Simulating the implementation of technological innovations in construction

Introducing new technologies or innovative processes can enhance construction efficiency and enable organisations to achieve objectives of lowering costs, continuous improvement and competitive advantage. New ideas have to show significant benefits before they are accepted. Despite of the differences between the construction and manufacturing industries, opportunities are still available to leam from manufacturing approaches to innovation. A fundamental challenge facing construction innovation is the way that construction organisations plan and control the implementation of innovation where many projects do not fulfil their time and cost objectives. Management should not only improve techniques for planning and scheduling but also allow managers to assess and simulate the anticipated performance resulting from innovation .. According to this assessment, managers would be more able and perhaps more ready to accept new processes/products or iterate the implementation process until a satisfactory level of performance has been achieved. Intangible benefits offered by advanced construction technologies are hard to quantify using traditional economic analysis techniques. This could result in the rejection of a potentially profitable idea. Benefits to be gained from improvements in operational efficiency are measured by cost and time-savings and increasing productivity. These benefits, in addition to intangible benefits, need to be measured and quantified. Simulating the implementation process of innovation has not been addressed, although many models have been developed to describe the innovation process in construction which considered implementation as a sequential process incorporating iterations. [Continues.

DESIGN PROCESS MODELING: TOWARDS AN ONTOLOGY OF ENGINEERING DESIGN ACTIVITIES

An ontology of engineering design activities, called the Design Activity Ontology (DAO), is developed in this research. The DAO models 82 information flows and 25 design activities. These activities cover phases of the design process from conceptual phase through detail design phase. The ontology provides a formalized and structured vocabulary of design activities for consistency and exchange of design process models. The DAO enables design processes to be modeled, analyzed and optimized. The DAO is constructed using information flows identified in current design literature, commonly accepted engineering design textbooks, and an existing activity ontology. Specifically, the DAO is an extension and refinement of the ontology proposed by Sim and Duffy. The DAO addresses several shortcomings of the Sim and Duffy ontology including: (1) lack of computational representation, (2) inability to construct process models from defined design activities, (3) redundant and semantically equivalent information flows, (4) complex information flows, and (5) inconsistent classification. These shortcomings are identified through Design Structure Matrix (DSM) modeling and analysis, and certain protocols for the analysis of the individual information flows. A total of 112 information flows and 26 activities from the Sim and Duffy ontology are reduced to 82 and 25 respectively. The DAO is implemented in the ProtŽgŽ using the Web Ontology Language (OWL) and Description Logic (DL). The implemented DAO is analyzed using DL\u27s subsumption property through the Fact++ reasoner. Finally, the DAO is exercised through two demonstration examples: (1) the design of a trash truck and (2) the design of an automotive tail light installation fixture. Results from the example support the completeness of the ontology; ability to formulate design processes; and identify \u27dead-end\u27 information flows, information flows required in design but not generated and critical information flows

Integrated automotive exhaust engineering : uncertainty management

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2006.Includes bibliographical references (p. 104-108).The global automotive industry has entered a stagnating period. Automotive OEMs and their tier suppliers are struggling for business growth. One of the most important strategies is to improve the engineering efficiency in the product development process. The engineering uncertainties have been identified as the main obstacles in the Lean Engineering practices. This study will be focused on the engineering development process of ArvinMeritor Emission Technologies. The lean engineering principles and techniques are applied to the current product development process. The Value Stream Mapping and Analysis method is used to identify the information flow inside the current engineering process. Based on the value stream map, the uncertainties at various development stages in the process are identified. The Design Structure Matrix is used to identify any unplanned design iteration, which results in lower engineering efficiency. The House of Quality is used to prioritize the importance of the iterations. The suggested excel program can effectively evaluate the effect of task duration, probability, impact and learning curve assumption.(cont.) In order to quantitatively predict the effects of the uncertainties, a System Dynamic model is specifically developed for the current engineering of Emission Technologies. The results clearly indicate the control factors for on-time delivery, efficient resource allocation, and cost reduction. This study has integrated the techniques from system engineering, system project management, and system dynamics. An improved automotive exhaust engineering process is proposed.by Xitian Fang and Deming Wan.S.M

WORKING AGILE TO SPEED UP RESEARCH WITH INDUSTRY: FIVE INDEPENDENCE PRINCIPLES

One of the obstacles to the ability of research to make an impact on industry resides on the research process itself. Today, there is a need to accelerate the means for research to support industrial transformation. At the same time, there is the need to maintain scientific rigorousness, which often requires time. To solve this trade-off, this paper evaluates existing research approaches through the lenses of agile development. The analysis is based on a simulation of research process architectures, and on observations made over several research projects with industry. The results of this analysis highlight five light-but-sufficient rules of research project behavior to keep momentum, motivation and trust when doing research with industry. The paper demonstrates the use of these five rules in a research sprint conducted iwith two automotive OEMs

Model-based approaches to support process improvement in complex product development

The performance of product development processes is important to the commercial success of new products. The improvement of these processes is thus a strategic imperative for many engineering companies — the aero-engine is one example of a complex product for which market pressures necessitate ever-shorter development times. This thesis argues that process modelling and simulation can support the improvement of complex product development processes. A literature review identified that design process modelling is a well-established research area encompassing a diverse range of approaches. However, most existing tools and methods are not widely applied in industry. An extended case study was therefore conducted to explore the pragmatic utility of process modelling and simulation. It is argued that iteration is a key driver of design process behaviour which cannot be fully reflected in a mechanistic model. Understanding iteration can help select an appropriate representation for a given process domain and modelling objective. A model-based approach to improve the management of iterative design processes was developed. This approach shows that design process simulation models can support practice despite their limited fidelity. The modelling and simulation framework resulting from this work was enhanced for application to a wider range of process improvement activities. A robust and extensible software platform was also developed. The framework and software tool have made significant contribution to research projects investigating process redesign, process robustness and process optimisation. These projects are discussed to validate the framework and tool and to highlight their applicability beyond the original approach. The research results were disseminated in academia and industry — 72 copies of the software were distributed following requests in the first three months of its release

New actor types in electricity market simulation models: Deliverable D4.4

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: The modelling of agents in the simulation models and tools is of primary importance if the quality and the validity of the simulation outcomes are at stake. This is the first version of the report that deals with the representation of electricity market actors’ in the agent based models (ABMs) used in TradeRES project. With the AMIRIS, the EMLab-Generation (EMLab), the MASCEM and the RESTrade models being in the centre of the analysis, the subject matter of this report has been the identification of the actors’ characteristics that are already covered by the initial (with respect to the project) version of the models and the presentation of the foreseen modelling enhancements. For serving these goals, agent attributes and representation methods, as found in the literature of agent-driven models, are considered initially. The detailed review of such aspects offers the necessary background and supports the formation of a context that facilitates the mapping of actors’ characteristics to agent modelling approaches. Emphasis is given in several approaches and technics found in the literature for the development of a broader environment, on which part of the later analysis is deployed. Although the ABMs that are used in the project constitute an important part of the literature, they have not been included in the review since they are the subject of another section.N/

Designing out waste in high-rise residential buildings: analysis of precasting and methods and traditional construction

The Construction industry is a major generator of waste material. Construction waste should be minimized at source. If we are to significantly reduce the level of construction waste designers should consider reducing construction waste during the design process. The majority of construction waste is generated from the concreting process. In general, any reduction in on-site concreting leads to waste reduction. Precasting and prefabrication therefore offers significant opportunities for the reduction of waste. If precasting is adopted there are significant implications for the design phase of the project. Additional information is needed by design staff, construction expertise is required as part of the design process. This paper shows how information modeling and Design Structure Matrix, (DSM), techniques enable designers to model and understand the implications of such decisions within the detailed design process

A Flow Model for Contract Car Manufacturing Project

This study is about contract car manufacturing (CCM) projects in a case company. The aimis to find out if it is possible to create a flow model that will fit to these projects in generaland that could support the flowing execution of the project. The target is expressed in thehypothesis of this study: It is possible to create a common flow model for a CCM projectand that can be applied to different project cases in the same context.The research is based on three literature domains, Design Science, Project Management, andSystems Thinking. They all are present in complex engineering projects execution but haveseldom been considered together in previous research.The model creation is based on the analysis of four CCM projects that have been worked outduring the past years in the case company. The main analysis is based on one project and theother three projects are thereafter compared to the results of the analysis. In the analysis ofthese projects the focus has been on the project flow with the aim of finding out what kind ofobstacles there are that prevent the project from proceeding according to the plannedschedule.The project analysis is based on four research questions. The first one aims to name the subproject areas, which build up the CCM project content. It will serve as a framework indeveloping the flow model. The sub-projects form the needed transformation process wherethe new car model can be manufactured in serial production. The three other researchquestions want to find out what kind of obstacles there are that prevent the project fromflowing and what kind of action support the flow mode during the project execution. Theissues that keep the project from flowing are connected to the important interdependencies. They are often on the external stakeholder’s responsibility and are not as easy to control asthe ones that are in own hands. This study analyses the interdependencies between projectdeliverables and points out the most important ones that have the largest amount ofinterdependencies with other deliverables. The most important ones have two features, theyhave a large amount of interdependencies and they need an output from external stakeholder. When the project management is well aware of the schedule risks and is proactivelyprepared to them this can support the project flow. The activities that produce the riskydeliverables should be described and planned in detail so that it is possible to control theproceeding step by step if the risk actualises.The analysis of the four case projects showed that a general flow model for CCM projects isplausible and can be implemented in all projects. Furthermore, this modelling principle canbe adapted to other kinds of projects as well. The deliverables only need to be formedaccordingly

Consumer behavior modeling for electrical energy systems : a complex systems approach

Orientador: Alexandre Rasi AokiCoorientador: Germano Lambert-TorresTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 27/02/2019Inclui referências: p. 141-154Resumo: Um sistema complexo é um sistema composto de muitas partes que interagem entre si, de modo que o comportamento coletivo emergente dessas partes é mais do que a soma de seus comportamentos individuais. O sistema elétrico de potência pode ser considerado um sistema complexo devido à sua diversidade de agentes heterogêneos inter-relacionados e a emergência de comportamento complexo. Sistemas de potência estão aumentando em complexidade com novos avanços relacionados à redes elétricas inteligentes tais como tecnologia de informação e comunicação, geração distribuída, veículos elétricos, armazenamento de energia e, especialmente, uma crescente interação e participação de um grande número de consumidores heterogêneos dispersos geograficamente. O sistema elétrico de potência pode ser estudado como um sistema técnico-socioeconômico complexo com múltiplas facetas, e a teoria de sistemas complexos pode fornecer uma base teórica sólida para seus desafios de modelagem e análise. O presente trabalho trata da aplicação da teoria de sistemas complexos em sistemas de potência, focando a análise no consumidor e no seu comportamento relacionado ao consumo de eletricidade, utilizando técnicas do campo da economia comportamental. Comportamentos complexos e emergentes sobre o consumo de eletricidade, bem como seu impacto nas redes elétricas, são analisados através da modelagem do comportamento dos cliente em uma simulação baseada em agentes, considerando quatro categorias de consumidores. A análise da simulação, aplicada a um estudo de caso em uma rede de distribuição de média tensão radial com dados reais, mostrou que premissas ligeiramente diferentes sobre o comportamento do consumidor no nível micro levam a resultados macro muito distintos e com comportamento não linear. Entender e modelar adequadamente o comportamento dos consumidores é de grande importância para o planejamento e operação de redes de energia, e a economia comportamental serve como uma base teórica promissora para modelar o comportamento no consumo de eletricidade. Os resultados deste trabalho mostraram que a teorias de sistemas complexos fornece ferramentas adequadas para lidar com sistemas de potência cada vez mais complexos, considerando-os não mais como um sistema independente agregado, mas como um sistema complexo integrado. Palavras-chave: distribuição de energia; consumo de eletricidade; teoria de sistemas complexos; simulação baseada em agentes; economia comportamental.Abstract: A complex system is a system composed of many interacting parts, such that the collective emergent behavior of those parts is more than the sum of their individual behaviors. Electrical energy systems may be considered a complex system due to its diversity of interrelated heterogeneous agents and emergent complex behavior. Energy systems are increasing in complexity with new advances related to the smart grid such as information and communication technology, distributed generation, electric vehicles, energy storage, and, especially, increasing interaction and participation of a large number of geographically distributed heterogeneous consumers. Power systems can be studied as a complex techno-socio-economical system with multiple facets, and Complex System Theory (CST) may provide a solid theoretical background for these modeling and analysis challenges. The present work deals with the application of CST into electrical energy systems, focusing the analysis on the consumer and their behavior on electricity consumption, using insights from the field of behavioral economics. Emergent complex behaviors on electricity consumption as well as its impact on power grids are analyzed by modeling customer behavior on an agent-based simulation, considering four different consumer categories. The analysis of the simulation, applied on a case study on a radial medium voltage distribution grid with real-world data, showed that slightly different assumptions on consumer behavior at the micro-level lead to very different and non-linear macro outcomes. To properly understand and model consumer behavior is of great importance to the planning and operation of electrical grids, and behavioral economics serves as a promising theoretical background to model behavior on electricity consumption. The results of this work showed that CST provides suitable tools to tackle electrical energy systems' increasing complexity, by considering the electrical power systems not as an aggregated independent system anymore, but as an integrated complex system. Keywords: power distribution; electricity consumption; complex systems theory; agent-based simulation; behavioral economics