Understanding new venture market application search processes: A propositional model.

Technology-based ventures are confronted with complex decisions on how to apply their technology platform in highly uncertain and ambiguous market environments. Based on four case studies, a dynamic decision model is developed in which we highlight the similarities between the search and learning processes in venture development contexts and in new product development contexts. This entrepreneurial search and learning process is understood as consisting of sequences of episodes – characterized by uncertainty and ambiguity - and scripts – i.e. approaches to market application search. The model implies that a venture's adaptability - i.e. its ability to move efficiently and effectively between these episodes and their related scripts - influences its survival.Case studies; Decision; Decisions; Learning; Market; Model; Processes; Product; Product development; Research; Sequences; Similarity; Studies; Technology; Uncertainty;

Ontologias para Manutenção Preditiva com Dados sensíveis ao tempo

As empresas de fabrico industrial devem assegurar um processo produtivo contínuo para serem competitivas e fornecer os produtos fabricados no prazo e com a qualidade exigida pelos clientes. A quebra da cadeia de fabrico pode ter desfechos graves, resultando numa redução da produção e na interrupção da cadeia de abastecimento. Estes processos são compostos por cadeias de máquinas que executam tarefas em etapas. Cada máquina tem uma tarefa específica a executar, e o resultado de cada etapa é fornecido à próxima etapa. Uma falha imprevista numa das máquinas tende a interromper toda a cadeia produtiva. A manutenção preventiva agendada tem como objetivo evitar a ocorrência de falhas, tendo como base o tempo médio antes da falha (MTBF), que representa a expectativa média de vida de componentes individuais com base em dados históricos. As tarefas de manutenção podem implicar um período de paralisação e a interrupção da produção. Esta manutenção é executada rotineiramente e a substituição de componentes não considera a necessidade premente da sua substituição, sendo os mesmos substituídos com base no ciclo do agendamento. É aqui que a manutenção preditiva é aplicável. Efetuando a recolha de dados de sensores dos equipamentos, é possível detetar irregularidades nos dados recolhidos, através da aplicação de processos de raciocínio e inferência, conduzindo à atempada previsão e deteção de falhas. Levando este cenário à otimização do tempo de manutenção, evitando falhas inesperadas, à redução de custos e ao aumento da produtividade em comparação com a manutenção preventiva. Os dados fornecidos pelos sensores são sensíveis ao tempo, variações e flutuações ocorrem ao longo do tempo e devem ser analisados em relação ao período em que ocorrem. Esta dissertação tem como objetivo o desenvolvimento de uma ontologia para a manutenção preditiva que descreva a sua abrangência e o campo da sua aplicação. A aplicabilidade da ontologia será demonstrada com uma ferramenta, igualmente desenvolvida, que transforma dados sensíveis ao tempo recolhidos em tempo real a partir de sensores de máquinas industriais, fornecidos por WebServices, em indivíduos dessa mesma ontologia, considerando a representação do fator temporal dos dados.Manufacturing companies must ensure a continuous production process to be competitive and supply the manufactured goods in time and with the desired quality the customers expect. Any disruption in the manufacturing chain may have disastrous consequences, representing a shortage of production and the interruption of the supply chain. The manufacturing processes are composed of a chain of industrial machines operating in stages. Each machine has a specific task to complete, and the result of each stage is forwarded to the next stage. An unpredicted malfunction of one of the machines tends to interrupt the whole production chain. Scheduled Preventive maintenance intends to avoid causes leading to faults, but relies on parameters such as Mean Time Before Failure (MTBF), which represents the average expected life span of individual components based on statistical data. A maintenance task may lead to a period of downtime and consequently to a production halt. Being the maintenance scheduled and executed routinely, the replacement of components, does not consider the effective need of its replacement, they are replaced based on the scheduling cycle. This is where predictive maintenance is applicable. By collecting sensor data of industrial equipment, anomalies can be determined through reasoning and inference processes applied to the data, leading to an early fault and time to failure prediction. This scenario leads to maintenance timing optimization, avoidance of unexpected failures, cost savings and improved productivity when compared to preventive maintenance. Data supplied by sensors is timesensitive, as variations and fluctuations occur over periods of time and must be analysed concerning the period they occur. This dissertation aims to develop an ontology for predictive maintenance that describes the scope and field of application. The applicability of the ontology will be demonstrated with a tool, also to be developed, that transforms time-sensitive data collected in real time from sensors of industrial machines, provided by a WebServices, into individuals of the same ontology, considering the representation of the temporal factor of the data

Cost estimation in initial development stages of products: an ontological approach

Cost estimation in the early stages of a product are fraught with uncertainties. The conceptual design of product development is characterized by the absence of data, the most critical being costs. The costs impact in the initial phases of the project is low, when discovered in later stages represent great risks. As there are no structured alternatives to obtaining costs in the conceptual phase, the reuse of data from past projects is an alternative discussed in the literature. Knowledge management approaches can search for data, nonexistent in the current phases, in successful earlier projects. The use of ontology is discussed as an approach in generating knowledge stored in a database. The proposed solution seeks to estimate costs based on previous projects. A query is formulated to describe the product function and settings. The ontological model searches the classes, instances, and properties in the database and generates a cost estimation. The costs of the previous project are reused to generate a new agile cost estimate without the need to consult other industry sectors. This dissertation project follows the methodological framework Design Science Research to make partial deliveries up to the final artifact, an ontological model. This proposal has great potential in the industry, considering there are no tools attending the initial phases with the same efficiency.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Estimativas de custos nas fases iniciais de um produto são repletas de incertezas. O projeto conceitual do desenvolvimento de produto e caracterizado pela ausência de dados, sendo os mais críticos os custos. O impacto dos custos nas fases iniciais do projeto e baixo, quando descobertos em fases posteriores representam grandes riscos. Como não existem meios estruturados de obtenção dos custos no projeto na fase conceitual, o reuso de dados de projetos passados e uma alternativa discutida na literatura. Abordagens de gerenciamento de conhecimento podem buscar dados, inexistentes nas fases atuais, em projetos anteriores bem sucedidos. O uso de ontologia e discutido como uma abordagem na geração de conhecimento armazenado em um banco de dados. A solução proposta busca estimar custos baseada em projetos anteriores. E formulada uma pergunta que descreva a função do produto e configurações. O modelo ontológico busca na base de dados classes, instâncias e propriedades e gera uma estimativa de custos. Os custos do projeto anterior são reutilizados para gerar uma nova estimativa de custos ágil sem necessidade de consultar outros setores da indústria. Este projeto de dissertação segue o framework metodológico Design Science Research para fazer entregas parciais ate a entrega do artefato final, um modelo ontológico. Esta proposta possui grande potencial na indústria, considerando que não existem ferramentas que atendam as fases iniciais com a mesma eficiência

Smart Change in Strategy: IBM‘s Response to Challenging Times

International Business Machines, or IBM, has been an indisputable force in the communications industry, leading the world into the modern, global technological age. Currently, IBM has revamped its business paradigm, allocating the majority of its resources to consulting work and data analyses rather than manufacturing as it had done so in the past — for the primary objectives of optimizing existing assets, resolving problems of burgeoning cities and beleaguered governments, and enhancing peoples‘ lives in a sustainable way

SCRO: A Domain Ontology for Describing Steel Cold Rolling Processes towards Industry 4.0

This paper introduces the Steel Cold Rolling Ontology (SCRO) to model and capture domain knowledge of cold rolling processes and activities within a steel plant. A case study is set up that uses real-world cold rolling data sets to validate the performance and functionality of SCRO. This includes using the Ontop framework to deploy virtual knowledge graphs for data access, data integration, data querying, and condition-based maintenance purposes. SCRO is evaluated using OOPS!, the ontology pitfall detection system, and feedback from domain experts from Tata Steel

An Object memory for an object-oriented database management system

Ankara : The Department of Computer Engineering and Information Sciences and the Institute of Engineering and Sciences of Bilkent Univ. , 1988.Thesis (Master's) -- Bilkent University), 1988.Includes bibliographical references leaves 86-89.Object-oriented paradigm is an approach that can be applied in various areas of computing. In this approach, each entity is represented by an object which captures the state and the behaviour of the entity. In this thesis, a focused survey of object-oriented paradigm in general and object-oriented database management systems in particular has been carried out and an object memory module is designed and implemented for an object-oriented database management system prototype. The object memory module handles the representation, access and manipulation of objects in the system and provides the primitive functions that are necessary in the development of the prototype.Kesim, F NihanM.S

ExtruOnt: An ontology for describing a type of manufacturing machine for Industry 4.0 systems

Semantically rich descriptions of manufacturing machines, offered in a machine-interpretable code, can provide interesting benefits in Industry 4.0 scenarios. However, the lack of that type of descriptions is evident. In this paper we present the development effort made to build an ontology, called ExtruOnt, for describing a type of manufacturing machine, more precisely, a type that performs an extrusion process (extruder). Although the scope of the ontology is restricted to a concrete domain, it could be used as a model for the development of other ontologies for describing manufacturing machines in Industry 4.0 scenarios. The terms of the ExtruOnt ontology provide different types of information related with an extruder, which are reflected in distinct modules that constitute the ontology. Thus, it contains classes and properties for expressing descriptions about components of an extruder, spatial connections, features, and 3D representations of those components, and finally the sensors used to capture indicators about the performance of this type of machine. The ontology development process has been carried out in close collaboration with domain experts.This research was funded by the Spanish Ministry of Economy and Competitiveness, grant number FEDER/TIN2016-78011-C4- 2R. The work of Víctor Julio Ramírez-Durán is funded by the contract with reference BES-2017-081193

A study of existing Ontologies in the IoT-domain

Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.Comment: Submitted to Elsevier JWS SI on Web semantics for the Internet/Web of Thing