Selecting a Flexible Manufacturing System Using Multiple Criteria Analysis

This paper describes a visually interactive decision support framework designed to aid the decision maker, typically top management, in selecting the most appropriate technology and design, when planning a flexible manufacturing system (FMS). The framework can be used in the pre-investment stage of the planning process, after the decision in principle has been made to build an FMS. First, both qualitative and quantitative criteria are used to narrow the set of alternative system configurations under consideration down to a small number of most attractive candidates. After this pre-screening phase, a multiobjective programming model is formulated for each remaining configuration, allowing the manager to explore and evaluate the costs and benefits of various different scenarios for each configuration separately by experimenting with different levels of batch sizes and production volumes. The system uses visual interaction with the decision maker, graphically displaying the relevant tradeoffs between such relevant performance criteria as investment and production costs, manufacturing flexibility, production volume and investment risk, for each scenario. Additional criteria, when relevant, can be included as well. The ease of use and interpretation and the flexibility make the proposed system a powerful analytical tool in the initial FMS design process. The insights gained from experimenting with the different scenarios form the basis of understanding the anticipated impact of techno-economic factors on the performance of the FMS configuration, and provide valuable information for the implementation stage of building the FMS. An example using real data from a case study in the Finnish metal product industry is provided to illustrate the methodology

A Nonlinear Multicriteria Model for Strategic FMS Selection Decisions

The strategic decision of selecting an optimal flexible manufacturing system (FMS) configuration is a complicated question which involves evaluating tradeoffs between a number of different, potentially conflicting criteria such as annual production volume, flexibility, production and investment costs, and average throughput of the system. Recently, several structured approaches have been proposed to aid management in the FMS selection process. While acknowledging the nonlinear nature of a number of the relationships in the model, notably between batch size and the number of batches produced of each part, these studies used linear simplifications to illustrate the decision dynamics of the problem. These linear models were shown to offer useful analytical tools in the FMS pre-design process. Due to the nonlinearities of the true relationships, however, the tradeoffs between the criteria could not fully be explored within the linear framework. This paper builds on the two-phase decision support framework proposed by Stam and Kuula (1989), and uses a modified nonlinear multicriteria formulation to solve the problem. The software used in the illustration can easily be implemented, is user-interactive and menu-driven. The methodology is applied to real data from a Finnish metal product company, and the results are compared with those obtained in previous studies

Transboundary Air Pollution in Europe: An Interactive Multicriteria Tradeoff Analysis

In this paper. the acid rain problem in Europe is discussed, stressing the transboundary tradeoffs between abatement costs of sulphur emission reduction and corresponding deposition levels in the different countries. An interactive decision support methodology is proposed which utilizes a powerful nonlinear multicriteria software package to evaluate various scenarios and tradeoffs. The concepts are illustrated using previously published data. The results from the tradeoff analysis show that reasonable deposition levels can be reached with limited transfers of funds between countries. The extent of these transfers can be controlled by selecting appropriate target levels for the criteria across countries

Korkeakouluopiskelijoiden selviytymisen tukeminen resilienssin vahvistamisen keinoin

Tiivistelmä. Tämän kandidaatin tutkielman tavoitteena on selvittää, kuinka korkeakouluopiskelijoiden selviytymistä voidaan tukea resilienssin vahvistamisen keinoin. Korkeakouluopiskelijoiden hyvinvoinnista on noussut huoli nopeiden koulu- ja työelämän muutosten ja kasvavien vaatimusten seurauksena sekä erityisesti viimeaikaisten maailman muutosten kuten pandemian ja sodan takia. Korkeakouluopiskelijoiden on todettu olevan kuormittuneempia muuhun väestöön verrattuna, joten resilienssin vahvistamisen tutkiminen juuri tällä ryhmällä on perusteltua. Tutkielma on toteutettu systemaattisena kirjallisuuskatsauksena, jonka avulla tarkastellaan aiempaa tutkimusta korkeakouluopiskelijoiden resilienssin vahvistamisesta. Tutkimusaineisto koostuu vertaisarvioiduista julkaisuista, joista 17 oli kansainvälisiä ja yksi kotimainen. Aineiston analyysi toteutettiin aineistolähtöisesti siitä esiin nousseiden teemojen mukaan. Tulokset osoittavat, että korkeakouluopiskelijoiden resilienssiä pystytään vahvistamaan monin eri tavoin. Esiin nousseet teemat tukivat resilienssin vahvistamista toiminnan kautta sekä tietojen ja taitojen opettamisen ja harjoittelun kautta. Lisäksi merkityksellisiä resilienssin vahvistamisen kannalta olivat perheeltä, ystäviltä ja koulun henkilökunnalta saatu sosiaalinen tuki sekä yliopiston tukipalvelut ja järjestelmät. Tulokset osoittivat myös sukupuolten välillä olevan eroja tekijöissä, jotka ovat resilienssin rakentumisen kannalta tärkeitä. Tutkimusten tuloksista ei voida kuitenkaan päätellä, ovatko tutkimusten resilienssiä kohentavat vaikutukset pysyviä, joten pitkittäis- ja seurantatutkimusta tarvittaisiin

Selecting a Flexible Manufacturing System using Multiple Criteria Analysis

A visual interactive decision support framework designed to aid the decision-maker, typically top management, in selecting the most appropriate technology and design when planning a flexible manufacturing system (FMS) is described. The framework can be used in the preinvestment stage of the planning process, after the decision in principle has been made to build an FMS. First, both qualitative and quantitative criteria are used to narrow the set of alternative system configurations under consideration down to a small number of most attractive candidates. After this prescreening phase, a multiobjective programming model is formulated for each remaining configuration, allowing the manager to explore and evaluate the costs and benefits of various different scenarios for each configuration separately by experimenting with different levels of batch sizes and production volumes. The system uses visual interaction with the decision-maker, graphically displaying the relevant trade-offs between such relevant performance criteria as investment and production costs, manufacturing flexibility, production volume and investment risk, for each scenario. Additional criteria, when relevant, can also be included. The ease of use and interpretation and the flexibility make the proposed system a powerful analytical tool in the initial FMS design process. The insights gained from experimenting with the different scenarios form the basis of understanding the anticipated impact of techno-economic factors on the performance of the FMS configuration, and provide valuable information for the implementation stage of building the FMS. An example using real data from a case study in the Finnish metal product industry is provided to illustrate the methodology

Transboundary Air Pollution in Europe: An Interactive Multicriteria Tradeoff Analysis

In this report, the acid rain problem in Europe is discussed, stressing the transboundary tradeoffs between abatement costs of sulphur emission reduction and corresponding deposition levels in the different countries. An interactive decision support methodology is proposed which utilizes a powerful nonlinear multicriteria software package to evaluate various scenarios and tradeoffs. This methodology provides a more appropriate tool for policy making than single-objective minimization of costs with given target deposition levels, because in the latter the tradeoffs cannot be analyzed directly. The results from a tradeoff analysis using previously published data suggest that reasonable deposition levels can be reached with limited transfers of funds between countries. The extent of these transfers can be controlled by selecting appropriate target levels for the criteria across countries

Business students' value priorities and attitudes towards sustainable development

Business students of today are future executives in companies and governments. Therefore, their education for sustainability needs to be carefully considered. However, very little is known about business students in terms of their value priorities and attitudes towards sustainable development. Value priorities guide attitudes, but they are more abstract and long-lasting. Teachers who understand their students' value priorities and attitudes could develop and customize their teaching accordingly. Our goal in this study is to measure business students' value priorities and their attitudes towards sustainability. We compare the results obtained from students in a university business school with a comparable nationwide sample. Our results show that there are differences in almost all values among business students and the comparable sample, in particular in universalism and power. Interestingly, attitudes to sustainable development are equally or even more favorable among business students. As a theoretical contribution in the field of education for sustainability we combined Sterling's three levels of sustainability education into our considerations and suggest that the evolvement of students' values and sustainability attitudes measured regularly should be reflected against them or a corresponding categorization. (C) 2020 The Authors. Published by Elsevier Ltd

Complexity Theory for a New Managerial Paradigm: A Research Framework

In this work, we supply a theoretical framework of how organizations can embed complexity management and sustainable development into their policies and actions. The proposed framework may lead to a new management paradigm, attempting to link the main concepts of complexity theory, change management, knowledge management, sustainable development, and cybernetics. We highlight how the processes of organizational change have occurred as a result of the move to adapt to the changes in the various global and international business environments and how this transformation has led to the shift toward the present innovation economy. We also point how organizational change needs to deal with sustainability, so that the change may be consistent with present needs, without compromising the future

Input-Adaptive Proxy for Black Carbon as a Virtual Sensor

Missing data has been a challenge in air quality measurement. In this study, we develop an input-adaptive proxy, which selects input variables of other air quality variables based on their correlation coefficients with the output variable. The proxy uses ordinary least squares regression model with robust optimization and limits the input variables to a maximum of three to avoid overfitting. The adaptive proxy learns from the data set and generates the best model evaluated by adjusted coefficient of determination (adjR2). In case of missing data in the input variables, the proposed adaptive proxy then uses the second-best model until all the missing data gaps are filled up. We estimated black carbon (BC) concentration by using the input-adaptive proxy in two sites in Helsinki, which respectively represent street canyon and urban background scenario, as a case study. Accumulation mode, traffic counts, nitrogen dioxide and lung deposited surface area are found as input variables in models with the top rank. In contrast to traditional proxy, which gives 20–80% of data, the input-adaptive proxy manages to give full continuous BC estimation. The newly developed adaptive proxy also gives generally accurate BC (street canyon: adjR2 = 0.86–0.94; urban background: adjR2 = 0.74–0.91) depending on different seasons and day of the week. Due to its flexibility and reliability, the adaptive proxy can be further extend to estimate other air quality parameters. It can also act as an air quality virtual sensor in support with on-site measurements in the future

Input-Adaptive Proxy for Black Carbon as a Virtual Sensor

Missing data has been a challenge in air quality measurement. In this study, we develop an input-adaptive proxy, which selects input variables of other air quality variables based on their correlation coefficients with the output variable. The proxy uses ordinary least squares regression model with robust optimization and limits the input variables to a maximum of three to avoid overfitting. The adaptive proxy learns from the data set and generates the best model evaluated by adjusted coefficient of determination (adjR2). In case of missing data in the input variables, the proposed adaptive proxy then uses the second-best model until all the missing data gaps are filled up. We estimated black carbon (BC) concentration by using the input-adaptive proxy in two sites in Helsinki, which respectively represent street canyon and urban background scenario, as a case study. Accumulation mode, traffic counts, nitrogen dioxide and lung deposited surface area are found as input variables in models with the top rank. In contrast to traditional proxy, which gives 20–80% of data, the input-adaptive proxy manages to give full continuous BC estimation. The newly developed adaptive proxy also gives generally accurate BC (street canyon: adjR2 = 0.86–0.94; urban background: adjR2 = 0.74–0.91) depending on different seasons and day of the week. Due to its flexibility and reliability, the adaptive proxy can be further extend to estimate other air quality parameters. It can also act as an air quality virtual sensor in support with on-site measurements in the future