Production networks in the Asia-Pacific region : facts and policy implications

Production networks have been extensively developed in the Asia-Pacific region. This paper employs two micro-level approaches, case studies and econometric analysis, using JETRO's firm surveys which investigate Japanese affiliates operating in Southeast Asia. These two approaches found that production networks have extended, involving suppliers, across various nations in the Asia-Pacific region, and that production bases in host and home countries have different roles. A home country serves as a headquarters with services such as R&D, international marketing, and financing. A high tariff policy in a host country may foster domestic industries through the expansion of procurement from domestic suppliers, either indigenous or foreign, but it may discourage a country from becoming an export platform.

Firm-level impacts of natural disasters on production networks : evidence from a flood in Thailand

In this paper, we explore the firm-level impacts of flooding in Thailand in 2011, specifically those on the procurement patterns at Japanese affiliates in Thailand. Our findings are as follow. First, the damaged small firms are more likely to lower their local procurement share, particularly the share of procurement from other Japanese-owned firms in Thailand. Second, damaged young firms and damaged old firms are more likely to raise the shares of imports from Japan and China, respectively. Third, there are no impacts on imports from ASEAN and other countries. These findings are useful for uncovering how multinational firms adjust their production networks before and after natural disasters.

Boundaries of firms and catching up by latecomers in global production networks : the case of a Mexican auto-parts manufacturer

For manufacturing firms in developing countries, there are high barriers to entry and to catching up with competitors in their global production networks (GPNs). This paper examines the case of a Mexican auto-parts manufacturer that succeeded in catching up in the automotive GPN. The author proposes that the door to GPNs is open thanks to frequent changes in the boundaries of firms, and also stresses the importance of the necessary conditions that generate opportunities, including institutional settings that facilitate market entry and catching up, and capability building by firms hopeful of entry.

Industrial deepening in East Asia

Structural transformations are an indispensable element of sustained economic growth. Within the context of East Asia, this study focuses on industrial deepening, which refers to the formation of local linkages and the creation of a robust local supplier base. To investigate the progress of industrial deepening, this study introduces two kinds of domestic procurement measures in addition to the previously developed local content measures. Specifically, two kinds of vertical specialization measures are used to demonstrate the degree to which respective East Asian economies are specialized within their vertical production networks. The results clearly show that the advancement of production networks is likely to reduce domestic procurement ratios, even if local supplier bases are strengthened in the respective countries. Moreover, the trend of domestic procurement ratios differs depending on the characteristics of particular industries and the industrial policies adopted by individual countries.

Skill sorting and production chains : evidence from India

This study proposes a new mechanism that explains skill-sorting patterns and skill wage differentials across industries based on the length of the industry's production chain. A simple simultaneous production model shows that when the quality of intermediate inputs deteriorates rapidly along the production chains, high-skilled individuals choose to work in industries with shorter production chains because of higher returns to skill. I empirically confirm this skill-sorting pattern and these inter-industry skill wage differentials in India, where the quality of intermediate inputs is likely to degrade rapidly because of the high number of unskilled laborers, poor infrastructure, and less-advantaged technology. The results remain robust even when considering selection bias, alternative reasons for inter-industry skill wage differentials, and a different period. The results of this study have important implications when considering countries' industrial development patterns.

Influence of termal fluctuations in radiation damage cascade production and defect dynamics in tungsten

The detailed study of the deterioration suffered by the materials of the components of a nuclear facility, in particular those forming part of the reactor core, is a topic of great interest which importance derives in large technological and economic implications. Since changes in the atomic-structural properties of relevant components pose a risk to the smooth operation with clear consequences for security and life of the plant, controlling these factors is essential in any development of engineering design and implementation. In recent times, tungsten has been proposed as a structural material based on its good resistance to radiation, but still needs to be done an extensive study on the influence of temperature on the behavior of this material under radiation damage. This work aims to contribute in this regard. Molecular Dynamics (MD) simulations were carried out to determine the influence of temperature fluctuations on radiation damage production and evolution in Tungsten. We have particularly focused our study in the dynamics of defect creation, recombination, and diffusion properties. PKA energies were sampled in a range from 5 to 50 KeV. Three different temperature scenarios were analyzed, from very low temperatures (0-200K), up to high temperature conditions (300-500 K). We studied the creation of defects, vacancies and interstitials, recombination rates, diffusion properties, cluster formation, their size and evolution. Simulations were performed using Lammps and the Zhou EAM potential for W

Application of Ultraintense Lasers to validate materials for laser fusion: production of ions and other relevant species

Justification of the need and demand of experimental facilities to test and validate materials for first wall in laser fusion reactors - Characteristics of the laser fusion products - Current ?possible? facilities for tests Ultraintense Lasers as ?complete? solution facility - Generation of ion pulses - Generation of X-ray pulses - Generation of other relevant particles (electrons, neutrons..)

Cup Anemometer's loss of performance due to ageing process, and its effect on Annual energy Production (AEP) estimates

The deviation of calibration coefficients from five cup anemometer models over time was analyzed. The analysis was based on a series of laboratory calibrations between January 2001 and August 2010. The analysis was performed on two different groups of anemometers: (1) anemometers not used for any industrial purpose (that is, just stored); and (2) anemometers used in different industrial applications (mainly in the field—or outside—applications like wind farms). Results indicate a loss of performance of the studied anemometers over time. In the case of the unused anemometers the degradation shows a clear pattern. In the case of the anemometers used in the field, the data analyzed also suggest a loss of performance, yet the degradation does not show a clear trend. A recalibration schedule is proposed based on the observed performances variations

On the complexity of radiation models for PV energy production calculation

Several authors have analysed the changes of the probability density function of the solar radiation with different time resolutions. Some others have approached to study the significance of these changes when produced energy calculations are attempted. We have undertaken different transformations to four Spanish databases in order to clarify the interrelationship between radiation models and produced energy estimations. Our contribution is straightforward: the complexity of a solar radiation model needed for yearly energy calculations, is very low. Twelve values of monthly mean of solar radiation are enough to estimate energy with errors below 3%. Time resolutions better than hourly samples do not improve significantly the result of energy estimations.

Radiation heat savings in polysilicon production: validation of results through a CVD laboratory prototype

This work aims at a deeper understanding of the energy loss phenomenon in polysilicon production reactors by the so-called Siemens process. Contributions to the energy consumption of the polysilicon deposition step are studied in this paper, focusing on the radiation heat loss phenomenon. A theoretical model for radiation heat loss calculations is experimentally validated with the help of a laboratory CVD prototype. Following the results of the model, relevant parameters that directly affect the amount of radiation heat losses are put forward. Numerical results of the model applied to a state-of-the-art industrial reactor show the influence of these parameters on energy consumption due to radiation per kilogram of silicon produced; the radiation heat loss can be reduced by 3.8% when the reactor inner wall radius is reduced from 0.78 to 0.70 m, by 25% when the wall emissivity is reduced from 0.5 to 0.3, and by 12% when the final rod diameter is increased from 12 to 15 cm.

About the origin of low wafer performance and crystal defect generation on seed-cast growth of industrial mono-like silicon ingots

The era of the seed-cast grown monocrystalline-based silicon ingots is coming. Mono-like, pseudomono or quasimono wafers are product labels that can be nowadays found in the market, as a critical innovation for the photovoltaic industry. They integrate some of the most favorable features of the conventional silicon substrates for solar cells, so far, such as the high solar cell efficiency offered by the monocrystalline Czochralski-Si (Cz-Si) wafers and the lower cost, high productivity and full square-shape that characterize the well-known multicrystalline casting growth method. Nevertheless, this innovative crystal growth approach still faces a number of mass scale problems that need to be resolved, in order to gain a deep, 100% reliable and worldwide market: (i) extended defects formation during the growth process; (ii) optimization of the seed recycling; and (iii) parts of the ingots giving low solar cells performance, which directly affect the production costs and yield of this approach. Therefore, this paper presents a series of casting crystal growth experiments and characterization studies from ingots, wafers and cells manufactured in an industrial approach, showing the main sources of crystal defect formation, impurity enrichment and potential consequences at solar cell level. The previously mentioned technological drawbacks are directly addressed, proposing industrial actions to pave the way of this new wafer technology to high efficiency solar cells.

Descriptive study of production factors affecting performance traits in growing-finishing pgis in Spain.

The objective of this study was to build up a data set including productive performance and production factors data of growing-finishing (GF) pigs in Spain in order to perform a representative and reliable description of the traits of Spanish growing-finishing pig industry. Data from 764 batches from 452 farms belonging to nine companies (1,157,212 pigs) were collected between 2008 and 2010 through a survey including five parts: general, facilities, feeding, health status and performance. Most studied farms had only GF pigs on their facilities (94.7%), produced ‘industrial’ pigs (86.7%), had entire male and female (59.5%) and Pietrain-sired pigs (70.0%), housed between 13-20 pigs per pen (87.2%), had  50% of slatted floor (70%), single-space dry feeder (54.0%), nipple drinker (88.7%) and automatic ventilation systems (71.2%). A 75.0% of the farms used three feeding phases using mainly pelleted diets (91.0%), 61.3% performed three or more antibiotic treatments and 36.5% obtained water from the public supply. Continuous variables studied had the following average values: number of pigs placed per batch, 1,515 pigs; initial and final body weight, 19.0 and 108 kg; length of GF period, 136 days; culling rate, 1.4%; barn occupation, 99.7%; feed intake per pig and fattening cycle, 244 kg; daily gain, 0.657 kg; feed conversion ratio, 2.77 kg kg-1 and mortality rate, 4.3%. Data reflecting the practical situation of the Spanish growing and finishing pig production and it may contribute to develop new strategies in order to improve the productive and economic efficiency of GF pig units.

Wireless Sensor Network Solution for Sustainable Food Production

Environmental monitoring has become a key aspect in food production over the last few years. Due to their low cost, low power consumption and flexibility, Wireless Sensor Networks (WSNs) have turned up as a very convenient tool to be used in these environments where no intrusion is a must. In this work, a WSN application in a food factory is presented. The paper gives an overview of the system set up, covering from the initial study of the parameters and sensors, to the hardware-software design and development needed for the final tests in the factory facilities.

Coordination mechanisms and software in industrial networks - a literature review

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.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

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.