developed process. The simulations were ran in the virtual environment of the Laboratory of Intelligent Machines of Lappeenranta University of Technology. A physically adequate real-time simulation model of NRMM was shown to be reliable and cost effective in testing of hardware components by the means of hardware-in-the-loop (HIL) simulations. A control interface connecting integrated electro-hydraulic energy converter (IEHEC) with virtual simulation model of log crane was developed. IEHEC consists of a hydraulic pump-motor and an integrated electrical permanent magnet synchronous motorgenerator. The results show that state of the art real-time NRMM simulators are capable to solve factors related to energy consumption and productivity of the NRMM. A significant variation between the test drivers is found. The results show that VERS can be used for assessing human effects on the life-cycle efficiency of NRMM. HIL simulation responses compared to that achieved with conventional simulation method demonstrate the advances and drawbacks of various possible interfaces between the simulator and hardware part of the system under study. Novel ideas for arranging the interface are successfully tested and compared with the more traditional one. The proposed process for assessing the effects of operators on the life-cycle efficiency will be applied for wider group of operators in the future. Driving styles of the operators can be analysed statistically from sufficient large result data. The statistical analysis can find the most life-cycle efficient driving style for the specific environment and machinery. The proposed control interface for HIL simulation need to be further studied. The robustness and the adaptation of the interface in different situations must be verified. The future work will also include studying the suitability of the IEHEC for different working machines using the proposed HIL simulation method.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.

Motor Types Comparison Determining Efficiency in Pumping Systems

Pumping, fan and compressor systems consume most of the motor electricity power in both the industrial and services sectors. A variable speed drive brings relevant improvements in a fluid system leading to energy saving that further on can be translated into Mtons reduction of CO 2 emissions. Standards and regulations are being adopted for fluid handling systems to limit the less efficiency pumps out of the European market on the coming years and a greater potential in energy savings is dictated by the Energy Efficiency Index (EEI) requirements for the whole pumping system and integrated pumps. Electric motors also have an International Efficiency (IE) classification in order to introduce higher efficiency motors into the market. In this thesis, the applicability of mid-size common electric motor types to industrial pumping system took place comparing the motor efficiency characteristics with each other and by analyzing the effect of motor dimensioning on the pumping system and its impact in the energy consumption.

Modelling the exothermic heat and the demand of cooling in paper and pulp industry biological wastewater treatment

This master thesis presents a study on the requisite cooling of an activated sludge process in paper and pulp industry. The energy consumption of paper and pulp industry and it’s wastewater treatment plant in particular is relatively high. It is therefore useful to understand the wastewater treatment process of such industries. The activated sludge process is a biological mechanism which degrades carbonaceous compounds that are present in waste. The modified activated sludge model constructed here aims to imitate the bio-kinetics of an activated sludge process. However, due to the complicated non-linear behavior of the biological process, modelling this system is laborious and intriguing. We attempt to find a system solution first using steady-state modelling of Activated Sludge Model number 1 (ASM1), approached by Euler’s method and an ordinary differential equation solver. Furthermore, an enthalpy study of paper and pulp industry’s vital pollutants was carried out and applied to revise the temperature shift over a period of time to formulate the operation of cooling water. This finding will lead to a forecast of the plant process execution in a cost-effective manner and management of effluent efficiency. The final stage of the thesis was achieved by optimizing the steady state of ASM1.