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Decision-making is part of everyday life. In theory, making a decision consists in assessing all the choices, their outcomes, and sometimes their probability of occurrence and then making the best choice according to the decision maker's preferences. For instance, should employees commute by bus or by car? If they take the bus, they will depend on the location of the bus stop and bus schedule and may arrive late at work if the bus is delayed. However, this option is more environmentally friendly. On the other side, the car offers more flexibility but is less environmentally friendly. According to whether they are concerned with the environment or flexibility, they will prefer one option to the other. However, in reality, decision-making is more complex. Indeed, making choices in the real world implies considering uncertainties during the decision process. In addition, more than one person is involved in the decision-making process which makes the final decision more complicated to make as each person has different preferences. Companies such as Safran Aero Boosters (SAB), an engineering company specialising in aerospace parts such as boosters, are affected by the latter type of decision-making process. 

This thesis identifies and models the decision-making problem within research and development in the (new) technologies department of the SAB company. To model this problem, a decision support tool, called Crystal Ball Decision Tool is proposed. Developed in Microsoft Excel and with the Palisade DecisionSuite Tools add-ins, Crystal Ball Decision Tool makes use of Monte Carlo simulation to handle uncertainties and Multi-Criteria Decision-Making methods to satisfy the different person's preferences within the decision-making process. This tool can support SAB employees in their decision-making by analysing technologies and comparing several technologies/projects, among which prioritisation must be made. In addition, Crystal Ball Decision Too allows centralising the decision-making process in one single tool. 

The decision support tool's abilities to analyse and compare technologies are then tested on three real SAB projects. Although improvements can be made to this very first version of the tool within the SAB company, the results are encouraging and show that the Crystal Ball Decision Tool fulfils its duty to assist in decision-making.

Decision support tool, Multi-criteria decision-making, Uncertainty, Risk --- Sciences économiques & de gestion > Finance --- Ingénierie, informatique & technologie > Sciences informatiques --- Sciences économiques & de gestion > Stratégie & innovation

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The focus of this reprint is on environmental planning and modeling. It examines articles on green consumption, biodiversity, and household waste recycling, as well as presenting a review of the trend in publications on household waste recycling. A number of country-based applications are presented and models are used to show how multiple perspectives can be considered in policy making. This reprint will be of special interest to researchers and readers involved in sustainability management. Further, although some chapters present models to solve sustainability problems, they also share policy and decision-making frameworks for applying such models.

bibliometric analysis --- bibliometrix --- household recycling --- research trends --- science mapping --- waste management --- analytic hierarchy process (AHP) --- ecosystem management --- expert opinion --- environmental planning and modeling --- rights-based tool --- multi-criteria decision making --- optimisation --- sustainability --- SWAT model --- water quality --- hydrology --- fertilizer application --- Songkhla Lake Basin --- green consumption --- environmental change --- environmental regulation --- social welfare --- APEX --- open-source software --- QGIS --- QAPEX --- best management practice --- LDC --- n/a

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This Special Issue addresses the important issue of the energy efficiency of both manufacturing processes and systems. Manufacturing is responsible for one-third of global energy consumption and CO2 emissions. Thus, improving the energy efficiency of production has been the focus of research in recent years. Energy efficiency has begun to be considered as one of the key decision-making attributes for manufacturing. This book includes recent studies on methods for the measurement of energy efficiency, tools and techniques for the analysis and development of improvements with regards to energy consumption, modeling and simulation of energy efficiency, and the integration of green and lean manufacturing. This book presents a breadth of relevant information, material, and knowledge to support research, policy-making, practices, and experience transferability to address the issues of energy efficiency.

History of engineering & technology --- energy consumption --- scheduling approach --- mixed-flow shop --- multi-objective optimisation --- tardiness fine --- energy efficiency --- sustainable machining --- multi-objective optimization --- multi-criteria decision making method --- small quantity cooling lubrication SQCL --- cu nanofluid --- remote laser welding --- energy-efficient process --- machine learning --- welding process --- neural network --- knowledge representation --- fuzzy reasoning Petri net --- energy efficient operation --- manufacturing system --- Manufacturing --- life-cycle assessment --- aluminum --- cast iron --- pulp --- paper --- structural change --- compressed air systems --- energy data analysis --- energy measures --- performance control --- operations --- maintenance --- energy accounting --- laser drilling --- percussion --- trepanning --- productivity --- cost --- material removal rate (MRR) --- specific energy consumption (SEC) --- Taguchi --- hole taper --- IN 718 --- electric discharge machining --- response surface methodology --- sustainability --- surface quality --- microstructure --- multi-criteria decision making --- process planning --- manufacturing energy efficiency --- clean manufacturing --- sustainable manufacturing --- digital manufacturing --- energy consumption --- scheduling approach --- mixed-flow shop --- multi-objective optimisation --- tardiness fine --- energy efficiency --- sustainable machining --- multi-objective optimization --- multi-criteria decision making method --- small quantity cooling lubrication SQCL --- cu nanofluid --- remote laser welding --- energy-efficient process --- machine learning --- welding process --- neural network --- knowledge representation --- fuzzy reasoning Petri net --- energy efficient operation --- manufacturing system --- Manufacturing --- life-cycle assessment --- aluminum --- cast iron --- pulp --- paper --- structural change --- compressed air systems --- energy data analysis --- energy measures --- performance control --- operations --- maintenance --- energy accounting --- laser drilling --- percussion --- trepanning --- productivity --- cost --- material removal rate (MRR) --- specific energy consumption (SEC) --- Taguchi --- hole taper --- IN 718 --- electric discharge machining --- response surface methodology --- sustainability --- surface quality --- microstructure --- multi-criteria decision making --- process planning --- manufacturing energy efficiency --- clean manufacturing --- sustainable manufacturing --- digital manufacturing

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This Special Issue addresses the important issue of the energy efficiency of both manufacturing processes and systems. Manufacturing is responsible for one-third of global energy consumption and CO2 emissions. Thus, improving the energy efficiency of production has been the focus of research in recent years. Energy efficiency has begun to be considered as one of the key decision-making attributes for manufacturing. This book includes recent studies on methods for the measurement of energy efficiency, tools and techniques for the analysis and development of improvements with regards to energy consumption, modeling and simulation of energy efficiency, and the integration of green and lean manufacturing. This book presents a breadth of relevant information, material, and knowledge to support research, policy-making, practices, and experience transferability to address the issues of energy efficiency.

History of engineering & technology --- energy consumption --- scheduling approach --- mixed-flow shop --- multi-objective optimisation --- tardiness fine --- energy efficiency --- sustainable machining --- multi-objective optimization --- multi-criteria decision making method --- small quantity cooling lubrication SQCL --- cu nanofluid --- remote laser welding --- energy-efficient process --- machine learning --- welding process --- neural network --- knowledge representation --- fuzzy reasoning Petri net --- energy efficient operation --- manufacturing system --- Manufacturing --- life-cycle assessment --- aluminum --- cast iron --- pulp --- paper --- structural change --- compressed air systems --- energy data analysis --- energy measures --- performance control --- operations --- maintenance --- energy accounting --- laser drilling --- percussion --- trepanning --- productivity --- cost --- material removal rate (MRR) --- specific energy consumption (SEC) --- Taguchi --- hole taper --- IN 718 --- electric discharge machining --- response surface methodology --- sustainability --- surface quality --- microstructure --- multi-criteria decision making --- process planning --- manufacturing energy efficiency --- clean manufacturing --- sustainable manufacturing --- digital manufacturing

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Efficiency and productivity assessment are essential to ensure the long-term financial sustainability of countries, services and processes. In the last few years, there has been an increasing interest in the environmental effects of economic activities, and the need to assess the environmental and energy efficiency has been internationally recognized. Energy and environmental efficiency assessments of decision-making units (DMUs), such as countries, utilities, processes and services are relevant and have strong implications for companies, regulators, stakeholders, policy makers, and customers. To improve both the decision-making process and the management of DMUs, fundamental and practical knowledge about energy and environmental efficiency and productivity is essential

Research & information: general --- electricity consumption (EC) --- undesirable outputs model --- data envelopment analysis (DEA) --- efficient --- inefficient --- data envelopment analysis --- energy efficiency --- performance --- bootstrap --- water treatment --- composite indicator --- sustainability --- water utilities management --- multi-criteria decision making (MCDM) --- evaluation --- energy --- environment --- efficiency --- transport --- DEA --- TOPSIS --- transit-oriented development (TOD) --- transit efficiency --- smartcard data --- network slacks-based measure data envelopment analysis (NSBM DEA) --- electricity consumption (EC) --- undesirable outputs model --- data envelopment analysis (DEA) --- efficient --- inefficient --- data envelopment analysis --- energy efficiency --- performance --- bootstrap --- water treatment --- composite indicator --- sustainability --- water utilities management --- multi-criteria decision making (MCDM) --- evaluation --- energy --- environment --- efficiency --- transport --- DEA --- TOPSIS --- transit-oriented development (TOD) --- transit efficiency --- smartcard data --- network slacks-based measure data envelopment analysis (NSBM DEA)