A Maintenance Service Improvement Approach Based on Queue Networks: Application

The quest to increase the performance of production systems that have become complex leads to the transfer to the maintenance function of the responsibility of guaranteeing the availability of such systems. Also, we will never stop saying that maintenance must integrate into all of the company’s initiatives, to affirm its role, which is to ensure greater availability and sustainability of the means of production. The objective of this paper is to evaluate the reliability and availability of a system without knowing the distribution law of the operating times. Among the methods for evaluating dependability criteria (Fault Trees, Petri Nets, etc.), we are interested in queues that have the advantage of taking into account functional dependencies, thus allowing a quantified optimization of maintenance. Indeed, queues make it possible to model parallel or sequential processes, implementing operations taking place at the same time or one after the other, meeting the needs of modeling production systems. The main result of this paper is the study of the influence of availability on the reliability of a multi-state production system.

Digital biofabrication to realize the potentials of plant roots for product design

Technological and economic opportunities,alongside the apparent ecological benefits,point to biodesign as a new industrial paradigm for the fabrication of products in the twenty-first century.The presented work studies plant roots as a biodesign material in the fabrication of self-supported 3D structures,where the biologically and digitally designed materials provide each other with structural stability.Taking a material-driven design approach,we present our systematic tinkering activities with plant roots to better understand and anticipate their responsive behaviour.These helped us to identify the key design parameters and advance the unique potential of plant roots to bind discrete porous structures.We illustrate this binding potential of plant roots with a hybrid 3D object,for which plant roots connect 600 computationally designed,optimized,and fabricated bioplastic beads into a low stool.

Waste Biomass Gasification Simulation Using Aspen Plus: Performance Evaluation of Wood Chips, Sawdust and Mixed Paper Wastes

Biomass is one of the most widely available energy sources and gasification is a thermal conversion process where biomass is transformed into a fuel gas with a gasifying agent. In this paper by using ASPEN Plus, a new steady state simulation model for down draft waste biomass gasification was developed. The model that is stoichiometric equilibrium-based is proposed to be used for optimization of the gasifier performance. Prediction accuracy of the model is validated by comparing with available experimental and modeling results in other literature. Then the model is used for comparative analysis of the gasification performance of sawdust, wood chips and mixed paper wastes. In the model, the operating parameters of temperature and equivalence ratio (ER) have been varied over wide range and their effect on syngas composition, syngas yield, low heating value (LHV) of syngas and cold gas efficiency (CGE) has been investigated. Raise in temperature increases the production of CO and H2 which leads to higher syngas yield, LHV and CGE. However, increasing ER decreases the production of CO and H2 which results lessens in LHV and CGE but syngas yield continuously increases because more oxygen is available for biomass reactions at high ER. The optimal values of CO and H2 mole fraction and CGE of sawdust, wood chips and mixed paper wastes are located at 900&degC, 1000&degC and 1000&degC, respectively and ER range is between 0.20 - 0.35 regardless of the kind of biomass which is used as the feedstock.

Refinement of Bouguer anomalies derived from the EGM2008 model,impact on gravimetric signatures in mountainous region:Case of Cameroon Volcanic Line,Central Africa

Global geopotential models have not included the very high frequencies of the Earth’s external gravity field.This is called omission error.This omission error becomes more important in mountainous areas(areas with highly variable topography).The work reported here consists in reducing the omission error in measurements of Bouguer gravity anomalies,by refining the global geopotential model EGM2008 using the spectral enhancement method.This method consists in computing the residual terrain effects and then coupling them to the gravimetric signal of the global geopotential model.To compute the residual terrain effects,we used the Residual Terrain Model(RTM)technique.To refine it required a reference surface(ETOPO1)developed up to degree 2190(the maximum degree of the EGM2008 model)and a detailed elevation model(AW3D30).Computation was performed with the TC program of the GRAVSOFT package.The topography of the study area was assumed to have a constant density of 2670 kg/m3.For the inner and outer zones,the respective integration radii of 10 km and 200 km have been chosen.We obtained very important RTM values ranging from−53.59 to 34.79 mGal.These values were added to the gravity anomalies grid of the EGM2008 model to improve accuracy at high frequencies.On a part of the Cameroon Volcanic Line and its surroundings(mountainous area),we made a comparison between the residual Bouguer anomalies before and after refinement.We report differences ranging from−37.40 to 26.40 mGal.We conclude that the impact of omission error on gravimetric signatures is observed especially in areas with high variable topography,such as on the Cameroon Volcanic Line and around the localities of Takamanda,Essu,Dumbo,and Ngambe.This finding illustrates the great influence that topography has on accurate measurement of these gravity anomalies,and thus why topography must be taken into account.We can conclude that in preparing a global geopotential model,a high resolution DTM must be used to decrease the omission error:the degree of expansion has to increase in order to take the higher frequencies into account.The refined Bouguer anomalies grid presented here can be used in addition to terrestrial gravity anomalies in the study area,especially in mountainous areas where gravimetric data are very sparse or nonexistent.

Techno-Economic Analysis of Power Production by Using Waste Biomass Gasification

Energy recovery from waste biomass can have significant impacts on the most pressing development challenges of rural poverty and environmental damages. In this paper, a techno-economic analysis is carried out for electricity generation by using timber and wood waste (T & WW) gasification in Iceland. Different expenses were considered, like capital, installation, engineering, operation and maintenance costs and the interest rate of the investment. Regarding to revenues, they come from of the electricity sale and the fee paid by the Icelandic municipalities for waste collection and disposal. The economic feasibility was conducted based on the economic indicators of net present value (NPV) and discounted payback period (DPP), bringing together three different subgroups based on gasifier capacities, subgroup a: 50 kW, subgroup b: 100 kW and subgroup c: 200 kW. The results show that total cost increases as the implemented power is increased. This indicator varies from 1228.6 k€ for subgroups a to 1334.7 k€ for subgroups b and 1479.5 k€ for subgroups c. It is worth mentioning that NPV is positive for three subgroups and it grows as gasifier scale is extended. NPV is about 122 k€ (111,020 $), 1824 k€ (1,659,840 $) and 4392 k€ (3,996,720 $) for subgroups a, b and c, respectively. Moreover, DPP has an inversely proportional to the installed capacity. It is around 5.5 years (subgroups a), 9.5 months (subgroups b) and 6 months (subgroups c). The obtained results confirm that using small scale waste biomass gasification integrated with power generation could be techno-economically feasible for remote area in Iceland.

Performance Investigation of Biomass Gasification for Syngas and Hydrogen Production Using Aspen Plus

This study presents a reliable model using Aspen Plus process simulator capable of performing a sensitivity analysis of the downdraft gasification linked to hydrogen production unit. Effects of key factors, including gasification temperature and steam to biomass ratio (SBR) on the syngas composition, calorific value of syngas and hydrogen production are discussed and then the optimal conditions for maximum hydrogen production are extracted. The model is validated by experimental and other modeling data and found to be in great agreement. The sensitivity analysis results obtained by only using air as gasification agent indicate that higher temperatures are favorable for a product gas with higher hydrogen content and calorific value. Moreover, steam consumption as gasifying agent leads to increasing the hydrogen content and heating value of the syngas compared to the use of air as gasification agent. Finally, the results show that the optimal conditions to have the highest value of hydrogen output from sawdust downdraft gasification are 800&#730C as gasifier temperature and 0.6 for SBR.

Assessment of the Selective Properties and Optimization of Mesh Size of Pelagic Trawl Codends, Used for Fishing Mackerel (Trachurus Spp) in the Gulf of Guinea

Over the past few decades, it has become widely recognized that the management strategies of world fisheries must ensure sustainability of target species. The intervening years have seen many improvements to the concept of gear selectivity and methods for measuring the selectivity of fishing towed gears. Improved understanding of the principles of the selection of fish by gears has changed the list of parameters which are known to have a significant effect upon selection. The recent development of new mathematical models and the increased availability of powerful computers have resulted in improvements in the analysis procedures for the data produced to measure a gear’s selectivity. The catch of mackerel in the gulfofGuineahas steeply declined during the last two decades, and resource management is clearly required. Therefore, the need for evaluation of trawl codends used in this fishery and the potential improvements to their selectivity are of prime importance. In this paper, we use semi-empirical models to define selective properties of pelagic trawl codends targeting black mackerel (Trachurus spp) in theGulfofGuinea. These properties are determined using the experimental and theoretical methods of assessing the parameters of the selectivity curve, and by plotting the curve. Selection parameters were obtained by fitting a logistic equation using a maximum likelihood method. Trawl codend selectivity is estimated for 17 internal diamond mesh sizes in the range 47 - 79 mm. Using the basic selectivity equations, we determine the needed mesh size A = 58 mm for fishing mackerel in the gulf of Guinea. This nominal mesh size gives room for nj = 0.1 catch of juveniles, which not exceeds the allowable proportion [nj] = 0.1. To provide resource conservation, there is the need to make amendments in the fishery regulations for more rational exploitation of mackerel stoks, because the currently use nominal mesh size A = 56 mm is rather unselective.

Simulation of a DI Diesel Engine Performance Fuelled on Biodiesel Using a Semi-Empirical 0D Model

Diesel engines have proven over the years important in terms of efficiency and fuel consumption to power generation ratio. Many research works show the potential of biodiesel as a substitute for conventional gasoil. Mainly, previous and recent researches have focused on experimental investigation of diesel engine performance fuelled by biodiesel. Researches on the mathematical description of diesel engine process running on biodiesel are scarce, and mostly about chemical and thermodynamic description of the combustion process of biodiesel rather than performance studies. This work describes a numerical investigation on the performance analysis of a diesel engine fuelled by palm oil biodiesel. The numerical investigation was made using a semi empirical 0D model based on Wiebe’s and Watson’s model which was implemented via the open access numerical calculation software Scilab. The model was validated first by comparing with experimental pressure and performance data of a one cylinder engine at rated speed and secondly by comparing with a six cylinders engine performance data at various crankshaft rotational speeds. Simulations were then made to analyze the engine performance when running on biodiesel. The calculations were made at constant combustion duration and constant coefficient of excess air. Results showed that the model matches the overall experimental data, such as the power output and peak cylinder pressure. The ignition delay was somehow underestimated by the model for the first experiment, which caused a slight gap on in cylinder pressure curve, whereas it predicted the average ignition delay fairly well for the second set of validation. The simulations of engine performance when running on biodiesel confirmed results obtained in previous experimental researches on biodiesel. The model will be further investigated for engine control when shifting to biodiesel fuel.

Two-Stage Production Planning Under Stochastic Demand:Case Study of Fertilizer Manufacturing

Agriculture is a key facilitator of economic prosperity and nourishes the huge global population.To achieve sustainable agriculture,several factors should be considered,such as increasing nutrient and water efficiency and/or improving soil health and quality.Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effectiveness of crop yields.Fertilizer supplies most of the necessary nutrients for plants,and it is estimated that at least 30%-50%of crop yields is attributable to commercial fertilizer nutrient inputs.Fertilizer is always a major concern in achieving sustainable and efficient agriculture.Applying reasonable and customized fertilizerswill require a significant increase in the number of formulae,involving increasing costs and the accurate forecasting of the right time to apply the suitable formulae.An alternative solution is given by two-stage production planning under stochastic demand,which divides a planning schedule into two stages.The primary stage has non-existing demand information,the inputs of which are the proportion of raw materials needed for producing fertilizer products,the cost for purchasing materials,and the production cost.The total quantity of purchased material and produced products to be used in the blending process must be defined to meet as small as possible a paid cost.At the second stage,demand appears under multiple scenarios and their respective possibilities.This stage will provide a solution for each occurring scenario to achieve the best profit.The two-stage approach is presented in this paper,the mathematical model of which is based on linear integer programming.Considering the diversity of fertilizer types,themathematicalmodel can advise manufacturers about which products will generate as much as profit as possible.Specifically,two objectives are taken into account.First,the paper’s thesis focuses on minimizing overall system costs,e.g.,including inventory cost,purchasing cost,unit cost,and ordering cost at Stage 1.Second,the thesis pays attention tomaximizing total profit based on information from customer demand,as well as being informed regarding concerns about system cost at Stage 2.

Numerical Analysis of the Compression Ratio’s Influence, the Nature of the Fuel and the Injection Feed on the Cylinder Pressure

This article analyses numerically the simultaneous influence of the compression rate, fuel nature and the advanced injection of fuel on maximum cylinder pressure during the combustion phrase with the help of the Python Spyder calculation code. Indeed, several authors have shown that the combustion of biofuels which make it possible to compensate for fossil and exhaustible resources, presents a cylinder pressure higher by about 3.5% compared to that of conventional diesel D100. This increase in pressure can be reduced by the means of controlling parameters making it possible to preserve the life of the engine and also reduce nitrogen oxides (NOx) and particular matter (PM). This article has two objectives which are: putting in place a numerical tool for the evaluation and simulation of thermal engines and the influence of control parameters on cylinder pressure. The single zone 0D combustion model which considers only the physical phenomena and considers the mixed fuel as a perfect gas is used. The fuel used is the Neem biofuel produced by Doctor Merlin Ayissi of the University of Douala and the D100 diesel fuel. The results are obtained from three fuel injection angles of 20°, 13° and 10° before the TDC (Top Dead Centre) and three values of the engine compression rates of 15, 20 and 25. The delay in combustion is characteristic of the fuel used as illustrated by the cetane number. The results show that the cylinder pressure increases with increasing compression rate and a very high advanced injection. It also shows that the pressure is high when diesel D100 is used instead of D100 biodiesel.

Heuristic Scheduling of Job Orders in a Build-to-Order Manufacturing System

With the continuous development of technology,traditional manual work has been becoming more and more automated.Most large or medium-sized companies have applied Enterprise Resource Planning(ERP)software into their business and production activities.However,since many small firms cannot afford ERP because of its expensive cost,they often still employ manual work for the same tasks this software resolves,especially for scheduling.This paper aims to provide a possible solution for small businesses to try automated scheduling and discover whether it can help much.There are two main ways to make this determination:a mathematical model and a heuristic model,which are suitable for assessing low-and medium-sized workloads,respectively.This case study was carried out in a small domestic interior furniture company,particularly in scheduling for their customized products in two-stage flow shop.Normally,they produce according to the sequence of customers’orders.However,when we applied these supportive tools with batch-processing machines,they experienced enhanced production performance due to diminishing setup time for distinctive items and a more streamlined arrangement of job sequences.These changes were implemented for some small companies that do not use many production stages and have a suitable number of jobs and customers.If this method were applied to larger demands,it would need further improvement and development to become a complete tool that can perform like a part of an ERP system.

Scheduling Optimization Modelling:A Case Study of a Woven Label Manufacturing Company

Production scheduling involves all activities of building production schedules,including coordinating and assigning activities to each person,group of people,or machine and arranging work orders in each workplace.Production scheduling must solve all problems such as minimizing customer wait time,storage costs,and production time;and effectively using the enterprise’s human resources.This paper studies the application of flexible job shop modelling on scheduling a woven labelling process.The labelling process includes several steps which are handled in different work-stations.Each workstation is also comprised of several identical parallel machines.In this study,job splitting is allowed so that the power of work stations can be utilized better.The final objective is to minimize the total completion time of all jobs.The results show a significant improvement since the new planning may save more than 60%of lead time compared to the current schedule.The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process.The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries.A practical case study demonstrates the effectiveness of the proposed model.

Empirical Evidence of Natural Shocks, Risk Perceptions and Resilience from Cameroon

Invariably, it is the poorest of the poor who are mostly affected by perverse disasters, policies and laws. A major concern in disaster research is to explore the relationship between shock experiences and victims＇ perceptions of risk, as well as their possible effect on victims＇ behavior for resilience and adaptation. We explore this relationship on victimized households of the 1986 Lake Nyos disaster, employing a quasi-experimental design. Matching was done with non-affected households. Both groups affected and non-affected households were of adequate size, and subject to the same questionnaire. Selection of （470） test and matching households was purposely limited to nine of the ten towns accommodating both survivors and non survivors of the examined disaster. A list constructed with traditional rulers in each village allowed for random sampling of non victims for comparative analysis. We then compare households affected by the disaster with those who were not. The results reveal differentiated perceptions of risk and management behavior contingent on whether households experienced the shock or not. However, solidarity and reciprocity remained extremely high and not significantly different amongst both household types, suggesting resilience of endogenous, informal risk response mechanisms to natural shocks. The article concludes that analyzing risk perceptions can help explain why some individuals, households or communities may be resilient to shocks and others not. We argue for a combination of subjective perceptions and objective shock analysis, especially if the analyst hopes to influence policy.

Mathematical and Numerical Modelling of Copper Tube Extrusion after Optimizing Geometrical and Operating Parameters

This study aimed to optimize cross-sectional area of the extruder and the flow rate of the material through the extruder. Extrusion process was first modelized using the continuum mechanics method before being simulated with the commercial software LS-DYNA using the Johnson-Cook model based on the finite element method after optimization of the factors with simplex algorithm. The study was carried out on a connecting rod: diameter of 145 mm, cross-section of 1.65 m2, length of 0.25 m, volume of 0.41 m3 and a mass of 37 kg. Optimum parameters obtained were temperature of 850℃, flow rate of 0.237 m/s, die diameter of 19.2 mm, pin diameter of 14 mm, extrusion strength of 565.6 kN and press pressure of 245 GPa. From these factors, a blank was obtained with external and internal diameters of 19.2 and 14 mm respectively over a length of 28 m with a thickness of 2.6 mm. Simulation using LS-DYNA software resulted in a difference in values of 7.4% between optimization and simulation when the difference of 2.4% was found between modelling and simulation. These values make the process optimal for industrial application to improve the extrusion requirements of copper tubes.

螺旋榨油机榨螺螺纹体积计算的研究

计算螺旋榨油机压缩比的关键是计算榨螺的体积。研究圆柱根圆等截面圆柱榨螺体积的计算,将螺纹对应的圆心角M等分,得到M个计算单元。由于榨螺推料面倾角和背面倾角的存在,该计算单元的6个外表面中,有两个平面、有两个圆柱曲面片、还有两个不同的螺旋面。将榨螺螺纹高度沿径向N等分,计算出N个薄壁圆管曲面片段的体积即可得到计算单元的体积。用VC++6.0编程,根据输入的榨螺参数计算螺纹的体积和榨膛空余容积。

基于空间四边形单元的正螺旋面下料图设计方法

分析正螺旋面的空间尺寸特点,将计算下料方法和三角线法相结合,计算组成螺旋叶片的各个空间四边形单元的展开尺寸,将四边形单元的展开图依次拼接即可得到螺旋叶片的展开图。用VisualC++编程,能够快速、较精确地展开各种规格的正螺旋面(包括圆台形螺旋),绘制近似展开图。同时得到DXF文件,供AutoCAD直接调用以便输出下料图。最后给出了设计实例。

Crustal thickness beneath Atlas region from gravity,topographic,sediment and seismic data

The Atlas region in northwest Africa is characterized by the Quaternary volcanism and elevated topography with past complex tectonic mitigation between the African and European plates.Geodynamics of this atypical region has left indubitably imprints in crustal architectonics,mainly regarding the crustal thickness as well as the crustal density structure.The knowledge of crustal thickness variations is of a significant interest,since it provides a crucial constraint to geodynamic and geophysical modelling of this region.In this study,we use gravity,topographic,bathymetric and sediment data together with results of seismic surveys to image the Moho topography beneath the Atlas region.The Bouguer gravity anomalies used for a gravimetric Moho recovery are obtained from the free-air gravity anomalies after subtracting the gravitational contributions of topography,bathymetry and sediments.The regional gravimetric Moho inversion constrained on seismic data is carried out by applying a regularized inversion technique based on Gauss-Newton’s formulation of improved Bott’s method,while adopting Earth’s spherical approximation.The numerical result reveals relatively significant Moho depth variations in the Moroccan Atlas,with minima of approximately 24 km along continental margins of the Mediterranean Sea and maxima exceeding 51 km beneath the Rif Cordillera.The Moho depth beneath the West African Craton varies from 32 km in its southern margin to 45 km beneath the Middle Atlas.The Tell Atlas is characterized by the shallow Moho depth of approximately 22 km and further deepening to 42 km towards the northern edge of the Aures Mountains.Our findings indicate a limited tectonic shortening of the High Atlas with the crustal thickness mostly within 36-42 km.Topographic discrepancies between the Rif Cordillera and the Atlas Mountains suggest that the hypothesis of isostatic compensation cannot be fully established.

Optimization Model in Manufacturing Scheduling for the Garment Industry

The garment industry in Vietnam is one of the country’s strongest industries in the world.However,the production process still encounters problems regarding scheduling that does not equate to an optimal process.The paper introduces a production scheduling solution that resolves the potential delays and lateness that hinders the production process using integer programming and order allocation with a make-to-order manufacturing viewpoint.A number of constraints were considered in the model and is applied to a real case study of a factory in order to viewhowthe tardiness and latenesswould be affected which resulted in optimizing the scheduling time better.Specifically,the constraints considered were order assignments,production time,and tardiness with an objective function which is to minimize the total cost of delay.The results of the study precisely the overall cost of delay of the orders given to the plant and successfully propose a suitable production schedule that utilizes the most of the plant given.The study has shown promising results that would assist plant and production managers in determining an algorithm that they can apply for their production process.

Improving Supply Chain Performance Through Supplier Selection and Order Allocation Problem

Suppliers play the vital role of ensuring the continuous supply of goods to themarket for businesses.If businesses do not maintain a strong bond with their suppliers,they may not be able to secure a steady supply of goods and products for their customers.As a result of failure to deliver products,the production and business activities of the business can be delayed which leads to the loss of customers.Normally,each trading enterprise will have a variety of commodity supply chains withmultiple suppliers.Suppliers play an important role and contribute to the value of the entire supply chain.Should any supplier encounters a problem,the whole supply chain of businesses will be affected and could lead to not guaranteeing the stable supply to the market.Thus,suppliers can be seen as a threat to businesses where they have the ability to increase input prices or decrease the quality of the required products and services they provide.The quantity of the business,and the supply lead time directly affect the operations and reduce the profitability of the business.The paper mainly focuses on the supplier selection problemunder a variety of price level and product families when using a two-phase fuzzy multi-objective linear programming.The objectives of the proposed model are to minimize the total purchasing and ordering cost in order to reduce the quantity of defective materials and the late-delivery components from suppliers.Moreover,the piecewise linear membership function is applied in themodel to determine an optimal solution which is based on the requirement of decision makers under their fuzzy environment.The results of this study can be applied in various business environment and provide a reliable decision tool for choosing potential suppliers relating to these objectives.Based on the results,the company canmake a good decision on supplier selection;therefore,the company can improve the quality and quantity of their final product.This is because,the best supplier can supply raw material using just-in-time application and reduce production risk on the manufacturing process.

Scheduling Flexible Flow Shop in Labeling Companies to Minimize the Makespan

In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison.The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders.This study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple machines.Based on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big data.Both optimization programs are used in this study and compared to determine which method can better solve the company’s problems.The proposed algorithm is able to improve machine utilization with large-scale problems.