Factory Simulation Research Articles

Evaluating Stocking Efficacy in an Ecosystem Undergoing Oligotrophication

Oligotrophication has negatively affected fisheries production in many freshwater ecosystems and could conceivably reduce the efficacy of stockings used to enhance fisheries. In Lake Michigan, offshore oligotrophication has occurred since the 1970s, owing to reductions in total phosphorus (TP) inputs and nearshore sequestration of TP by nonindigenous dreissenid mussels. We evaluated simultaneous effects of stock enhancement and oligotrophication on salmonine species (Chinook salmon Oncorhynchus tshawytscha, lake trout Salvelinus namaycush, and steelhead O. mykiss) that support valuable recreational fisheries. We employed a novel application of an Ecopath with Ecosim model by conducting a full factorial simulation experiment. Our design included multiple levels of salmonine stocking, consumption by invasive quagga mussels (Dreissena bugensis), and TP that were informed by manager interests. Under all levels of TP and quagga mussel consumption, our results showed that stock enhancement could still increase salmonine biomass, but positive responses were stronger for lake trout and steelhead than Chinook salmon. Simulations showed that quagga mussel consumption has deleterious effects on pelagic-oriented prey fishes and Chinook salmon, which feed almost exclusively on the pelagic-oriented alewife (Alosa pseudoharengus). In summary, results from our simulation experiment suggested that lake trout and steelhead are better suited to the current ecosystem than Chinook salmon, and therefore, stock enhancement provides the highest gains for these two species. Furthermore, simulated biomass of all recreational salmonine species increased with increasing TP, indicating the need for managers to consider how potential future oligotrophication will limit the carrying capacity of salmonine biomass in Lake Michigan.

20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

Abstract. Measurements of the stable carbon isotope ratio (δ13C) on annual tree rings offer new opportunities to evaluate mechanisms of variations in photosynthesis and stomatal conductance under changing CO2 and climate conditions, especially in conjunction with process-based biogeochemical model simulations. The isotopic discrimination is indicative of the ratio between the CO2 partial pressure in the intercellular cavities and the atmosphere (ci∕ca) and of the ratio of assimilation to stomatal conductance, termed intrinsic water-use efficiency (iWUE). We performed isotope-enabled simulations over the industrial period with the land biosphere module (CLM4.5) of the Community Earth System Model and the Land Surface Processes and Exchanges (LPX-Bern) dynamic global vegetation model. Results for C3 tree species show good agreement with a global compilation of δ13C measurements on leaves, though modeled 13C discrimination by C3 trees is smaller in arid regions than measured. A compilation of 76 tree-ring records, mainly from Europe, boreal Asia, and western North America, suggests on average small 20th century changes in isotopic discrimination and in ci∕ca and an increase in iWUE of about 27 % since 1900. LPX-Bern results match these century-scale reconstructions, supporting the idea that the physiology of stomata has evolved to optimize trade-offs between carbon gain by assimilation and water loss by transpiration. In contrast, CLM4.5 simulates an increase in discrimination and in turn a change in iWUE that is almost twice as large as that revealed by the tree-ring data. Factorial simulations show that these changes are mainly in response to rising atmospheric CO2. The results suggest that the downregulation of ci∕ca and of photosynthesis by nitrogen limitation is possibly too strong in the standard setup of CLM4.5 or that there may be problems associated with the implementation of conductance, assimilation, and related adjustment processes on long-term environmental changes.

Attribution of seasonal leaf area index trends in the northern latitudes with “optimally” integrated ecosystem models

Significant increases in remotely sensed vegetation indices in the northern latitudes since the 1980s have been detected and attributed at annual and growing season scales. However, we presently lack a systematic understanding of how vegetation responds to asymmetric seasonal environmental changes. In this study, we first investigated trends in the seasonal mean leaf area index (LAI) at northern latitudes (north of 30°N) between 1982 and 2009 using three remotely sensed long-term LAI data sets. The most significant LAI increases occurred in summer (0.009m2 m-2 year-1 , p<.01), followed by autumn (0.005m2 m-2 year-1 , p<.01) and spring (0.003m2 m-2 year-1 , p<.01). We then quantified the contribution of elevating atmospheric CO2 concentration (eCO2 ), climate change, nitrogen deposition, and land cover change to seasonal LAI increases based on factorial simulations from 10 state-of-the-art ecosystem models. Unlike previous studies that used multimodel ensemble mean (MME), we used the Bayesian model averaging (BMA) to optimize the integration of model ensemble. The optimally integrated ensemble LAI changes are significantly closer to the observed seasonal LAI changes than the traditional MME results. The BMA factorial simulations suggest that eCO2 provides the greatest contribution to increasing LAI trends in all seasons (0.003-0.007m2 m-2 year-1 ), and is the main factor driving asymmetric seasonal LAI trends. Climate change controls the spatial pattern of seasonal LAI trends and dominates the increase in seasonal LAI in the northern high latitudes. The effects of nitrogen deposition and land use change are relatively small in all seasons (around 0.0002m2 m-2 year-1 and 0.0001-0.001m2 m-2 year-1 , respectively). Our analysis of the seasonal LAI responses to the interactions between seasonal changes in environmental factors offers a new perspective on the response of global vegetation to environmental changes.

Disentangling the effects of compositional and structural diversity on forest productivity

AbstractQuestionsTree species diversity is widely reported to positively influence forest productivity. Yet, a consistent attribution of productivity effects is complicated by the fact that compositional and structural diversity are often related in forest ecosystems. Here, our objective was to disentangle the effects of diversity in species and structures on forest productivity. We further assessed whether the influence of structure and composition on productivity changes over the course of forest development.LocationHainich National Park, central Germany.MethodsWe conducted a factorial simulation experiment in which 63 unique combinations of six different tree species were studied over 500 yr of forest development. The model used wasiLand, a process‐based simulator operating at individual tree resolution. The indicators of compositional diversity considered included species richness, entropy, evenness and identity, while structural diversity was characterized by indicators describing vertical and horizontal stand structure. Net primary production (NPP) was studied as the response variable, and random forest analysis was used to synthesize simulation output.ResultsWe found positive effects of both compositional and structural diversity on productivity, but their influence changed distinctly over the course of forest development. In early‐seral stages, diversity effects onNPPwere dominated by aspects of tree species composition, and displayed a strong positive selection effect for European beech (Fagus sylvaticaL.). In later stages of forest development, diversity effects onNPPwere dominated by structural diversity, with productivity increasing with increased variation in tree diameter and canopy complexity.ConclusionTo better understand the effects of diversity on ecosystem functioning, both the compositional and structural dimensions of diversity in forest ecosystems (and their changes over time) need to be considered. In the context of ecosystem management our results suggest that the reduction in productivity associated with the loss of a canopy tree species (e.g. due to the invasion of an alien pest species) can to some degree be compensated through increased structural diversity. Fostering both compositional and structural diversity are important means to increase the robustness of forest ecosystem functioning.

Tricanter Production Process Optimization by Digital Factory Simulation Tools

As a result of globalization the aspects of raising productivity and speed of production with extreme requests on the flexibility of the production systems are gaining importance. These aspects of production are affected by type of product and production and mainly by the capability of companies to correctly manage the manufacturing process. Manufacturing process is globally quicker than it was and the areas of logistics and production planning are still gaining more importance. Gradual changes are also in complexity of production. Without modern tools for production planning it would be very hard to manage production effectively. These tools are part of digital factory concept. Because of those tools the effective planning of production and utilizing the production facilities capacity to its fullest is possible. This paper describes development and implementation of the digital factory concept and its tools in our partner company and is built on previous paper dedicated to common implementation principles of digital factory tools. The main goal of digital factory implementation was optimization of the Tricanter production planning process, elimination of bottle-necks of production system and optimization of manufacturing facilities capacities utilization.

Simulating a Semiconductor Packaging Facility: Sustainable Strategies and Short-time Evidences

Semiconductor packaging plays a crucial role in semiconductor manufacturing because it is among the closest steps to the end customers. However, the complexity of production conditions makes controlling a semiconductor packaging facility a challenging task, and dynamic factory simulation has been considered as an effective means to fulfill this task. The large amounts of money, time, efforts, and expertise required to conduct a factory simulation study force a semiconductor packaging firm to pursue the persistent application of the factory simulation model (i.e., the sustainability of the factory simulation model). This challenge has rarely been discussed in previous studies. This study proposed several strategies to enhance the sustainability of a factory simulation model. In addition, the effectiveness of these strategies were examined by identifying short-time evidence rather than observing for a long duration to enhance efficiency. According to the experimental results, the adoption of the quick start-up, scaled-down, and OOAD strategies reduced the requirement of money, time, and effort in building the factory simulation model, and enhanced the sustainability.

Effects of Distributed Generations’ Integration to the Distribution Networks Case Study of Solar Power Plant

All over the world, the Distributed Generations (DGs) integration to power system has increased in the recent years due to economic, environmental and technical advantages. Turkey which has the huge solar potential has focused on integrating both licensed and unlicensed solar power plants by providing 10 years of purchasing guarantee as an incentive for the electricity producers from solar energy. However, the integration of DGs has several negative effects on the distribution networks (DNs). This work is concerned with investigating the possible challenges that may arise due to integration of PV based DGs on the existing distribution networks. Short circuit current level with respect to variation in MW integration is studied for the case the utility network is weak and strong. When the utility network is strong, the integration effect of inverter based DGs like solar power plants were observed insignificant. However, for the weak utility networks, the integration of inverter based DGs has been observed to have significant influence. Finally, directly integrated DGs (without inverter) are considered to reveal its difference with the non-inverter based DGs. As the case study, the distribution network integration of a solar power project, which is found in the Antalya region of Turkey, is investigated. This is 12 MW solar power plant designed to be connected to the local distribution network in Antalya. It is concluded that the effects of directly integrated DGs are observed more prominent compared to the inverter based DGs. DigSILENT Power Factory simulation tool is used for the study.

Simulation of Bullwhip Effect in a Supply Chain for Lean Learning Factory Purposes

A mission of the Learning Factory (LF) is a development of practice-based engineering curriculum through the simulation of a real factory by specialized equipment. In this paper, supply chain network simulator is developed, as a replacement for the traditional board Beer Game. The board Beer Game could be misused by participants in order to avoid significant bullwhip effect, which occurrence is the Beer Game main aim. The disadvantage of the board Beer Game, that participants have insight in inventory levels and placed orders and thus strategically act upon their knowledge or even activate a sort of decentralized information sharing policy, is avoided. Further considerations prove the mandatory occurrence of bullwhip effect without decentralized information sharing policy on three case studies. Optimal mathematical model for placing orders within supply chain was defined according to multi-criteria optimization process using spreadsheet simulation. As even optimal model results with the bullwhip effect, newly developed system will always lead to the tremendous bullwhip effect during the learning process.

Developing performance measurement system for Internet of Things and smart factory environment

To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.

Ecosystem service provision, management systems and climate change in Valsaín forest, central Spain

This study addresses the impact of climate change and management approach on the provision of four ecosystem services (ES) (timber production, protection against gravitational hazards, carbon sequestration and biodiversity) in Valsain forest in central Spain. The hybrid forest patch model PICUS v1.6 was used to simulate the development of 24 representative stand types over 100 years (2010–2110) in a full factorial simulation experiment combining three management regimes [“business as usual” management (BAU) and two alternatives to BAU (AM1 and AM2)], a no-management scenario (NOM) and six climate scenarios (historic climate represented by the period 1961–1990 and five transient climate change scenarios). Simulations indicated relatively small differences as regards the impact of the different management alternatives (BAU, AM1 and AM2) on the provision of ES as well as a clear improvement in biodiversity, protection and carbon storage under the no-management regime (NOM). Although timber production indicators were the most sensitive to climate change scenarios, biodiversity-related indicators responded fastest to the management regimes applied. Indicators of protection against rockfall and landslides were affected by both management and climate change. The results indicate substantial vulnerability of ES provisioning under the more extreme climate change scenarios at low elevations (1250 m). At higher elevations, the productivity of Scots pine stands may show a moderate decrease or increase, depending on the climate change scenario.

Habitat degradation and loss as key drivers of regional population extinction

Habitat quality is a fundamental driver of species distributions and population outcomes but is often difficult to measure and compare alongside measures of habitat amount and fragmentation. Consequently, habitat quality is often omitted from many landscape-level habitat analyses or more indirectly or subjectively represented in resulting habitat management or conservation planning. Yet, the implications of this conceptual and planning omission are poorly understood. We lack general theory that identifies the conditions under which habitat quality is expected to play a vital role in characterizing local and regional population responses. Using a factorial simulation design, we examined the independent contributions of habitat quality, amount, and fragmentation to population persistence to identify the conditions under which habitat quality might be expected to play a more important role than those of habitat amount or fragmentation. We generated a wide range of fractal landscapes, independently varying in habitat amount, fragmentation, and quality in QRule. We simulated interactive animal movement, habitat selection, and persistence for r and K strategist species with short and long dispersal abilities using spatially explicit individual-based models developed in HexSim. Population abundance and extinction risk were recorded through time for each landscape-species combination and used to quantify the relative influence of habitat amount, fragmentation, and landscape quality on population outcomes. We found that habitat degradation influenced extinction risk through a wide range of landscape conditions and species attributes. The most severe extinction responses were observed in scenarios of combined habitat loss and degradation, suggesting that the interactive effects of these variables may greatly affect persistence. Landscape quality modified extinction risks associated with habitat amount-fragmentation thresholds, and we found evidence for quality-based extinction thresholds as habitat was degraded. The strength of landscape-level quality on extinction risk outcomes suggests that habitat degradation should be further investigated as a major driver of population responses to landscape change. A more inclusive paradigm may be required to elucidate the general influences landscape change on population extinction. Habitat degradation, along with habitat loss and fragmentation, should be explicitly considered when assessing the implications of landscape change on population extinction.

Greening of the Earth and its drivers

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services(1,2). Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982-2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. The regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.

Data in support of energy performance of double-glazed windows.

This paper provides the data used in a research project to propose a new simplified windows rating system based on saved annual energy (“Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network” (Shakouri Hassanabadi and Banihashemi Namini, 2012) [1], “Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates” (Banihashemi et al., 2015) [2]). A full factorial simulation study was conducted to evaluate the performance of 26 different types of windows in a four-story residential building. In order to generalize the results, the selected windows were tested in four climates of cold, tropical, temperate, and hot and arid; and four different main orientations of North, West, South and East. The accompanied datasets include the annual saved cooling and heating energy in different climates and orientations by using the selected windows. Moreover, a complete dataset is provided that includes the specifications of 26 windows, climate data, month, and orientation of the window. This dataset can be used to make predictive models for energy efficiency assessment of double glazed windows.

Digital Factory Simulation Tools

The article deals with the use of Siemens digital factory concept for production capacity planning. In the increasing competitive environment of globalized world economy, pressure to grow effciency of production pro-cesses and systems greatly increases. In addition the increasing cmplexity of product requires appropriate as well as-sembly and logistic processes as production process planning and control. These requirements in the production process planning and cotrol may be due to its complexity filled only with appropriate instruments provided by comprehesive concept of the digital factory, which allow effective use of information on production, promote collaboration between departments and provide relevant data to anyone who needs it. This paper describes implementation of digital factory simulation tools for the production process planning and control at our industrial partner. This approach to production capacity planning using the digital factory concept is unique in the Czech Republic.

Potential use of the N2/Ar ratio as a constraint on the oceanic fixed nitrogen loss

AbstractUsing a global ocean biogeochemical model, we investigate the suitability of the N2/Ar supersaturation ratio (ΔN2/Ar) as a tracer of marine nitrogen fixation and denitrification, i.e., the main biological processes that add or remove fixed nitrogen to or from the ocean. In a series of factorial simulations, we demonstrate that, in regions away from the oxygen minimum zones (OMZs), the ΔN2/Ar characteristics are mostly determined by benthic denitrification occurring in the deep ocean with minor contributions from benthic and water column denitrification at shallower depths. In the OMZs, the subsurface maxima of ΔN2/Ar are mainly determined by water column denitrification. In contrast, nitrogen fixation has little impact on ΔN2/Ar owing to the rapid loss of the N2 supersaturation signal through air‐sea exchange. We thus conclude that ΔN2/Ar can act as a powerful constraint on water column and benthic denitrification occurring in intermediate to deep waters, but it cannot be used to estimate nitrogen fixation. A comparison between the currently very limited observations of the ΔN2/Ar with our model results shows an acceptable level of agreement, suggesting that the model's prescribed rates and distributions of benthic and water column denitrification (i.e., 140 and 52 Tg N yr−1, respectively) are reasonable and confirm the results derived from other constraints.

Seasonal responses of terrestrial ecosystem water-use efficiency to climate change.

Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2 . The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt , the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 , and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005gCm(-2) mm(-1) yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.

Development of a cloud-based factory simulation system for enabling ubiquitous factory simulation

This study investigated several problems related to the implementation of cloud-based factory simulation. First, the differences between cloud-based factory simulation and parallel and distributed factory simulation were discussed. Individually managed, resource heterogeneity, uneven load partitioning, and potential business opportunities were found to be the novel characteristics that discriminate cloud-based factory simulation from parallel and distributed factory simulation. The problems in existing cloud-based factory simulation systems are discussed. An experimental cloud-based factory simulation system was developed and used for simulating a mobile lift table factory. We investigated problems related to the implementation of cloud-based factory simulation.We discussed differences between cloud-based and parallel or distributed simulations.We discussed problems in existing cloud-based factory simulation systems.We developed an experimental cloud-based factory simulation system.

Transfer of Model of Innovative Smart Factory to Croatian Economy Using Lean Learning Factory

Croatia's manufacturing industry faces many problems and obstacles that have a large impact on its competitiveness. Insufficiently educated and unskilled personnel, particularly in the production and management fields, are decreasing competitiveness that is necessary for survival in the global market. Objective of project Innovative Smart Enterprise is to establish a special learning environment in one Laboratory asLean Learning Factory, i.e. simulation of a real factory through specialized equipment. The Lean Learning Factory's mission is to integrate needed knowledge into the engineering curriculum. Therefore, Lean Learning Factory at University of Split is in continuous developing process to support practice-based engineering curriculum with possibility of learning necessary tools and methods, using didactic games or real life products and equipment. Solution proposal for best balance between toys and real products consider design and production line development for product Karet. It is a traditional and original product from Croatia, so it will raise enthusiasmin learning process in both students and industry employees. Two assembly lines will be developed, one traditionally equipped and one intelligent, networked, flexible, and fully improved by Lean tools. By deeper analysis of both assembly lines, hybrid assembly lines could be designed, to balance on one side assembly tact time according to customer demand and total cost of installation and running on the other side. Methods and tools adapted and implemented, in both design and analysis process for optimization of this hybrid assembly line would be scaled and adjusted for industry use as part as knowledge transfer from university to enterprises.

Performance modelling and simulation of metal powder bed fusion production system

New opportunities arise for the deployment of metal powder bed fusion as a scalable batch production method particularly for high value manufacturing in aerospace and medical industries. To avoid costly errors in design of such ‘Factories of the Future’, a discrete event simulation of a concept factory of 22 additive manufacturing machines is constructed. The impacts of part variety, operators and shift patterns on throughput and cost are investigated. Results showed optimum staffing are dependent upon the build duration of parts being manufactured. In all cases, significant improvements in machine utilisation and throughput can be achieved by full analysis of operator levels and shift patterns.

Investigation &amp; Minimization of Loss in Distribution System

For efficient and reliable operation of distribution system, the reactive power and voltage should be controlled so that energy loss should be minimized, bus-bar voltage should be maintained at acceptable limit (0.95P.U min and 1.05P.U max) and three phase voltages should approach as close as to the balanced system voltage . This paper work presents study of distribution system loss in the case of Textile factory, ArbaMinch town. The study makes a detail work on power system issues such as energy loss in the distribution system and its reduction techniques, reactive power flow and its compensation, power factor and voltage quality indicators such as voltage unbalance and voltage regulation. To achieve the objective, the existing distribution system of study site is modeled by using DIgSILENT Power Factory Software and simulation is carried out for unbalanced and balanced operation conditions. Clamp-on meter measurement is used to determine the load demand and line to line voltages. The results obtained for loss, power factor, voltage regulation and voltage unbalance are compared against accepted standards of IEEE, NEC & Ethiopian Electric Power Corporation (EEPCo) and possible solutions are recommended based on results obtained.