A method for capturing customers’ preferences for housing customisation

The housebuilding sector has used mass production systems and reduced portfolios for many decades in different countries, countering the constant changes in society, resulting in neglecting the increasing diversity of customers’ requirements. Housebuilding companies should be able to meet this requirement’s diversity by offering a higher product variety and at the same time maintaining costs within market expectations. Mass customisation strategies have been presented as efficient alternatives to keep the balance between fulfilling clients’ specific needs and maintaining reasonable prices in housing by focusing on value generation. Moreover, there are limited ways of increasing value generation in housing considering its tradeoff with product cost, emphasising the need for the delimitation of a set of options (i.e.: solution space) adequate to customers’ preferences. Some research opportunities highlighted in the literature for adopting mass customisation in housing include solution space clear definition and the need for methods to explore the value perceived in product alternatives and reduce trade-offs between preferences and choice complexity. Accordingly, the main aim of this investigation is to propose a method for capturing customers’ preferencess and supporting customer integration in mass customisation strategies for housing. The design science approach was used as methodological underpinning for building the solution in this investigation. This thesis was structured in three academic papers. The first paper provides an overview of the available practices in house building and focuses on developing a framework of customer integration and core decision categories that support the definition of mass customisation strategies. In the second paper, a method for identifying customers’ preferences and support solution space definition was proposed, based on preference modelling and willingness-to-pay approaches regarding customer value and its balance with operations costs. In paper 3, another method is presented by adapting menu-based choice for housing and its implementation in an empirical study. The main contributions of this thesis include the method for capturing customers’ preferences, a framework of decision categories, and approaches for modelling customers willingness-to-pay for customised housing

decision theory criteria for the planning of distributed energy storage systems in the presence of uncertainties

This paper deals with the use of distributed energy storage systems in microgrids, and proposes a planning method which accounts for the uncertainties of load and distributed generation. Objectives of the planning method are the reduction of the energy costs, while providing the supply of ancillary services as a technical support to the network. The energy costs are evaluated considering a hourly varying pricing scheme and optimizing the storage systems charging/discharging stages. The technical support is devoted to the restraint of bus voltage amplitudes, and of network components' currents/powers within admissible ranges. The input data uncertainties are managed through three decision theory criteria (i.e., the minimization of expected costs; an approach based on the weighted regret felt by the design engineer; and a stability area criterion), which allow considering the multiple design alternatives and futures (i.e., possible values of uncertain input data) in an accurate and feasible way. The design alternatives refer to the size and location of the distributed storage systems, while each future is associated with a different level of load demand and power production of distributed generation over the whole planning period. The results of numerical applications are reported and discussed with reference to a Cigre test network

Impact and risk analysis in the integrated development of product and production system

The assessment of risks and influences of engineering changes of a product or production system on affected technical (sub-) systems of the same or a different domain are of great importance in order to evaluate possible alternatives and to select solutions. The increasing complexity of mechatronic products and production systems with Industry 4.0 technology reinforces the demand for a method that supports engineers in decision making in both technical and strategic issues. By using the method presented in this contribution, interdependencies between product functions, product features and the corresponding production processes and machines can be modelled and used to estimate the impact and risks of changes in one of those domains. Using the method, the change propagation of variations in and between the domains can be evaluated. The objective of the method is to support decision making in different use-cases like integrated product- and production system development, product variations while carrying over most of the production system or varying production processes while carrying over the product to improve production key performance indicators (KPI). Based on the model of PGE – Product Generation Engineering, the information of the reference system is used to identify the interdependencies. The inclusion of strategic factors like know-how and costs is implemented in the model, as well as the quantity and type of variations. The method consists of a representative model for a quick, holistic overview about the interdependencies and of a tool based model by using Model-Based Systems Engineering (MBSE) for an automatic connection and evaluation of the data. The contribution is part of the project I4TP - Sino German Industry 4.0 Factory Automation Platform (i4tp.org), in which a platform is developed to automatically configure a turnkey production system for a product in development

Towards natural language question generation for the validation of ontologies and mappings

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-view. However, the growing number of ontologies and their fast evolution over time make manual validation challenging. Methods: We propose a novel semi-automatic approach based on the generation of natural language (NL) questions to support the validation of ontologies and their evolution. The proposed approach includes the automatic generation, factorization and ordering of NL questions from medical ontologies. The final validation and correction is performed by submitting these questions to domain experts and automatically analyzing their feedback. We also propose a second approach for the validation of mappings impacted by ontology changes. The method exploits the context of the changes to propose correction alternatives presented as Multiple Choice Questions. Results: This research provides a question optimization strategy to maximize the validation of ontology entities with a reduced number of questions. We evaluate our approach for the validation of three medical ontologies. We also evaluate the feasibility and efficiency of our mappings validation approach in the context of ontology evolution. These experiments are performed with different versions of SNOMED-CT and ICD9. Conclusions: The obtained experimental results suggest the feasibility and adequacy of our approach to support the validation of interconnected and evolving ontologies. Results also suggest that taking into account RDFS and OWL entailment helps reducing the number of questions and validation time. The application of our approach to validate mapping evolution also shows the difficulty of adapting mapping evolution over time and highlights the importance of semi-automatic validation.The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-vi7115FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)2014/14890-

Can an ecological scarcity method for Germany support robust decisions? – analysing the effect of uncertain target values on the impact assessment of energy generation technologies

Purpose Potentially contradictory indicators in Life Cycle Assessment cause ambiguity and thus uncertainty regarding the interpretation of results. The weighting-based ecological scarcity method (ESM) aims at reducing interpretation uncertainty by applying policy-based normative target values. However, the definition of these target values is uncertain due to different reasons such as questionable temporal representativeness. By means of an uncertainty analysis, this paper examines if ESMs are an appropriate approach to support robust decisions on multidimensional environmental impacts. Methods To assess the effect of uncertain target values (inputs) on environmental indicators (output), the ESM based Life Cycle Impact Assessment (LCIA) is combined with a Monte Carlo Analysis. The comprehensive uncertainty analysis includes the following steps: (1) sample generation, (2) output calculation and (3) results analysis and visualisation. (1) To generate a sample, moderate and strict limits for target values are derived from laws, directives or strategies. Random input parameters are drawn from a uniform distribution within those limits. (2) The sample is used to conduct several LCIAs leading to a distribution of total impact scores. (3) The results’ robustness is evaluated by means of the rank acceptability index to identify stable ranks for energy generation systems taken from ecoinvent v. 3.7.1. Results and discussion Applying moderate and strict target values in the ESM, results in substantial differences in the weighting sets. Even though the application of stricter target values changes the contribution of an environmental indicator to the total impact score the ranking of the energy generation systems varies only slightly. Moreover, the Monte Carlo Analysis reveals that displacement effects in ranks are not arbitrary: systems switch at most between ranks next to each other and most of the analysed systems dominate at least a single rank. Technologies with high shares of land use, global warming and air pollutants and particulate matter show a higher rank variance. Conclusions The weighting schemes, deduced from target values, provide a meaningful ranking of alternatives. At the same time, the results are not excessively sensitive to the uncertainties of the target values, i.e. the inherent uncertainty of the target values does not result in arbitrary outcomes, which is necessary to support robust decisions. The ESM is able to effectively facilitate decision making by making different environmental issues comparable

Pilot3: A crew multi-criteria decision support tool – Estimating performance indicators and uncertainty for tactical trajectory management

During a flight, when a change in the operational conditions arises (e.g., new updated weather forecast, delay at reaching a given waypoint), different alternative trajectories can be computed with dedicated optimisation or prediction systems. These systems usually produce trajectories with trade-offs between expected fuel usage and delay. The pilot, or the dispatcher, considers these expected values in order to decide how to tactically operate the aircraft. This approach has two main challenges. Firstly, it requires the translation of arrival delay into parameters which are relevant for the airlines, such as on-time performance and cost of delay. Secondly, uncertainties in the system need to be estimated, such as holding time at arrival, or taxi-in time. Both of these estimations (airlines performance indicators and uncertainty) rely on the airline staff expertise. Finally, the crew faces a multi-criteria decision process as different objectives (cost, on-time performance) and constraints need to be considered. The use of prior to the flight estimations, such as the cost index of the operational flight plan, might not be relevant at the moment of reassessing the flight, as the situation has evolved (for example, the number of passengers who can potentially miss their connections will depend on the status of the fleet of the airline). In other cases, this expected cost of delay could be estimated by the crew or the dispatchers, but generally it is difficult to internalise the dynamics of cost due to IROPS on passengers, or even to estimate the cost of a potential curfew at the end of the day. Uncertainties such as the expected holding delay, distance flown at the arrival TMA, or taxi-in time, might lead to sub-optimal decisions, such as recovering delay, using extra fuel, which does not translate into economic benefit, as larger holding than anticipated might lead to passengers still missing their connection; or shorter distances flown in the TMA means that speed-ups performed during the cruise were unnecessary. Pilot3, a Clean Sky 2 Research and Innovation action, sets out to overcome these issues by developing a multi-criteria support decision tool, which combines explicit estimation of key performance indicators and estimation of ATM operational parameters. These estimators will be developed incrementally, from simple heuristics to machine learning models. Pilot3 prototype comprises five sub-systems: * An Alternatives Generator, which will compute the different alternatives to be considered by the pilot; fed by two independent sub-systems: * Performance Indicators Estimator, which provides the Alternatives Generator with information on how to estimate the impact of each solution for the different performance indicators; * Operational ATM Estimator, which provides the Alternative Generator with information on how to estimate some operational aspects such as tactical route amendments, expected arrival procedure, holding time in terminal airspace, distance flown (or flight time spent) in terminal airspace due to arrival sequencing and merging operations, or taxi-in time; * Performance Assessment Module, which, considering the expected results for each alternative on the different KPIs, is able to filter and rank the alternatives considering airlines and pilots preferences; and * Human Machine Interface, which will present these alternatives to the pilot and allow them to interact with the system. Pilot3 is led by the University of Westminster with the Universitat Politecnica de Catalunya, Innaxis and PACE Aerospace Engineering and Information Technology as partners. The Topic Manager is Thales AVS France SAS. With support from the Advisory Board, Pilot3 has already identified the key operational performance indicators that crew should consider when tactically adjusting their trajectories (on-time performance and total cost, including fuel, IROPs and others); and a literature review and filtering process on multi-criteria decision making techniques has been conducted to select the most suitable method for the different phases of the optimisation process (trajectory generation, filtering and ranking of alternatives)

Enhancing geographical information systems capabilities with multi-criteria evaluation functions

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Sustainability Assessment of Community Scale Integrated Energy Systems: Conceptual Framework and Applications

abstract: One of the key infrastructures of any community or facility is the energy system which consists of utility power plants, distributed generation technologies, and building heating and cooling systems. In general, there are two dimensions to “sustainability” as it applies to an engineered system. It needs to be designed, operated, and managed such that its environmental impacts and costs are minimal (energy efficient design and operation), and also be designed and configured in a way that it is resilient in confronting disruptions posed by natural, manmade, or random events. In this regard, development of quantitative sustainability metrics in support of decision-making relevant to design, future growth planning, and day-to-day operation of such systems would be of great value. In this study, a pragmatic performance-based sustainability assessment framework and quantitative indices are developed towards this end whereby sustainability goals and concepts can be translated and integrated into engineering practices. New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components. Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance. A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Facilitating meta-design techniques for multi-disciplinary conceptual design

The research reported in this paper was supported by the EU FP6 funded project, SimSAC (Simulating Aircraft Stability and Control Characteristics for Use in Conceptual Design)