Vehicle Travel Time Models for AGV Systems under Various Dispatching Rules

The design and evaluation of AGV-based material handling systems are highly complex because of the randomness and the large number of variables involved. Vehicle travel time is a fundamental parameter for solving various flexible manufacturing system (FMS) design problems. This article presents stochastic vehicle travel time models for AGV-based material handling systems with emphasis on the empty travel times of vehicles. Various vehicle dispatching rules examined here include the nearest vehicle selection rule and the longest idle vehicle selection rule. A simulation experiment is used to evaluate and demonstrate the presented models.     

Enriching the tactical network design of express service carriers with fleet scheduling characteristics

Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns nodes to hubs, determines arcs between hubs, and routes parcels through the network. Afterwards, fleet scheduling creates a schedule for vehicles operated in the network. The strong relation between flow routing and fleet scheduling makes it difficult to optimise the network cost. Due to this complexity, fleet scheduling and network design are usually decoupled. We propose a new tactical network design model that is able to include fleet scheduling characteristics (like vehicle capacities, vehicle balancing, and drivers’ legislations) in the network design. The model is tested on benchmark data based on instances from an express provider, resulting in significant cost reductions.     

Experimental investigation of an FMS due-date scheduling problem: Evaluation of machine and AGV scheduling rules

Although extensive research has been conducted to solve design and operational problems of automated manufacturing systems, many of the problems still remain unsolved. This article investigates the scheduling problems of flexible manufacturing systems (FMSs). Specifically, the relative performances of machine and automated guided vehicle (AGV) scheduling rules are analyzed against various due-date criteria. First, the relevant literature is briefly reviewed, and then the rules are tested under different experimental conditions by using a simulation model of an FMS. The sensitivity to AGV workload, buffer capacity, and processing-time distribution is also investigated to assess the robustness of the scheduling rules.     

Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.     

Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The model is based on a process‐level approach, accounting for all significant materials by their transformation processes (aluminum castings, polyethylene blow molding; etc.) and plant operation activities (painting; heating, ventilation, and air conditioning [HVAC], etc.) germane to VMA. Using quantitative results for these material/transformation process pairings, a percent‐by‐weight material/transformation distribution (MTD) function was developed that permits the model to be applied to a range of vehicles, both conventional and advanced (e.g., hybrid electric, light weight, aluminum intensive). Upon consolidation of all inputs, the model reduces to two terms: one proportional to vehicle mass and a plant overhead per vehicle term. When the model is applied to a materially well‐characterized conventional vehicle, reliable estimates of cumulative energy consumption (34 gigajoules/vehicle) and carbon dioxide (CO₂) emissions (2 tonnes/vehicle) with coefficients of variation are computed for the VMA life cycle stage. Due to the more comprehensive coverage of manufacturing operations, our energy estimates are on the higher end of previously published values. Nonetheless, they are still somewhat underestimated due to a lack of data on overhead operations in part manufacturing facilities and transportation of parts and materials between suppliers and vehicle manufacturing operations. For advanced vehicles, the material/transformation process distribution developed above needs some adjusting for different materials and components. Overall, energy use and CO₂ emissions from the VMA stage are about 3.5% to 4.5% of total life cycle values for vehicles.     

Impact of Updated Material Production Data in the GREET Life Cycle Model

The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model developed by Argonne National Laboratory quantifies the life cycle energy consumption and air emissions resulting from the production and use of light‐duty vehicles in the United States. GREET is comprised of two components: GREET 1 represents the fuel cycle of various energy carriers, including automotive fuels, and GREET 2 represents the vehicle cycle, which accounts for the production of vehicles and their constituent materials. The GREET model was updated in 2012 and now includes higher‐resolution material processing and transformation data. This study evaluated how model updates influence material and vehicle life cycle results. First, new primary energy demand and greenhouse gas (GHG) emissions results from GREET 2 for steel, aluminum, and plastics resins are compared herein with those from the previous version of the model as well as industrial results. A part of the comparison is a discussion about causes of differences between results. Included in this discussion is an assessment of the impact of the new material production data on vehicle life cycle results for conventional internal combustion engine (ICE) vehicles by comparing the energy and GHG emission values in the updated and previous versions of GREET 2. Finally, results from a sensitivity analysis are presented for identifying life cycle parameters that most affect vehicle life cycle estimates.     

A Loop Material Flow System Design for Automated Guided Vehicles

We develop an exact integer programming formulation to design a loop material flow system for unit-load automated guided vehicles. The model simultaneously determines both the design of the unidirectional loop flow pattern and the location of the pickup and delivery stations. The objective is to minimize the total loaded-vehicle trip distances. To solve the problem, we concentrate on developing a better formulation for the LP subproblem, preprocessing the problem, identifying the appropriate set of LP/IP routines, analyzing the mathematical properties of the problem, and developing an intelligent branch and bound solution procedure.     

Multi-Hop Routing Optimization Method Based on Improved Ant Algorithm for Vehicle to Roadside Network

This paper proposes a route optimization method to improve the performance of route selection in Vehicle Ad-hoc Network （VANET）. A novel bionic swarm intelligence algorithm, which is called ant colony algorithm, was introduced into a traditional ad-hoc route algorithm named AODV. Based on the analysis of movement characteristics of vehicles and according to the spatial relationship between the vehicles and the roadside units, the parameters in ant colony system were modified to enhance the performance of the route selection probability rules. When the vehicle moves into the range of several different roadsides, it could build the route by sending some route testing packets as ants, so that the route table can be built by the reply information of test ants, and then the node can establish the optimization path to send the application packets. The simulation results indicate that the proposed algorithm has better performance than the traditional AODV algorithm, especially when the vehicle is in higher speed or the number of nodes increases.     

Reducing greenhouse gas emissions of a heterogeneous vehicle fleet

Recent research on the vehicle routing problem attempts to integrate so-called “green” aspects into classical planning models. The minimization of transport-related emissions (especially CO₂) instead of driving distances is an important integration approach. Within this paper, we propose an approach which is focusing on the reduction of CO₂ emissions caused by transportation. Based on the observation that vehicles with different maximal payload values have different payload-dependent fuel consumption characteristics, we integrate into Dantzig’s classical vehicle routing model the option of choosing vehicles of different size for route fulfillment. Then, the Emission Minimization Vehicle Routing Problem with Vehicle Categories (EVRP-VC) is introduced. It aims at minimizing the fuel consumption, respectively CO₂ emissions instead of the driving distances. Comprehensive computational experiments with CPLEX are conducted to evaluate the EVRP-VC. A major finding is that the quantity of fuel needed to serve a given request portfolio can be reduced tremendously by using an inhomogeneous fleet with vehicles of different size.     

A comparative study of FMS tool allocation and part type selection approaches for a varying part type mix

Hankins and Rovito (1984) examined the impact of different tool policies on cutting tool inventory levels and spindle utilization for a flexible manufacturing system (FMS). This study provides a broader perspective of the impact of tool allocation approaches on flow times, tardiness, percent of orders tardy, machine utilization, and robot utilization. Part type selection procedures have been suggested for the FMS prerelease planning problem. However, very little research has specifically evaluated the part type selection procedures across different tool allocation approaches. Also, with the exception of Stecke and Kim (1988, 1991) no other known study has provided any insights on what tool allocation approaches are appropriate when processing different mixes of part types. This research is devoted to addressing those issues. Three tool allocation approaches, three production scheduling rules, and three levels of part mix are evaluated in this study through a similation model of a flexible manufacturing system. The specific impacts of the tool approaches, their interaction effects with the part type selection rules, and their effectiveness at different part type mix levels are provided through the use of a regression metamodel.     

Cooperation and Defection at the Crossroads

We study a simple traffic model with a non-signalized road intersection. In this model the car arriving from the right has precedence. The vehicle dynamics far from the crossing are governed by the rules introduced by Nagel and Paczuski, which define how drivers behave when braking or accelerating. We measure the average velocity of the ensemble of cars and its flow as a function of the density of cars on the roadway. An additional set of rules is defined to describe the dynamics at the intersection assuming a fraction of drivers that do not obey the rule of precedence. This problem is treated within a game-theory framework, where the drivers that obey the rule are cooperators and those who ignore it are defectors. We study the consequences of these behaviors as a function of the fraction of cooperators and defectors. The results show that cooperation is the best strategy because it maximizes the flow of vehicles and minimizes the number of accidents. A rather paradoxical effect is observed: for any percentage of defectors the number of accidents is larger when the density of cars is low because of the higher average velocity.     

Dynamics of HIV neutralization by a microbicide formulation layer: biophysical fundamentals and transport theory

Topical microbicides are an emerging HIV/AIDS prevention modality. Microbicide biofunctionality requires creation of a chemical-physical barrier against HIV transmission. Barrier effectiveness derives from properties of the active compound and its delivery system, but little is known about how these properties translate into microbicide functionality. We developed a mathematical model simulating biologically relevant transport and HIV-neutralization processes occurring when semen-borne virus interacts with a microbicide delivery vehicle coating epithelium. The model enables analysis of how vehicle-related variables, and anti-HIV compound characteristics, affect microbicide performance. Results suggest HIV neutralization is achievable with postcoital coating thicknesses approximately 100 mum. Increased microbicide concentration and potency hasten viral neutralization and diminish penetration of infectious virus through the coating layer. Durable vehicle structures that restrict viral diffusion could provide significant protection. Our findings demonstrate the need to pair potent active ingredients with well-engineered formulation vehicles, and highlight the importance of the dosage form in microbicide effectiveness. Microbicide formulations can function not only as drug delivery vehicles, but also as physical barriers to viral penetration. Total viral neutralization with 100-mum-thin coating layers supports future microbicide use against HIV transmission. This model can be used as a tool to analyze diverse factors that govern microbicide functionality.     

Impact of Parcel Size,Field Shape,Crop Yield,Storage Location,and Collection Equipment on the Performance of Single-Pass Cut-and-Chip Harvest System in Commercial Shrub Willow Fields

In this study, an integrated system of harvesting, collecting, and transporting willow biomass crop to a storage site was modeled and evaluated using the IBSAL simulation model. A scenario analysis was used to quantify the impacts of five major input parameters on the performance of the integrated system. These parameters include parcel size, field shape, willow yield, distance to the storage site, and type of the collection equipment. Multiple performance indicators were identified to quantify the impacts on the system such as size of the equipment fleet, effective material and field capacity of the harvester, operating costs, and waiting times. The input data were collected from 36 commercial, short-rotation, shrub willow fields in northern New York State. The simulation results indicated that crop yield and type of collection equipment have the highest impact on operating costs and the equipment fleet size. As the size of equipment fleet increases in the system, variability in the system performance tends to increase. Field shape has the least impact on the overall system performance compared to the other four input parameters. The simulation results suggest that a combination of performance indicators need to be considered to evaluate the overall performance of the dynamic and complex system of harvesting, collection and transportation in commercial willow fields. The developed IBSAL model and scenario analysis approach can assist in planning this system based on the characteristics of field, crop, and logistical equipment to reach a high system performance.     

Simultaneous determination of lot size and production rate at capacity-constrained multiple-product systems

In the capacity constrained manufacturing systems where multiple product types are manufactured, the products are often produced in lots. Although the lot production may increase the system throughput by reducing changeover times, it may also increase production lead time because each item in a large lot has a long waiting time. Hence, a production manager should consider both throughput and lead time at the same time when deciding production lot sizes. This paper, which is an extension to the previous work done in Koo et al. (2007) that assumes homogeneous setup times, addresses a lot sizing problem in the system with multiple product types and unequal setup times. We develop a non-linear optimization model for simultaneous determination of throughput rate and lot size for each product. Since this optimization model cannot be solved analytically, we propose a heuristic solution procedure by analyzing the characteristics of the problem. Some numerical examples are presented to validate the proposed model, and finally the performance of the heuristic procedure is evaluated by comparison with the results of simulation experiments.     

Regional assessment of local emissions of electric vehicles using traffic simulations for a use case in Germany

Purpose

In order to assess the global and local environmental impacts of different penetration rates of electric vehicles (EVs) within a region, we developed a life cycle approach based on a detailed traffic simulation assessing local emissions for individual roads with a high time resolution. The aim was to estimate the reduction potential of local emissions such as particulate matter within a region through a substitution of conventional with electric vehicles.

Materials and methods

The chosen approach assessing local emissions includes a detailed traffic simulation of a vehicle fleet composed of individual vehicles with a daily schedule. The driving pattern is modeled based on a survey of driving patterns in Germany. Incorporation of traffic density for each road and emissions of electric and conventional vehicles permits conclusions on the reduction potential for each street. Moreover, a feasible reduction potential for a particular region can be assessed. A case study for Aachen, Germany is presented within this paper. For the classification of the local emissions with the usual life cycle assessment approach, a comparison of EV, PHEV, and conventional vehicles has been conducted for Germany providing the results for impact categories according to CML 2001.

Results and discussion

Based on simulation results, an estimation of the reduction potential for Aachen for different penetration rates of electric vehicles including particulate matter (PM₁₀), carbon monoxide (CO), and nitrogen oxygen (NOx) is carried out. Electric vehicles possess the highest reduction potential for CO and NOx. Assuming 50?% of the total vehicle fleet in 2010 substituted by electric vehicles, local emissions of CO reduce by 46.6?%, for NOx by 38.8?%, and for PM₁₀ by 22.4?%. Due to fluctuations in driving patterns throughout a day, the results are highly time dependent. However, improvements in combustion engine technologies results in an increased reduction potential for conventional vehicles. The direct comparison between the vehicle types showed that the benefit of electric vehicles depends on the considered impact category.

Conclusions

Electric vehicles are able to reduce local emissions within a region. Moreover, this approach focusing on the use phase of vehicles within a regional assessment and the resulting local emissions as well as the detailed analysis of the driving behavior allows a distinguished assessment of the reduction potential of electric vehicles. Additionally, an assessment of policy measures such as drive restrictions for conventional vehicles can be simulated on the base of this approach.     

Vehicle dispatching for highly loaded semiconductor production considering bottleneck machines first

Semiconductor wafer fabrication lines can be characterized by re-entrant product flow, long production lead-time, large variety of production processes, and large capital investment. These distinctive characteristics make the flow control in the fab very complicated. Throughput rate and lead-time are among the most important performance measures. The throughput rate is usually determined by a bottleneck resource, and the lead-time depends on the machine utilization level and the amount of variability in the system. Due to the high efficiency of material handling and reduced particles, automated material handling systems such as automatic guided vehicles (AGVs), overhead hoist transporters (OHTs), and overhead shuttles (OHSs) are being widely used in wafer fabrication lines (wafer fabs) instead of human operators. Although a material handling system itself is seldom a bottleneck of production in a fab, it is important for that to effectively support the bottleneck machines to maximize the throughput and reduce production lead-time. This paper presents a vehicle dispatching procedure based on the concept of theory of constraints, in which vehicle dispatching decisions are made to utilize the bottleneck machines at the maximum level. Simulation experiments have been performed to compare the proposed vehicle dispatching procedure with existing ones under different levels of machine utilization, vehicle utilization, and local buffer capacity.     

A note on the selection of priority rules in software packages for project management

Various software packages for project management include a procedure for resource-constrained scheduling. In several packages, the user can influence this procedure by selecting a priority rule. However, the resource-allocation methods that are implemented in the procedures are proprietary information; therefore, the question of how the priority-rule selection impacts the performance of the procedures arises. We experimentally evaluate the resource-allocation methods of eight recent software packages using the 600 instances of the PSPLIB J120 test set. The results of our analysis indicate that applying the default rule tends to outperform a randomly selected rule, whereas applying two randomly selected rules tends to outperform the default rule. Applying a small set of more than two rules further improves the project durations considerably. However, a large number of rules must be applied to obtain the best possible project durations.     

Diffusive Public Goods and Coexistence of Cooperators and Cheaters on a 1D Lattice

Many populations of cells cooperate through the production of extracellular materials. These materials (enzymes, siderophores) spread by diffusion and can be applied by both the cooperator and cheater (non-producer) cells. In this paper the problem of coexistence of cooperator and cheater cells is studied on a 1D lattice where cooperator cells produce a diffusive material which is beneficial to the individuals according to the local concentration of this public good. The reproduction success of a cell increases linearly with the benefit in the first model version and increases non-linearly (saturates) in the second version. Two types of update rules are considered; either the cooperative cell stops producing material before death (death-production-birth, DpB) or it produces the common material before it is selected to die (production-death-birth, pDB). The empty space is occupied by its neighbors according to their replication rates. By using analytical and numerical methods I have shown that coexistence of the cooperator and cheater cells is possible although atypical in the linear version of this 1D model if either DpB or pDB update rule is assumed. While coexistence is impossible in the non-linear model with pDB update rule, it is one of the typical behaviors in case of the non-linear model with DpB update rule.     

A model for the minimum cost configuration problem in flexible manufacturing systems

This paper presents a mathematical programming model to help select equipment for a flexible manufacturing system, i.e., the selection of the types and numbers of CNC machines, washing stations, load/unload stations, transportation vehicles, and pallets. The objective is to minimize equipment costs and work-in-process inventory cost, while fulfilling production requirements for an average period. Queueing aspects and part flow interactions are considered with the help of a Jacksonian-type closed queueing network model in order to evaluate the system's performance. Since the related decision problem of our model can be shown to be NP-complete, the proposed solution procedure is based on implicit enumeration. Four bounds are provided, two lower and two upper bounds. A tight lower bound is obtained by linearizing the model through the application of asymptotic bound analysis. Furthermore, asymptotic bound analysis allows the calculation of a lower bound for the number of pallets in the system. The first upper bound is given by the best feasible solution and the second is based on the anti-starshaped form of the throughput function.