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.     

Analysis of flexible manufacturing systems with distinct repeated visits: DrQ

This article examines the performance effects caused by repeated part visits at the workstations of a flexible manufacturing system (FMS). Such repeated part visits to the same workstations are commonly associated with fixture changes for machining complex parts, reclamping, and remounting or reorienting them. Since each of the repeated visits to a workstation may require different processing requirements, the resulting queueing network does not have a product form solution. We therefore develop an approximate mean value analysis model for performance evaluation of an FMS that may produce multiple part types with distinct repeated visits. We provide numerical examples and validate the accuracy of our solution algorithm against simulation. These examples show that the proposed model produces accurate throughput and utilization predictions with minimal computational efforts. These examples reveal that increasing the total pallet population may result in a reduction of the aggregate throughput, and that the FMS's performance could be more sensitive to the mix of pallets and part routes than to the total number of pallets. Our model will be of use, in particular, when managers wish to control individual operations (e.g., to adjust individual operation times to achieve economic savings in tool wear and breakage costs) or to investigate the performance implications of route changes due to alternate assignments of particular manufacturing tasks to certain workstations.     

Towards operational cost minimization for cloud bursting with deadline constraints in hybrid clouds

In hybrid clouds, there is a technique named cloud bursting which can allow companies to expand their capacity to meet the demands of peak workloads in a low-priced manner. In this work, a cost-aware job scheduling approach based on queueing theory in hybrid clouds is proposed. The job scheduling problem in the private cloud is modeled as a queueing model. A genetic algorithm is applied to achieve optimal queues for jobs to improve the utilization rate of the private cloud. Then, the task execution time is predicted by back propagation neural network. The max–min strategy is applied to schedule tasks according to the prediction results in hybrid clouds. Experiments show that our cost-aware job scheduling algorithm can reduce the average job waiting time and average job response time in the private cloud. In additional, our proposed job scheduling algorithm can improve the system throughput of the private cloud. It also can reduce the average task waiting time, average task response time and total costs in hybrid clouds.     

A case study in FMS production planning and dispatching

The speedy development and extensive application of computers have helped play a significant role in a new technological revolution. The importance of FMS flexibility in producing a variety of products and adapting rapidly to customer requirements makes FMSs attractive. Further, FMSs are most appropriate for largevariety and medium- to high-volume production environments. However, the module of the FMS production planning system is not perfect. This paper focuses on a new scheme for FMS production planning and dispatching under the realistic assumptions promoted by a particular flexible manufacturing factory. Some practical constraints such as fixture uniqueness, limited tool magazine capacity, and a given number of pallets are considered. The simulation results indicate that the scheme provides a good production plan, according to the short-term plans from the MIS Department. Some conclusions are drawn and a discussion is presented.     

Batch sizes and lead-time performance in flexible manufacturing systems

Production lead-time performance in flexible manufacturing systems is influenced by several factors which include: machine groupings, demand rates, machine processing rates, product batching, material handling system capacity, and so on. Hence, control of lead-time performance can be affected through the manipulation of one or more of these variables. In this article, we investigate the potential of batch sizing as a control variable for lead-time performance through the use of a queueing network model. We establish a functional relationship between the two variables, and incorporate the relationship in an optimization model to determine the optimal batch size(s) which minimizes the sum of annual work-in-process inventory and final inventory costs. The nonlinear batch sizing problem which results is solved by discrete optimization via marginal analysis. Results show that batch sizing can be a cheap and effective variable for controlling flexible manufacturing system throughput.     

Optimal Routing in General Finite Multi-Server Queueing Networks

The design of general finite multi-server queueing networks is a challenging problem that arises in many real-life situations, including computer networks, manufacturing systems, and telecommunication networks. In this paper, we examine the optimal routing problem in arbitrary configured acyclic queueing networks. The performance of the finite queueing network is evaluated with a known approximate performance evaluation method and the optimization is done by means of a heuristics based on the Powell algorithm. The proposed methodology is then applied to determine the optimal routing probability vector that maximizes the throughput of the queueing network. We show numerical results for some networks to quantify the quality of the routing vector approximations obtained.     

Production Capacity of Flexible Manufacturing Systems with Fixed Production Ratios

Determining the production capacity of flexible manufacturing systems is a very important issue in the design of such systems. We propose an approach for determining the production capacity (i.e., the maximum production rate) of a flexible manufacturing system with several part types, dedicated pallets, and fixed production ratios among the different part types. We show that the problem reduces to the determination of a single parameter for which we propose an iterative procedure. Simulation or approximate analytical techniques can be used as the building block performance evaluation technique in the iterative procedure.     

Performance Analysis of Flexible Manufacturing Systems with a Single Discrete Material-Handling Device

We present an analytical model for performance prediction of flexible manufacturing systems (FMSs) with a single discrete material-handling device (MHD). This configuration of FMS is significant for many reasons: it is commonly found in industry, it simplifies material-handling control, it is amenable to analytical modeling, and it forms a building block for more complex systems. Standard queueing models are inadequate to analyze this configuration because of the need to take into consideration many nontrivial issues such as state-dependent routing, interference from the MHD, and the analysis of the MHD. To account for state-dependent routing, we develop an iterative method that is built around mean value analysis. To analyze the MHD interference, we use two queueing network models. In the first, we ignore queueing at the MHD but model the interference from the MHD by inflating the station service times. The second network models the queueing for the MHD and estimates the blocking (inflation) times needed for the first model. By iterating between the two networks, we are able to predict the performance of this configuration of FMS. Our analytical estimates are validated against discrete event simulation and shown to be quite accurate for initial system design.     

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase. For the required volume of products, we use integer programming to select the number of stations and the number of machines at each station and to allocate tasks to stations. We use queueing network analysis, which takes into account the mean and variance of processing times among different products to determine the necessary capacity of the material-handling system. We iterate between the two analyses to find the combined solution with the lowest costs. Work-in-process costs are also included in the analysis. Computational results are presented.     

Life cycle assessment comparison of wooden and plastic pallets in the grocery industry

Wooden and plastic pallets are used extensively in global trade to transport finished goods and products. This article compares the life cycle performance of treated wooden and plastic pallets through a detailed cradle‐to‐grave life cycle assessment (LCA), and conducts an analysis of the various phytosanitary treatments. The LCA investigates and evaluates the environmental impacts due to the resources consumed and emissions of the product throughout its life cycle. The environmental impacts of the pallets are compared on a one‐trip basis and a 100,000‐trips basis. Impact categories are chosen with respect to environmental concerns. The results show that on a one‐trip basis, wooden pallets with conventional and radio frequency (RF) heat treatment incur an overall carbon footprint of 71.8% and 80.3% lower, respectively, than plastic pallets during their life cycle; and in comparison with wooden pallets treated with methyl bromide fumigation, they incur 20% and 30% less overall carbon footprint. Theoretical calculations of the resource consumption and emissions of RF treatment of pallets suggest that dielectric technology may provide a lower‐carbon alternative to both current ISPM 15‐approved treatments and to plastic pallets. Methyl bromide fumigation (15.95 kg CO₂ equivalent [eq.]) has a larger carbon footprint than conventional heat treatment (12.69 kg CO₂ eq.) of pallets. For the 100,000‐trips basis, the differences are even more significant. The results recommend that wooden pallets are more environmentally friendly than plastic pallets, and conventional and RF heat treatment for wooden pallets is more sustainable than methyl bromide fumigation treatment.     

Redescription of Phacodinium metchnikoffi (Ciliophora, Hypotrichida): general morphology and taxonomic position.

Living and stained specimens of Phacodinium metchnikoffi, collected near Madrid, Spain, were studied under light microscopy. Infraciliature was stained using a silver-impregnation procedure. The somatic infraciliature is composed of a relatively small number of discontinuous kinetics, formed by groups of few kinetosomes (pallets). The buccal ciliature is composed of an adoral zone of membranelles and a paroral formation otherwise unknown in ciliates, with many short kineties, which lie on a rigid stem. We propose that P. metchnikoffi is a primitive hypotrich and, consequently, we present a new classification system for hypotrichs.     

Redescription of Phacodinium metchnikoffi (Ciliophora, Hypotrichida): General Morphology and Taxonomic Position

ABSTRACT Living and stained specimens of Phacodinium metchnikoffi , collected near Madrid, Spain, were studied under light microscopy. Infraciliature was stained using a silver-impregnation procedure. The somatic infraciliature is composed of a relatively small number of discontinuous kineties, formed by groups of few kinetosomes (pallets). The buccal ciliature is composed of an adoral zone of membranelles and a paroral formation otherwise unknown in ciliates, with many short kineties, which lie on a rigid stem. We propose that P. metchnikoffi is a primitive hypotrich and, consequently, we present a new classification system for hypotrichs.     

Broadening cell selection criteria with micropallet arrays of adherent cells.

A host of technologies exists for the separation of living, nonadherent cells, with separation decisions typically based on fluorescence or immunolabeling of cells. Methods to separate adherent cells as well as to broaden the range of possible sorting criteria would be of high value and complementary to existing strategies. Cells were cultured on arrays of releasable pallets. The arrays were screened and individual cell(s)/pallets were released and collected. Conventional fluorescence and immunolabeling of cells were compatible with the pallet arrays, as were separations based on gene expression. By varying the size of the pallet and the number of cells cultured on the array, single cells or clonal colonies of cells were isolated from a heterogeneous population. Since cells remained adherent throughout the isolation process, separations based on morphologic characteristics, for example cell shape, were feasible. Repeated measurements of each cell in an array were performed permitting the selection of cells based on their temporal behavior, e.g. growth rate. The pallet array system provides the flexibility to select and collect adherent cells based on phenotypic and temporal criteria and other characteristics not accessible by alternative methods.     

Environmental impacts of wooden,plastic, and wood-polymer composite pallet: a life cycle assessment approach

Purpose

Waste recycling is one of the essential tools for the European Union’s transition towards a circular economy. One of the possibilities for recycling wood and plastic waste is to utilise it to produce composite product. This study analyses the environmental impacts of producing composite pallets made of wood and plastic waste from construction and demolition activities in Finland. It also compares these impacts with conventional wooden and plastic pallets made of virgin materials.

Methods

Two different life cycle assessment methods were used: attributional life cycle assessment and consequential life cycle assessment. In both of the life cycle assessment studies, 1000 trips were considered as the functional unit. Furthermore, end-of-life allocation formula such as 0:100 with a credit system had been used in this study. This study also used sensitivity analysis and normalisation calculation to determine the best performing pallet.

Result and discussion

In the attributional cradle-to-grave life cycle assessment, wood-polymer composite pallets had the lowest environmental impact in abiotic depletion potential (fossil), acidification potential, eutrophication potential, global warming potential (including biogenic carbon), global warming potential (including biogenic carbon) with indirect land-use change, and ozone depletion potential. In contrast, wooden pallets showed the lowest impact on global warming potential (excluding biogenic carbon). In the consequential life cycle assessment, wood-polymer composite pallets showed the best environmental impact in all impact categories. In both attributional and consequential life cycle assessments, plastic pallet had the maximum impact. The sensitivity analysis and normalisation calculation showed that wood-polymer composite pallets can be a better choice over plastic and wooden pallet.

Conclusions

The overall results of the pallets depends on the methodological approach of the LCA. However, it can be concluded that the wood-polymer composite pallet can be a better choice over the plastic pallet and, in most cases, over the wooden pallet. This study will be of use to the pallet industry and relevant stakeholders.

     

A heuristic method to determine the number of pallets in a flexible manufacturing system with several pallet types

This article presents a new heuristic method, called PANORAMA, that enables the determination of an appropriate number of pallets of each type that should circulate in a flexible manufacturing system. Production and return-on-investment constraints are considered. Statistical results derived using data from three existing flexible manufacturing systems, as well as randomly generated data, demonstrate the accuracy of the heuristic proposed.     

Synaptic efficacy shapes resource limitations in working memory

Working memory (WM) is limited in its temporal length and capacity. Classic conceptions of WM capacity assume the system possesses a finite number of slots, but recent evidence suggests WM may be a continuous resource. Resource models typically assume there is no hard upper bound on the number of items that can be stored, but WM fidelity decreases with the number of items. We analyze a neural field model of multi-item WM that associates each item with the location of a bump in a finite spatial domain, considering items that span a one-dimensional continuous feature space. Our analysis relates the neural architecture of the network to accumulated errors and capacity limitations arising during the delay period of a multi-item WM task. Networks with stronger synapses support wider bumps that interact more, whereas networks with weaker synapses support narrower bumps that are more susceptible to noise perturbations. There is an optimal synaptic strength that both limits bump interaction events and the effects of noise perturbations. This optimum shifts to weaker synapses as the number of items stored in the network is increased. Our model not only provides a circuit-based explanation for WM capacity, but also speaks to how capacity relates to the arrangement of stored items in a feature space.     

The optimal configuration and workload allocation problem in flexible manufacturing systems

In this article we consider the problem of determining the minimum cost configuration (number of machines and pallets) for a flexible manufacturing system with the constraint of meeting a prespecified throughput, while simultaneously allocating the total workload among the machines (or groups of machines). Our procedure allows consideration of upper and lower bounds on the workload at each machine group. These bounds arise as a consequence of precedence constraints among the various operations and/or limitations on the number or combinations of operations that can be assigned to a machine because of constraints on tool slots or the space required to store assembly components. Earlier work on problems of this nature assumes that the workload allocation is given. For the single-machine-type problem we develop an efficient implicit enumeration procedure that uses fathoming rules to eliminate dominated configurations, and we present computational results. We discuss how this procedure can be used as a building block in solving the problem with multiple machine types.     

Cluster associative memory formation in a three-layer network of phase oscillators

A three-layer network model of oscillatory associative memory is proposed. The network is capable of storing binary images, which can be retrieved upon presenting an appropriate stimulus. Binary images are encoded in the form of the spatial distribution of oscillatory phase clusters in-phase and anti-phase relative to a reference periodic signal. The information is loaded into the network using a set of interlayer connection weights. A condition for error-free pattern retrieval is formulated, delimiting the maximal number of patterns to be stored in the memory (storage capacity). It is shown that the capacity can be significantly increased by generating an optimal alphabet (basis pattern set). The number of stored patterns can reach values of the network size (the number of oscillators in each layer), which is significantly higher than the capacity of conventional oscillatory memory models. The dynamical and information characteristics of the retrieval process based on the optimal alphabet, including the size of “attraction basins“ and the input pattern distortion admissible for error-free retrieval, are investigated.