950 resultados para INTERNATIONAL PRODUCTION MANAGEMENT


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The high number of import rejections of food commodities suggests that producers in exporting countries are not complying with established standards. To understand why this is the case, we explore the behavior of producers and consumers in developing countries. First, we examine the successful transformation of production practices adopted by shrimp producers in Thailand. In support of the dramatic change in practices, we observe an important role played by the public sector in providing a means to visualize chemical residues and to control processes upstream of the supply chain via a registration system and a traceability system called Movement Document. Furthermore, very active information sharing by the private sector contributes to the dissemination of useful technical and market information among producers. We also examine the knowledge and perceptions of consumers with respect to food safety in Vietnam. We find that consumers in Hanoi and Ho Chi Minh City behave differently toward the third-party certification VietGAP, probably owing to differences in the history of market mechanisms between the two cities.

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This study analyses the effects that the project management certification has on employability. This analysis started with a participative process in which various groups of experts who are involved in the certification of people were consulted. A personal interview was carried out amongst 106 professionals —certifying bodies, training institutions, the civil service, and international organisations— and amongst professional who are certified in project management by the International Project Management Association in Spain. The results show that the certification emerges as a powerful tool for improving employability. The effects are demonstrated across two complementary aspects: internal company aspects and external aspects relating to the labour market. Finally, by compiling the different agents’ opinions, a series of measures emerge for improving the accreditation processes as an employability tool and increasing the mutual learning between public and private actors.

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This paper groups recent supply chain management research focused on organizational design and its software support. The classification encompasses criteria related to research methodology and content. Empirical studies from management science focus on network types and organizational fit. Novel planning algorithms and innovative coordination schemes are developed mostly in the field of operations research in order to propose new software features. Operations and production management realize cost-benefit analysis of IT software implementations. The success of software solutions for network coordination depends strongly on the fit of three dimensions: network configuration, coordination scheme and software functionality. This paper concludes with proposals for future research on unaddressed issues within and among the identified research streams.

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El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

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The inbound logistic for feeding the workstation inside the factory represents a critical issue in the car manufacturing industry. Nowadays, this issue is even more critical than in the past since more types of car are being produced in the assembly lines. Consequently, as workstations have to install many types of components, they also need to have an inventory of different types of the component in a compact space. The replenishment is a critical issue since a lack of inventory could cause line stoppage or reworking. On the other hand, an excess of inventory could increase the holding cost or even block the replenishment paths. The decision of the replenishment routes cannot be made without taking into consideration the inventory needed by each station during the production time which will depend on the production sequence. This problem deals with medium-sized instances and it is solved using online solvers. The contribution of this paper is a MILP for the replenishment and inventory of the components in a car assembly line.

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Cloud Agile Manufacturing is a new paradigm proposed in this article. The main objective of Cloud Agile Manufacturing is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

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This paper proposes a new manufacturing paradigm, we call Cloud Agile Manufacturing, and whose principal objective is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

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"Parts II and III available only from the National Archives and Records Service, Washington 25, D.C."

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Innovation and internationalization in services are key drivers of structural transformation, productivity growth and overall economic performance in Latin America. The services sector accounts for two thirds of the region’s GDP and provides over 60% of its employment. These shares are higher than in other developing regions, but still lower than in countries with higher levels of per capita income. The spread of information and communication technologies in Latin America over the past three decades has vastly enhanced both the tradability of services and the sector’s propensity to innovate. Long considered unrelated processes, both internationalization and innovation are today widely recognized as key and complementary sources of firm-level competitiveness and human capital enhancement. The advent of many novel types of business and consumer services is furthermore a key factor in the rising insertion of Latin American firms in regional and global value chains and transnational production networks, which are now the predominant form of organization of international production and trade. This volume explores three different levels of interaction between internationalization and innovation in the services sector in Latin America. Part I analyses the role of services in manufacturing and other sectors’ global value chains from a theoretical perspective, drawing on the experiences of Brazil and Mexico. Part II reviews innovation and internationalization policies and their effects on the performance of the services sector. Part III presents a series of case studies on innovation and internationalization linkages in Brazil, Chile, Costa Rica and Mexico. The book concludes that, in order for Latin American countries and firms to upgrade into services value chains, public and private initiatives must generate a host of regional public goods —enhanced investment climates, supply of skills, greater access to finance, improved protection of intellectual property, better value appropriation, enhanced efforts at standardization and quality certification— to strengthen the links between innovation and internationalization.

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Purpose - The purpose of this research paper is to demonstrate how existing performance measurement may be adopted to measure and manage performance in extended enterprises. Design/methodology/approach - The paper reviews the literature in performance measurement and extended enterprises. It explains the collaborative architecture of an extended enterprise and demonstrates this architecture through a case study. A model for measuring and managing performance in extended enterprises is developed using the case study. Findings - The research found that due to structural differences between traditional and extended enterprises, the systems required to measure and manage the performance of extended enterprises, whilst being based upon existing performance measurement frameworks, would be structurally and operationally different. Based on this, a model for measuring and managing performance in extended enterprises is proposed which includes intrinsic and extrinsic inter-enterprise coordinating measures. Research limitations/implications - There are two limitations this research. First, the evidence is based on a single case, thus further cases should be studied to establish the generalisibility of the presented results. Second, the practical limitations of the EE performance measurement model should be established through longitudinal action research. Practical implications - In practice the model proposed requires collaborating organisations to be more open and share critical performance information with one another. This will require change in practices and attitudes. Originality/value - The main contribution this paper makes is that it highlights the structural differences between traditional and collaborative enterprises and specifies performance measurement and management requirements of these collaborative organisations. © Emerald Group Publishing Limited.

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Discusses the necessity for the conscious recognition of the phenomenon known as the extended enterprise; this demands that product, process and supply chain design are all considered simultaneously. Structure must be given to the extended enterprise in order to understand and manage it efficaciously. The authors discuss multiple perspectives for doing this, and employ the notions of “3-dimensional concurrent engineering” and “holonic thinking” for conceiving what the structure may look like. Describes a current “action research” project that is investigating potential lead-time reductions within an extended enterprise’s product introduction process. This aims to produce process visualisations, a framework for structuring and sychronising phases and stage-gates within the extended enterprise, and a new simulation tool which will provide a synthetic distributed hypermedia network. These deliverables will be used to play strategic “games” to explore problem issues within the product introduction process that belongs to the extended enterprise, develop teamwork across autonomous companies, and ultimately, contribute to the design of future extended enterprise supply chains.