5 resultados para Job shop

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Purpose: The purpose of this paper is to identify factors that facilitate tacit knowledge sharing in unstructured work environments, such as those found in automated production lines. Design/methodology/approach: The study is based on a qualitative approach, and it draws data from a four-month field study at a blown-molded glass factory. Data collection techniques included interviews, informal conversations and on-site observations, and data were interpreted using content analysis. Findings: The results indicated that sharing of tacit knowledge is facilitated by an engaging environment. An engaging environment is supported by shared language and knowledge, which are developed through intense communication and a strong sense of collegiality and a social climate that is dominated by openness and trust. Other factors that contribute to the creation of an engaging environment include managerial efforts to provide appropriate work conditions and to communicate company goals, and HRM practices such as the provision of formal training, on-the-job training and incentives. Practical implications: This paper clarifies the scope of managerial actions that impact knowledge creation and sharing among blue-collar workers. Originality/value: Despite the acknowledgement of the importance of blue-collar workers' knowledge, both the knowledge management and operations management literatures have devoted limited attention to it. Studies related to knowledge management in unstructured working environments are also not abundant. © Emerald Group Publishing Limited.

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A doença descrita no livro bíblico de Jó é controversa, e tem interessado a teólogos, psiquiatras e dermatologistas, há tempos. Neste trabalho os autores apontam para evidências do diagnóstico de insuficiência renal crônica com alterações neurológicas.

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Minimizing the makespan of a flow-shop no-wait (FSNW) schedule where the processing times are randomly distributed is an important NP-Complete Combinatorial Optimization Problem. In spite of this, it can be found only in very few papers in the literature. By considering the Start Interval Concept, this problem can be formulated, in a practical way, in function of the probability of the success in preserve FSNW constraints for all tasks execution. With this formulation, for the particular case with 3 machines, this paper presents different heuristics solutions: by integrating local optimization steps with insertion procedures and by using genetic algorithms for search the solution space. Computational results and performance evaluations are commented. Copyright (C) 1998 IFAC.